OnlineCyberTools MCP (280+ filterable tools)

Server Quality Checklist

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Latest release: v0.5.1
Disambiguation2/5
Many tools have overlapping or very similar purposes (e.g., multiple base converters, hash generators, text statistics tools). Even with detailed descriptions, the sheer volume of similar tools makes it difficult for an agent to select the correct one.
Naming Consistency3/5
Within categories, naming follows a pattern (e.g., conversion_*, crypto_*, encoding_decoding_*), but across categories there is mixed use of snake_case and camelCase, and some names are ambiguous (e.g., 'process', 'run'). Overall inconsistent.
Tool Count1/5
262 tools is far too many for a coherent tool set. The server appears to be a collection of every possible utility, leading to bloat and making navigation impractical for an agent.
Completeness3/5
Given the broad scope, the set covers most common operations across many domains. However, some specific sub-areas may have gaps, and the emphasis on quantity over completeness is apparent.
Average 4.7/5 across 245 of 262 tools scored. Lowest: 3.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 10 commits in the last 12 weeks
- Last stable release on June 3, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description describes a read-only DNS lookup, but annotations set readOnlyHint=false, indicating a contradiction. Per rules, a contradiction yields a score of 1. The description otherwise adds useful behavioral context (e.g., rate limits, remote worker, no auth), but the contradiction overrides.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening, alternative tool mention, and behavioral details. It is slightly lengthy but every sentence adds value. Front-loading the purpose and sibling differentiation is effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single lookup with 3 parameters) and presence of output schema, the description covers all necessary context: usage scope, behavioral notes (DNS query, remote worker, rate limits, CAPTCHA), and authentication requirements. No gaps are apparent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed parameter descriptions. The description adds minimal extra meaning (e.g., clarifying action is only lookup and domain is prepended with _dmarc.), but does not significantly enhance understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Look up and validate a domain's DMARC policy by making a live DNS TXT query', specifying the verb, resource, and method. It also explicitly distinguishes from sibling tools like SPF and MX record checkers, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: 'Use network_spf_record_checker instead for SPF/Sender-Policy records or network_mx_record_lookup for mail-server MX records; this tool only resolves DMARC', including an alternative tool mention and scope limitation (single action=lookup).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations set readOnlyHint: false, implying potential side effects, but the description describes a purely read-only operation (lookup). This is a direct contradiction between annotations and description, which misleads the agent about safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is front-loaded with title and type, and all sentences add value. It is concise yet comprehensive without being verbose, though could be slightly more structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of output schema and annotations, the description covers usage, limitations (DNS changes, rate limits), security considerations (CAPTCHA, worker), and alternatives, providing complete context for agent decision.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are already well-documented. The description adds examples and validation hints but does not significantly enhance meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it performs reverse DNS lookup (PTR/IP to hostname) and distinguishes it from forward DNS and WHOIS lookups. The verb 'resolve' and resource 'IP address' are specific, and the description explicitly names sibling tools for comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use this tool (reverse DNS) and when not: 'use network_dns_lookup for forward records' and 'network_whois for registration/ownership data'. Provides clear context and alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses up to 25 ranked matches but does not mention case sensitivity, error handling, or any rate limits. Adequate but could be more detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and key details. No fluff; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (1 parameter, no output schema), the description fully explains what the tool returns and its constraint (25 results). No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter description already matching the tool description's semantics. The tool description does not add additional meaning beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states keyword search across the Online Cyber Tools catalogue. Specifies return fields (URL, API URL, description, category) and limit of 25 ranked matches. Distinct from siblings which are mostly specific conversion/encoding tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies use for general search but does not explicitly compare with alternatives or provide when-to-use/not-to-use guidance. No exclusions or alternative tool names mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It discloses that the operation is fetching guidance (read-only), but it does not mention potential failure modes, authentication requirements, or rate limits. The description is minimally adequate for a straightforward fetch operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, each serving a clear purpose: stating the action and providing input examples. It is front-loaded and contains no redundant words, achieving maximum efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one parameter, no output schema), the description is mostly complete. It explains the purpose and input format. It could optionally describe the output (e.g., 'returns the guidance text'), but the phrase 'full ... page guidance' implies a textual response, making it sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the parameter as 'Menu ID or MCP tool name to describe.' The description adds concrete examples ('ping', 'network_ping'), which clarify the expected format beyond the schema description. This adds value given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Fetch' and clearly identifies the resource as 'the full Online Cyber Tools page guidance for a tool.' This distinguishes it from sibling tools, which are actual tool implementations (e.g., conversions, crypto) rather than meta-documentation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides examples of acceptable inputs ('menu ID such as `ping` or an MCP tool name such as `network_ping`'), which aids usage, but it does not explicitly state when to use this tool versus alternatives like the 'search' sibling tool. More explicit guidance on selecting this tool would improve the score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds key behavioral details beyond annotations: validation, warnings, no disk writes, no privileges. Aligns perfectly with readOnlyHint and idempotentHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with purpose but contains redundant enumeration of unit types across multiple sentences. Could be more concise; the cut-off also suggests it's overly long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all essential aspects: operations, unit types, warning behavior, and non-destructive nature. Output schema exists, so return format isn't needed. Completeness is high despite minor redundancy.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% with descriptions. The tool description adds context about validation and warnings, and maps sections to objects, providing extra value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates systemd unit files from structured fields. It distinguishes from siblings like linux_ssh_config_generator, though the sibling list is broad. The cut-off at the end slightly reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Describes two operations (generate/presets) and emphasizes it never writes to disk or runs systemctl, guiding safe usage. However, it doesn't fully articulate when to use alternatives beyond the truncated mention of linux_ssh_con.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Contradiction with annotations: description claims 'non-destructive and read-only with respect to this service', but annotations set readOnlyHint=false. This inconsistency undermines transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with purpose, then clear usage guidance, then behavioral details, all in a compact paragraph. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (live network call, rate limits, third-party dependency), the description covers purpose, usage, behavior, parameters, limitations, and return value. Output schema exists but description already mentions returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds validation details (rejected private/reserved/loopback hosts, 255-byte cap) beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb 'Whois Lookup' and resource 'domain name or public IP address' clearly state what the tool does. Distinguishes from siblings like osint_domain_age, network_dns, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (ownership, registrar, registration-record data) and provides alternatives (osint_domain_age, network_dns, network_reverse_dns, network_asn_lookup) with clear reasons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint, destructiveHint, idempotentHint, openWorldHint. Description adds that it never executes commands, is read-only, non-destructive, and rate-limited. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured and front-loaded, but slightly verbose and has a cut-off trailing phrase. Could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers overall functionality, safety, and return types (though cut off). Given complexity and presence of output schema, description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. Description provides high-level context but doesn't add meaning beyond schema for individual parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool builds Linux/FreeBSD user/group admin command lines, parses /etc/passwd and /etc/group, and audits for problems. It distinguishes from sibling linux_command_builder by specifying it is for account management only.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use linux_command_builder instead for general commands. Also mentions rate limits. Lacks explicit when-not-to-use beyond sibling differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description reinforces by stating the tool 'only BUILDS config text' and 'never writes files, edits a live server, reloads, or restarts anything.' This adds meaningful context beyond annotations, though it could mention more about idempotency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the purpose and provides a comprehensive overview. It could be slightly more concise, but the structure is logical and covers capabilities, constraints, and alternatives without excessive verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (14 parameters, nested objects, output schema), the description covers all major features (TLS, reverse proxy, PHP, static, security headers, error pages, logging) and the two modes. The output schema exists, so return values are not required. It feels complete for the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description does not need to explain parameters extensively. It mentions a few key constraints (requires serverName for generate) but does not add significant new meaning beyond what is already in the input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates configuration text for Apache, Nginx, and Caddy web servers. It specifies the exact output (VirtualHost, server block, Caddyfile) and explicitly distinguishes from sibling tools like linux_htaccess_generator and linux_ssh_config_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (for full virtual-host or server-block files) and when to use alternatives (linux_htaccess_generator for .htaccess, linux_ssh_config_generator for SSH config). It also explains the two modes (generate and presets) and prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist beyond the title, so the description carries the full burden. It discloses that the tool reads barcodes from camera or image, auto-detects, or allows region selection. It is a read-only operation with no destructive behavior. It could mention privacy (e.g., not storing images) but is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences front-load the purpose and provide key details (supported formats, input methods, features). No unnecessary information; each sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks information about the output format (e.g., decoded text, raw data). Given no output schema, this gap is notable. It also does not mention the sibling 'osint_barcode_generator' for contrast. However, for a simple scanner, the core purpose is clear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 defined parameters (additionalProperties: true), so schema coverage is 100%. The description implicitly defines the input (camera or file) without formal parameters. Since no parameters are needed, the description adds sufficient meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a barcode and QR code scanner, lists many supported formats (UPC, EAN, Code 128, etc.), and indicates it works from camera or image file. This distinguishes it from the sibling 'osint_barcode_generator' which generates barcodes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the input methods (camera or image file) and provides guidance on auto-detection or manual region selection. However, it does not explicitly state when not to use this tool or compare it with alternatives like 'osint_qr_code_generator' or other scanners.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden. It discloses the hard rate limit, a key behavioral constraint. It does not mention success/failure response or side effects, but for a straightforward submission tool, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, no redundant words, and front-loaded with the core purpose. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the purpose and a constraint (rate limit), but omits information about what happens after submission (e.g., confirmation, ticket ID). With no output schema, the agent is left guessing the response format. This is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for all 6 parameters. The description adds no extra parameter information beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'File a bug report against one of the tools,' specifying a concrete verb and resource. It distinguishes from sibling tools that perform conversions, encoding, or transformations, none of which are bug-reporting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'only when you have concrete reproduction details,' and warns about the hard rate limit. This tells the agent not to waste attempts on vague reports and sets expectations for frequency.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses randomness of output, read-only nature, pure local compute, and rate limiting (60 req/min for anonymous). Annotations already indicate readOnlyHint=true and destructiveHint=false, and the description adds valuable behavioral context without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, starting with purpose, then details, then sibling comparison, then behavioral notes. Every sentence adds value, though it could be slightly more concise by merging some sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 params, enums, output schema), the description covers generation behavior, output content (text + stats), and constraints (randomness, rate limit). It is complete for selecting and invoking the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 4 parameters. The description adds minimal additional semantics beyond enumerating themes and formats already available in the schema. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates themed Lorem Ipsum placeholder text with specific vocabularies and formats. It explicitly differentiates itself from sibling tool text_lorem_ipsum by mentioning themed vs plain and output format differences.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool (when you want a non-Latin themed vocabulary) and when to use the sibling tool text_lorem_ipsum (for plain Lorem Ipsum with HTML list output). This is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds valuable context: local execution, no external service contact, rate limits (30 req/min for anonymous). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph of 4 sentences, covering purpose, alternatives, and behavior. It is well-structured and front-loaded, but slightly verbose in listing all behavioral traits.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 7 parameters and an output schema. The description explains the core transformation, usage guidance, and behavioral traits. It does not explain return values (handled by output schema). Complete enough for informed usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description does not need to add parameter details. The description provides high-level overview but does not repeat or augment schema info. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool generates TypeScript interfaces/types from JSON, with details on recursive inference, nested interfaces, and union types. It distinguishes from siblings by naming alternative tools for different tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear when-to-use guidance (convert JSON to TS types) and explicitly lists alternatives (JSON Schema generator, CSV converter, formatter), helping the agent choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds that it runs locally, is non-destructive, contacts no external service, and has a rate limit (60 requests/minute). This extra context is valuable and consistent with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-organized: purpose first, then mode/precision details, then usage guidance, and finally behavioral notes. It is informative but slightly verbose; could be tightened without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, output exists), the description covers all necessary aspects: modes, precision, input format, special-case detection, and return value (full bit breakdown). It also distinguishes from siblings, providing a complete contextual picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for all 4 parameters. The description largely restates the enums and parameters (mode, precision, inputFormat) but adds little new semantics beyond tying them to usage context. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts between decimal and IEEE 754 binary floating-point, specifying modes (decimal-to-ieee754, ieee754-to-decimal) and precision. It also contrasts with sibling tools like conversion_base_converter and conversion_binary_decimal, making the purpose distinct and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool (need exact bit layout, exponent, special cases) and when to use alternatives (conversion_base_converter for integer radix, conversion_binary_decimal for signed/unsigned integers). Also notes it runs locally and is read-only, providing clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent. Description adds rich behavioral context: local execution, rate-limited, in-memory processing, no persistence or logging, and key handling details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph with dense information, front-loaded with main action. Could be improved with bullet points for readability, but not excessive.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, behavioral notes, supported algorithms, key/output formats, and security. Output schema exists, so return details are not needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions. The description adds overall context but does not significantly enhance individual parameter meaning beyond examples and return format explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'HMAC Generator (Keyed Hash)' and explains it computes an HMAC for authentication. It explicitly distinguishes from crypto_hash for unkeyed digests.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: 'Use this when a shared secret must be involved' and 'use crypto_hash instead for an unkeyed digest with no secret', naming the alternative sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnly, idempotent, non-destructive), description adds local execution, deterministic behavior, no external service contact, rate limiting, and return of variant and notes. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is information-dense but well-structured with clear sentences. Slightly verbose for some readers, but each sentence adds meaningful context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given rich annotations and expected output schema, description covers all key aspects: input formats, variants, use-case distinction, and behavioral properties. No missing information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed parameter descriptions. Description adds minimal extra value beyond mentioning default variant, but serves as reinforcement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly defines the tool as computing Keccak digests for text/hex/base64 inputs, with specific mention of Ethereum/blockchain use. Distinguishes from crypto_sha3_generator by highlighting the 0x01 vs 0x06 padding difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs when to use this tool (Ethereum/blockchain-compatible Keccak) versus crypto_sha3_generator (NIST-standard SHA-3), providing clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, and idempotentHint. The description adds useful context: runs locally, contacts no external service, rate-limited (60/min), and is non-idempotent. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded with the core purpose. It covers key details without excessive verbosity. Slight redundancy in mentioning formatting twice, but generally well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (implied by description mentioning return arrays), the description covers runtime behavior, rate limits, idempotency, and local execution. It is complete for a straightforward generation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter well-described in the schema. The description adds high-level context (e.g., version 1 is time-based, version 4 random) but does not significantly enhance understanding beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it's a UUID generator for v1 and v4 with optional formatting. It specifies the verb 'Generate' and the resource 'RFC 4122 UUIDs'. This distinguishes it from the sibling tool 'data_uuid_validator' which validates/decodes UUIDs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('mint fresh identifiers for databases, API keys, or test fixtures') and when not to ('use data_uuid_validator instead to validate or decode an existing UUID'). It also mentions the tool runs locally, is read-only, non-destructive, and rate-limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds details about built-in checksum, offline operation, and length/byte analysis, complementing annotations (readOnlyHint, idempotentHint) without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise single paragraph with front-loaded purpose and useful detail; slightly redundant in repeating 'Bubble Babble' but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Completely covers purpose, usage, alternatives, behavioral traits, and return value (converted result plus analysis); output schema further reduces need for return details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Description explains the effect of 'operation' (encode/decode) and 'format' (text/hex/binary) beyond the schema, including how inputs are interpreted, adding value despite high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool is an encoder/decoder for Bubble Babble, gives example usage ('xexax'), and explicitly contrasts with sibling tool encoding_decoding_base64, differentiating when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit alternative (base64) and mentions local, read-only, non-destructive, offline, and rate-limited behavior, but lacks more detailed when-not-to-use guidance beyond the base64 comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive. Description adds valuable context: no external contact, structural/arithmetic only, rate-limited (20 req/min). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with core purpose, then details. Slightly verbose but every sentence adds value. Well-structured for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers input, validation process, limitations (no external contact), rate limits, sibling alternative, and output format (mention of result array and summary). Output schema exists so fine to skip details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers parameters fully (100% coverage). Description adds meaning: ibans accepts multiple entries separated by newlines, ignores spaces, uppercases, and iban is a convenience alias. Also explains validation logic.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it validates and decodes IBANs offline, checking country code, length, BBAN structure, and check digits. It distinguishes itself from the sibling osint_bic_swift_validate, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises using osint_bic_swift_validate for BIC/SWIFT validation, implying when not to use this tool. Context about offline validation is clear, but no exhaustive list of when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds useful behavioral context beyond annotations: it discloses local pure-JS implementation, read-only/non-destructive nature, no external service contact, rate limiting (30 req/min), and explicit now parameter for deterministic behavior. Annotations already indicate read-only and idempotent, so the description provides additional detail without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately long but well-structured with a clear front-loaded purpose statement and logical flow. Every sentence adds value, although it could be slightly more condensed without losing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (six operations, nested parameters, output schema exists), the description covers all necessary aspects: what operations do, when to use, behavioral traits, parameter semantics, and return structure. It is complete enough for an AI agent to understand and select the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds extra meaning beyond the schema, such as explaining that 'now' parameter ensures deterministic output by not reading the clock, and clarifying the behavior of exp/nbf deltas in assembleClaims. This provides enough value to raise the score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'JWT Decode, Validate, Sign and Claim Builder' and lists six specific operations. It explicitly differentiates from the sibling tool encoding_decoding_jwt by noting that this tool also verifies HMAC signatures and builds claims, providing a specific verb+resource with sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes explicit guidance on when to use this tool versus the sibling encoding_decoding_jwt, and states limitations for asymmetric algorithms (decoded but not verified/signed server-side). However, it does not provide explicit 'when-not-to-use' or alternatives for asymmetric operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds that it runs locally, is read-only, non-destructive, contacts no external service, and is rate-limited, providing useful behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is informative but not overly verbose; three sentences cover purpose, usage, and output. Slightly long but each sentence is valuable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 params, output schema), the description covers purpose, guidelines, behavior, and return value (detected MIME, dimensions, snippets). No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions for all 6 parameters. Description provides slight additional context (e.g., accepting full data URI, default fileName), but baseline is 3 due to high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool encodes base64 images, sniffs MIME type and dimensions, and emits code snippets. It explicitly distinguishes from siblings like webdev_data_uri_generator and file_base64_file_encoder.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use (embeddable code for raster images) and when not (use webdev_data_uri_generator for text/SVG, file_base64_file_encoder for non-image files).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds value by stating it runs locally, is read-only, non-destructive, contacts no external service, is rate-limited, and details return values (braille string, ASCII-braille, stats, reference). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph with no redundant information. It front-loads the core purpose and then adds necessary details about usage, behavior, and output. Every sentence is meaningful and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (two grades, encode/decode, output structure) and the existence of an output schema, the description fully explains what the tool does, its limitations (not certified), behavior (local, rate-limited), and return value structure. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters (text, operation, grade) with descriptions and examples. The description does not add additional parameter-level detail but provides context for the overall function. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a Braille Converter for Grade 1 & 2, converting between text and Unicode Braille patterns. It differentiates from sibling converters by specifying grades and use cases (preview/education aid), making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use: 'preview how labels, signage, or short copy render in braille cells' and 'read back braille into Latin text.' It also clarifies it is not for certified transcriptions (textbook/Nemeth/music), providing clear context. It does not mention alternatives among siblings but is sufficiently precise.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that the tool runs locally, is read-only, non-destructive, offline, no auth, and has a default rate limit. It also explains the return value includes a per-step breakdown. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that is information-dense and front-loads the main purpose. It could be slightly more structured, but it is concise and covers essential points without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters, nested objects, and an output schema, the description adequately covers the tool's behavior and return format. It mentions the step-by-step conversion breakdown, which adds value beyond the schema. However, the description could be more structured for complex parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds context about step-by-step breakdown and fixed-width handling but does not significantly enhance parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool converts a whole number between decimal and hexadecimal in either direction, with details on signed/unsigned, bit widths, and hex formatting. It clearly distinguishes from siblings by listing alternative tools for other conversions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('Use this when you need decimal-hex specifically with a step-by-step breakdown and fixed-width signed handling') and lists specific alternatives for other conversion needs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, and idempotentHint. The description reinforces these with 'read-only, non-destructive, offline, no auth' and adds that it returns a converted string plus an analysis block. This adds context beyond the annotations without contradiction. Slight deduction because some behavioral traits (e.g., exactly what the analysis block contains) are not detailed, but the description is sufficient given annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with the core purpose, followed by usage guidance and behavioral context. Every sentence earns its place with no redundancy or wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters (100% schema coverage), no nested objects, and an existing output schema, the description covers the tool's purpose, usage scope, behavioral traits, and return structure (converted string + analysis block). It is fully complete for an agent to understand how and when to use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description does not add significant meaning beyond the schema; it mentions that decimal/octal values must be 0-1114111, which is already in the schema's from_format description. No additional parameter details are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts between five textual encodings (ASCII, binary, hex, decimal, octal) as sequences of byte/codepoint values. It distinguishes from siblings like conversion_base_converter (single integer arbitrary radix), conversion_binary_decimal (signed/unsigned with bit width), and conversion_decimal_hex (two's complement). The verb 'convert' and the specific resource (five encodings) are explicitly defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('when you need to move character data across base representations') and when not to, naming three specific alternatives. It also notes that the tool runs locally, is read-only, offline, requires no auth, and has default rate limits, helping the agent understand invocation context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, and idempotentHint. The description adds valuable context: 'Runs locally on the input you provide: read-only, non-destructive, contacts no external service, and is rate-limited.' This goes beyond annotations, though the core behavioral traits are already covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences, concise and front-loaded. It starts with the core purpose, then usage guidance, then behavioral traits, then return values. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (dictionary attack, multiple options), the description covers purpose, usage, behavioral traits, and explicitly lists the return fields (match found, recovered password, detected hash type, attempts, elapsed seconds). This is complete for an agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for each parameter (hash, type, dictionary, useCommonPasswords). The description does not add additional semantics beyond summarizing the process (dictionary + built-in list). Baseline 3 is appropriate as the schema already documents parameters well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Hash cracker (dictionary attack). Recover the plaintext behind a password hash by testing it against a wordlist'. It distinguishes itself from sibling tools like crypto_hash_identifier and crypto_password_strength by specifying when to use them instead, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is given: 'Use it to audit weak hashes; run crypto_hash_identifier first if the algorithm is unknown, and crypto_password_strength to score a password you already have.' This tells the agent when to use this tool and when to use alternatives, fulfilling the dimension perfectly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds detail beyond annotations: randomness, seed reproducibility (with caveat about generatedAt), local execution, read-only nature, and rate limiting. Consistent with annotations (readOnlyHint=true, idempotentHint=false) and enriches agent understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with purpose, well-organized into purpose, usage comparison, and behavioral notes. However, it is somewhat verbose and includes redundant information (e.g., field types already in schema). Minor truncation at end does not impair clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, input structure, field types, behavioral traits, and alternatives. Output format is mentioned as 'grouped by path' and output schema provides complete structure. Truncation of final sentence ('rate-li') slightly reduces completeness but core information is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage, so the description adds little new parameter information. It summarizes field types and endpoint structure, but these are already detailed in the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates mock REST APIs from JSON schema with multiple endpoints. It explicitly distinguishes itself from sibling tools (data_faker, data_random_data_generator, data_sample_data_generator) by naming them and describing their different use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: 'Use this when you need multi-endpoint API fixtures keyed by route' and lists three specific alternatives with concise descriptions of when to use each.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds valuable behavioral context: 'Runs locally on the numbers you provide: read-only, non-destructive, contacts no external service, and is rate-limited (60 requests/minute).' It also details the output for the solve operation, which is not in annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at 8 sentences, front-loaded with purpose, structured by operation, and every sentence adds value. It covers purpose, operations, outputs, usage guidance, and behavioral traits without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has three operations and 7 parameters. The description explains all operations, required parameters per operation, degenerate cases (a=0), output details, and behavioral traits. It is completely adequate given the schema and annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds high-level context about which operation uses which parameters but does not deepen the meaning of individual parameters beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it solves quadratic equations, evaluates f(x), and builds monic quadratics from roots. It explicitly distinguishes from sibling tools math_scientific_calculator and math_matrix_calculator, which prevents confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use instructions: 'Use this for second-degree polynomial algebra; use math_scientific_calculator for general expression evaluation and math_matrix_calculator for linear algebra.' It also explains the three operations and their required parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds useful context beyond that: it mentions the tool is read-only, non-destructive, uses an in-memory table (no external service), and has rate limits (30 req/min, 180/hr). This adds value but the annotations already cover core safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: it starts with the core purpose, then details filtering capabilities, provides usage contrast, and ends with behavioral and rate-limit info. Every sentence contributes value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description explicitly lists what is returned (service name, description, security note, full match list, display slice, summary counts), ensuring the agent understands the response structure. It covers all key aspects for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add significant new meaning beyond what the parameter descriptions provide; it restates or summarizes them. No added depth.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'TCP/UDP Port Reference Lookup' and explicitly contrasts with network_port_scanner for probing live hosts, making its unique function unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use this tool ('offline port-number and service identification') and when not to ('use network_port_scanner instead to probe a live host for actually-open ports'), including a named alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true and destructiveHint=false. The description adds valuable behavioral context: SSE streaming format, outbound probe sending, worker/clamping behavior, and rate limits. It does not contradict annotations and provides additional detail beyond structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: it starts with the core function, then provides key behavioral details, usage guidance, and rate limits in a logical order. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a live traceroute tool, the description covers the streaming nature, network effects, rate limits, worker behavior, and parameter clamping. It also describes the SSE event types, providing sufficient context for an AI agent to understand the tool's behavior and outputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters have descriptions in the input schema (100% coverage). The tool description adds minimal extra meaning, only briefly mentioning clamping behavior already documented in the schema. Baseline of 3 is appropriate as schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs a live traceroute to a target host, streaming results hop-by-hop via SSE. It distinguishes from the sibling network_ping by specifying that this tool is for full path information, while network_ping is for single round-trip measurements.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use this tool vs network_ping, highlights that results vary between calls due to live network state, and mentions CAPTCHA and rate limits. It also notes the preferred use of a remote worker with local fallback.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, idempotentHint. Description adds valuable operational context: runs locally (no external BIN-lookup), is rate-limited at 60 req/min for anonymous callers, and is for test/reference data only. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences perfectly structured: first sentence defines purpose and core functionality, second adds disclaimer and alternatives, third covers behavioral traits and outputs. No redundant text; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (Luhn check, issuer detection, length/formatted output), the description covers all necessary aspects. It mentions the return fields (validity, card type, issuer, length, formatted number, warnings). Output schema exists, so explanation of return format is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with a clear parameter description (card_number with stripping of non-digits, length constraints). The description does not add additional meaning beyond the schema, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it validates credit card numbers via Luhn checksum, identifies issuing network, and returns brand-specific checks and formatted number. It explicitly lists alternative sibling tools for other identifier types, making the purpose and scope unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use (for credit card validation) and when not to (does not verify real/funded cards). It names alternative tools (osint_iban_validator, osint_bic_swift_validator, osint_ean_upc_validator) for other identifier types, providing clear guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, etc. Description adds useful context: pure local compute, offline, rate-limited, and behavior for blank lines. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single well-structured paragraph of about 4 sentences, front-loaded with main purpose, and efficiently packs details without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all key aspects: purpose, usage, parameters, return values (numbered result, final number, counts), and constraints (rate limit, offline). Output schema enriches completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage. Description adds value by explaining format options (simple, padded, custom) and control over start, increment, pad width, and blank lines.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Add Line Numbers' with specific verb and resource, explains it prefixes lines with sequential numbers, and distinguishes from sibling tool text_remove_line_numbers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this to annotate logs, code, or lists; use text_remove_line_numbers for the inverse.' Also mentions rate limit and pure local compute, guiding when to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, and idempotent. Description adds valuable context: runs locally, rate-limited (60/min anonymous), and provides return statistics. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise (5 sentences) and front-loaded with purpose. Every sentence adds value; no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, output schema exists, and sibling tools, the description is complete: covers purpose, usage, behavior, return values (statistics and top-15 analysis).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description does not add new parameter meaning beyond what the schema already provides; words are split on whitespace is mentioned in schema too.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool removes duplicate words from text, keeping first occurrence, and splits on whitespace. It distinguishes from sibling tools text_duplicate_line_remover and text_remove_duplicate_characters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use this tool (dedupe word list/tags) and when to use alternatives (line deduplication, character deduplication). Provides clear context and exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond annotations: 'Pure local compute: read-only, non-destructive, offline, and rate-limited (60 requests/min for anonymous callers).' It also details return values (cleaned result, counts, pattern, confidence) and error conditions (empty input, invalid regex). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at 5 sentences, front-loaded with the main purpose and then providing mode details and use cases. Every sentence adds value without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (three modes, regex parameter, rate limiting, return statistics) and the presence of an output schema, the description covers all necessary aspects: modes, usage scenarios, limitations (rate limit, error handling), and return values. It is fully adequate for an AI agent to understand and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds significant meaning: explains auto mode samples first 10 lines, pattern mode uses customRegex, manual strips leading digits. It clarifies the reserved flag and default behaviors, enhancing understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Remove Line Numbers' as the core function and specifies stripping leading line numbers and numbered prefixes. It distinguishes from sibling tool text_add_line_numbers by calling itself the inverse, providing clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases: cleaning pasted code listings, logs, or numbered output. It also mentions it's the inverse of text_add_line_numbers. However, it doesn't explicitly state when not to use the tool or list alternative tools, but the guidance is clear enough for correct selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent. The description adds that it is pure local compute, offline, rate-limited (60/min for anonymous), and explains the return value structure (joined result + statistics + settings). This goes beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that efficiently covers purpose, usage, options, and behavior. It is front-loaded with the main action. Slightly verbose in listing all formats, but that detail is useful for the agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (not shown) and schema coverage is 100%, the description is sufficiently complete. It mentions return value components and contrasts with a sibling tool. It could mention the default separator or output format more explicitly, but overall adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for each parameter. The description does not add new semantic meaning beyond what's in the schema, but it provides a readable overview. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool joins text elements into one string with configurable formatting. It names the core action (join) and resource (text elements), and distinguishes from the sibling tool text_splitter, providing clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description directly tells when to use this tool ('merge lines/items') and when not to, by pointing to text_splitter as the inverse. It includes explicit guidance on usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent. Description adds significant context: runs locally, no external service, rate-limited (60 req/min), returns trimmed text plus statistics. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose and key options. Every sentence earns its place with no fluff. Structure is clear and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 6 parameters fully described in schema, annotations covering safety and idempotency, and mention of output statistics, the description is complete enough for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description summarizes options but does not add new meaning beyond what the schema field descriptions already provide. No deeper explanation of parameter interactions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The title and description clearly state it trims whitespace and custom characters, with detailed options. It distinguishes from siblings like text_find_replace and text_duplicate_line_remover, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (normalize whitespace/tidy formatting) and when not (pattern-based edits and duplicate line removal), naming alternative tools. This provides clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, and idempotent. The description adds valuable behavioral context: 'Runs locally on the text you provide... contacts no external service, and is rate-limited (60 requests/minute for anonymous callers).' This goes beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: purpose, options list, usage alternatives, behavioral notes. It is appropriately sized and front-loaded with the core purpose. Minor redundancy with annotations, but not excessive.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, 100% schema coverage, and presence of output schema, the description sufficiently covers the tool's function. It mentions return value (ranked results array plus summary stats) and effective options. Could include a brief example, but not necessary for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description paraphrases some options (fold case, drop stop words, etc.) but adds little new meaning beyond what the schema already describes. No additional parameter constraints or examples are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Count how often each word appears' and the resource 'block of text', and specifies the output 'ranked frequency table with per-word percentage and rank'. It also distinguishes from sibling tools by naming text_statistics and word_counter as alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides when to use this tool versus alternatives: 'Use text_word_frequency when you only need a plain single-word frequency list...; use text_statistics for a full linguistic profile... and word_counter for raw totals...' This gives clear guidance on context of use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds non-annotation info: offline-capable, rate-limited (60 req/min), no auth, month-clamp behavior. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is moderately long but well-structured, front-loading core purpose. Each sentence adds value, though could be slightly shortened. Efficient communication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (11 params, 3 operations, output schema exists), description covers main behaviors, input requirements, return types (implied by operation), and error handling (month-clamp). Sibling differentiation is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all parameters. Description adds semantics by explaining operation enum behavior and duration object meaning (signed, month-clamp), going beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates date differences and duration arithmetic using proleptic-Gregorian date math, with specific operations (diff, addDuration, subtractDuration). It distinguishes itself from siblings in the usage guidelines section.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (days-between, business-day counts, date arithmetic) and when to use alternative siblings (time_age_calculator, time_date_calculator, time_time_duration). Provides clear direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds key operational traits: runs locally via Node bridge, offline, rate-limited (60/min, 500/hr, 2000/day), non-destructive, idempotent. Also describes return value (sizes and delta). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single well-structured paragraph: starts with tool purpose, then sibling differentiation, then behavioral notes, then return info. Dense but not verbose given 11 parameters and multiple siblings. Could be slightly shorter but earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage vs siblings, behavioral traits (local, rate limits), and return value. With output schema present, no need to detail return structure. Schema covers parameters. Minor gap: does not explicitly mention that it works on CSS strings only (but schema required field 'css' makes it obvious).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 11 parameters with 100% description coverage. The description offers a high-level summary of options (indent size/type, spacing, comments, sorting, newline) but adds no detail beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'CSS Beautifier' with verb 'Pretty-print and re-indent' and resource 'minified or messy CSS'. Explicitly distinguishes from siblings: webdev_css_minifier for minification and webdev_code_formatter for multi-language formatting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when-to-use ('make CSS readable') and when-not-to-use ('use webdev_css_minifier for the inverse, webdev_code_formatter for multi-language'). Gives direct alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that the tool is 'Pure offline reference, read-only, contacts no network, and is rate-limited,' which confirms and extends the annotations with additional behavioral details (offline, rate-limited). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three well-structured sentences: first sentence states purpose and what is looked up; second explains usage modes with parameters; third notes behavior (offline, read-only, rate-limited) and return format. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (not shown but referenced), 100% schema description coverage, and only 5 optional parameters, the description fully covers functionality, usage modes, behavioral traits, and return structure. It is complete for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. The description explains that 'code selects one status,' 'category filters to one class,' and 'search matches code/name/description/use-case text,' adding semantic context beyond the schema field descriptions. It also clarifies that 'includeExamples' is accepted for compatibility but examples are always present.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is an HTTP status code reference tool for looking up codes by number, name, category, etc. It is distinct from sibling tools which are converters, generators, or other utilities; no direct overlap exists, so differentiation is inherent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains how to use the tool: pass no body for full table, or narrow by code, category, or search. It also notes it is offline and read-only, providing safe usage context. However, it does not explicitly list alternatives or state when not to use it, though sibling tools do not compete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, and idempotentHint. The description adds value by stating it's a 'pure client-style compute over a built-in ~170-emoji database (no network, no external API); read-only and non-destructive' and mentions rate limits of 60 requests per minute for anonymous callers. This provides useful behavioral context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with multiple sentences, each adding value. It front-loads the main purpose and then provides usage guidelines, behavioral notes, and parameter details. Slightly verbose but no wasted words; could be a bit more concise but still effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity and the presence of an output schema, the description covers all necessary aspects: purpose, usage, behavior (including database size and rate limits), and parameter semantics. No gaps are apparent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for both parameters (query and search_type). The description adds a brief summary of search types but does not significantly enhance the meaning beyond the schema. Baseline 3 is appropriate since the schema already does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to look up emoji by glyph, name, keyword, category, or Unicode code point and return Unicode metadata plus HTML entities. It uses specific verbs like 'look up' and 'return', and distinguishes itself from sibling tools like conversion/emoji/random, encoding/unicode, and encoding/html-entities. This makes the purpose very clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool: 'when you have one search term and want full Unicode/HTML detail for matching emoji'. It also provides clear alternatives: 'use conversion/emoji/random instead to sample random emoji without a query, and encoding/unicode or encoding/html-entities for escaping arbitrary text rather than looking up emoji'. This is excellent guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, non-destructive, idempotent. The description adds concrete behavioral details: runs locally, offline, no auth, default rate limit. It also outlines parsing behavior and return contents, complementing annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (4-5 sentences) and well-structured: name, enumeration, parsing details, usage guidance, operational context, return info. Some minor redundancy but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 params, 6 representations, parsing rules) and existing output schema, the description covers major aspects: supported types, parsing behavior, conversion constraints, and sibling distinctions. Could clarify multi-value output but schema likely covers.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 100% schema coverage, the description adds significant meaning: parsing rules per from_type (character-by-character vs token splitting), output format specifics (3 decimals for float, exponential for scientific, range limits for roman and words). This goes beyond enum labels.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as a 'String / Number Format Converter' that converts between six representations. It enumerates the types and differentiates from siblings by naming conversion_roman_numerals and conversion_number_base as alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises using this tool for mapping characters to/from code points or reformatting number lists, and directs users to specialized tools for Roman numerals and number base conversion. This provides clear when-to and when-not-to guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds important behavioral context beyond annotations: fresh random salt per call (non-idempotent), server-side execution, read-only nature, no external service contact, rate limits (5/min, 30/hr, 100/day). Annotations already declare readOnlyHint=true and idempotentHint=false, but description enriches with specifics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured with title, purpose, usage guidance, comparisons, and behavioral notes. It packs substantial information but remains readable; minor trimming could improve conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 params, output schema, annotations), the description fully covers purpose, usage, behavior, rate limits, and alternatives. No significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions, examples, enums, and defaults for all 5 parameters. Description adds minimal extra meaning beyond schema (e.g., 'required and non-empty' for password). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Generate Argon2 Password Hash' and explains the exact function: hash a plaintext password with Argon2 KDF, returning PHC-encoded hash plus parsed parameters. It distinguishes from sibling crypto_argon2_verify and other crypto tools like crypto_bcrypt.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool (create new hash) vs. crypto_argon2_verify (check password). Recommends Argon2 over bcrypt, scrypt, pbkdf2, providing clear alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint, idempotentHint, etc.) are reinforced and expanded by the description: 'Runs locally on the input you provide: read-only, non-destructive, contacts no external service, and is rate-limited.' The return value structure is also disclosed. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences structured with title/purpose, algorithm list, usage guidance, behavioral notes, and return value summary. Front-loaded and concise; every sentence adds distinct value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with many algorithms and output format nuances, the description covers purpose, usage, behavior, and return format. Output schema exists and the description summarizes it. A minor gap: no explicit clarification of output format behavior for non-numeric algorithms, but the schema covers it. Overall sufficient for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for each parameter (text, algorithms, outputFormat). The description adds high-level context (e.g., 'non-cryptographic' though including cryptographic hashes) but does not substantially augment schema-level parameter semantics beyond reinforcing the purpose. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it computes non-cryptographic checksums and hashes over UTF-8 text, listing supported algorithms (CRC, Adler, Fletcher, FNV, SHA, etc.). It distinguishes from siblings by referencing crypto_hash for cryptographic digests and crypto_hash_identifier for detection, establishing a specific verb+resource with explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: 'Use it when you need fast verification or legacy checksums; use crypto_hash for cryptographic file/text digests, or crypto_hash_identifier to detect an unknown hash's algorithm.' It also notes the tool is read-only, non-destructive, and rate-limited, giving clear context for when to invoke versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds behavioral context beyond annotations: runs locally, read-only, non-destructive, idempotent, rate-limited (60 req/min), contacts no external service. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured and front-loaded with the main purpose. It is slightly verbose but every sentence adds value. Could be slightly more concise, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema existence, the description is complete. It covers rate limits, idempotency, local operation, and return content (ranked candidates, confidence scores, etc.). No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only one parameter 'hash' with 100% schema description coverage. The schema already explains stripping prefixes and recognizing special formats. Description does not add significant new semantics beyond what schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool identifies hash algorithms by analyzing length, character set, and structural pattern, listing many specific algorithms. It explicitly distinguishes from sibling tools like crypto_hash_cracker and crypto_hash.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage guidance: 'Use this when you have a hash and do not know its type.' It also specifies what the tool does not do (crack, reverse, lookup) and directs to crypto_hash_cracker for plaintext recovery.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds significant context beyond annotations: hand-rolled parser (no eval), local execution, read-only/non-destructive, no external service, rate-limited. Annotations already indicated readOnlyHint=true and destructiveHint=false, but the description enriches with implementation details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured with clear sections: purpose, returns, syntax support, usage guidance, implementation. It's informative but somewhat verbose; could be slightly more concise without losing clarity. Still efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of JSONPath evaluation and the existence of an output schema, the description covers all necessary aspects: input, expression rules, output structure (matches array, path, value, count), and contextual comparisons. It is complete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add much beyond what's in the schema for the parameters. It mentions non-empty and root token $ for expression, but that's already in the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it evaluates a JSONPath expression against a JSON document and returns matched values with paths. It specifies supported syntax (child/recursive-descent, wildcards, slices, filters) and distinguishes itself from siblings like data_json_schema_validator, format_json, and webdev_xml_to_json.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('extract or query values from a JSON document you already have') and when not to, naming specific sibling tools for alternative tasks. This provides clear guidance for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds context: 'Runs locally on the input you provide: read-only, non-destructive, contacts no external service, and is rate-limited.' No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is front-loaded and concise, with four sentences covering function, features, alternatives, and safety. Each sentence adds value, though slightly more structure could improve readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool complexity (6 params, output schema exists), the description adequately covers input, options, safety, and usage guidance. No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for 6 parameters. Description summarizes parameter choices (delimiter formats, case, encoding) but does not add significant meaning beyond schema descriptions. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Hex to ASCII Converter (Bidirectional)' and details the conversion between hex and text with options. It distinguishes itself from siblings like conversion_number_base, encoding_decoding_binary_text, and encoding_decoding_base64.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explicitly names alternative tools for different use cases: conversion_number_base for multi-radix, encoding_decoding_binary_text for binary representation, encoding_decoding_base64 for MIME-safe transport. It also notes local execution and rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, destructiveHint, and idempotentHint. The description adds value by noting local execution, offline operation, rate limit (60/min), and return content analysis, exceeding what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph with clear structure: purpose, technical detail, usage guidance, operational notes. Efficient but could be slightly more concise; still well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given full schema coverage and output schema existence, the description is comprehensive. Covers all parameters, usage context, behavioral notes, and return value analysis.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description still adds meaning by explaining operation, mode, format, and their defaults. Clarifies that mode/format are ignored when decoding, which is not in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Encode or Decode HTML Entities' and explains the conversion. It distinguishes from sibling tools by naming specific alternatives (URL, Unicode, string escape). The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (HTML/XML markup safety) and when not, listing three sibling tools with distinct purposes. This provides clear guidance for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds: 'Runs locally on the input you provide: read-only, non-destructive, contacts no external service, and is rate-limited (60 requests/minute...' It also mentions handling surrogate pairs and astral code points. While it doesn't explain error handling, it adds sufficient operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a medium paragraph with front-loaded purpose, then operation/format details, then unescape auto-detection, then sibling alternatives, and finally local execution/rate limit. It is mostly concise, though could be slightly more structured (e.g., bullet points). Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, 100% schema coverage, annotations, and an output schema, the description covers all needed aspects: what it does, how to set operation and format, unescape auto-detection, sibling alternatives, and local/rate-limited behavior. No critical gaps remain for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter described. The description adds extra meaning for the 'format' parameter by detailing each syntax (e.g., 'json/java use backslash-uXXXX, python adds backslash-UXXXXXXXX for astral'). This goes beyond the schema's brief enum labels.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it's a Unicode Escaper and Unescaper, specifying escape targets (JSON, Python, Java, CSS, HTML, XML, URL) and distinguishing itself from sibling tools like encoding_decoding_html_entities and conversion_emoji. The verb 'Escape/Unescape' and resource 'text into Unicode escape sequences' are specific and unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool (escape/unescape Unicode) and when not to use it, naming alternatives: 'Use encoding_decoding_html_entities for named HTML entities, encoding_decoding_punycode for IDN domain names...' This provides clear guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds beyond annotations: read-only, non-destructive, offline, rate-limited. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise, front-loaded, each sentence adds value. Slightly verbose but appropriate for complex tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, modes, safety, offline nature, rate limits, and output schema mention. Fully adequate for complex 6-param tool with existing output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, baseline 3. Description adds detailed explanation of operation modes and cross-references parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
States specific purpose: look up POSIX/Linux process signal table, returns comprehensive signal info. Clearly distinguishes from conversion and other linux tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says use as static cheatsheet, does not send/deliver signals. Implies context but doesn't compare to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true. Description adds valuable context: triggers on-demand fetch for stale pairs, not idempotent, results change daily, rate limited to 30 req/min. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is front-loaded with main purpose and contains all necessary information without redundancy. Slightly long but each sentence adds value; could be trimmed slightly but remains effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (caching, daily rates, rate limiting, 31 currencies) and presence of output schema, description fully covers what an agent needs to know: purpose, behavior, limitations, and alternatives.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions including enums, case-insensitivity, and equal from/to behavior. Description does not add new parameter information beyond what schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool converts a money amount between ISO 4217 currencies using daily EOD FX rates. Lists output fields and distinguishes from siblings by naming math_currency_converter_history and math_unit_converter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool (present-day conversion among the 31 supported currencies) and when to use alternatives (math_currency_converter_history for multi-day series, math_unit_converter for non-currency conversions). Also mentions rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes not idempotent behavior, data source (local cache + EODHD fetch), rate limit (30 req/min), and resolution path. Adds context beyond annotations (readOnlyHint=false, idempotentHint=false, openWorldHint=true).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is comprehensive but not overly verbose; each sentence adds value. Well-structured with purpose first, then details, usage, and rate limit. Could be slightly more concise but handles complexity well.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (3 parameters, output schema), description covers behavior, data source, non-idempotence, rate limits, and alternatives. Output schema exists, so no need to detail return values. Complete for agent decision.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions and enums; description adds minimal extra meaning (e.g., 'equal from/to returns a flat series of 1' already in schema). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it fetches a historical EOD FX rate series for a currency pair, for charting. It also distinguishes from sibling tools math_currency_converter_convert and math_unit_converter, specifying when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this for a multi-day time series... use math_currency_converter_convert for a single present-day amount conversion, and math_unit_converter for non-currency...' providing clear context and alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint=true, idempotentHint=true), description adds deterministic behavior, BigInt exactness, decimal string output, index/range bounds, rate limit, and return value shape variability. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph with effective front-loading of main operations. Every sentence contributes value. Could be slightly more structured (e.g., bullet points) but remains clear and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's multiple operations, 6 parameters, and output schema existence, the description covers all necessary context: operation types, constraints, limits, behavior, rate limiting, and return value variability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description's added value is limited. It provides high-level context (e.g., operation types) but does not significantly enrich individual parameter understanding beyond the schema's own descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates Fibonacci sequences, computes nth term via fast doubling, tests membership, and lists values in a range. It distinguishes itself from siblings by naming alternatives (math_prime_number_checker, math_factorial_calculator).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool (for Fibonacci operations) and when to use alternatives (primality, factorials). Also provides context: runs locally, read-only, non-destructive, no external service, rate-limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds algorithmic details (Euclidean algorithm, trial division, BigInt), confirms local execution with no external service, and specifies rate limits (60 req/min). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused paragraph that front-loads the core function. It efficiently covers purpose, usage, and behavior without waste. Could be slightly tighter but is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description need not detail return values, yet it still mentions return structure. It covers algorithms, rate limits, local execution, and parameter requirements, making it fully informative for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all parameters. The description adds minor context (string coercion for 'numbers', algorithm notes) but largely restates schema info. Minimal additional value beyond schema, so baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a GCD/LCM calculator and prime factorizer. It specifies the operations (gcd, lcm, factorize) and distinguishes from siblings like math_prime_number_checker, math_factorial_calculator, and math_bitwise_calculator, leaving no ambiguity about its purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use the tool ('for number-theory reductions') and when not to, with named alternative tools. Also mentions rate-limiting and local execution, providing clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses beyond annotations: runs locally, read-only and non-destructive (consistent with annotations), rate-limited (60 requests/min for anonymous), algorithm details for determinant (cofactor vs LU). While annotations already provide readOnlyHint/destructiveHint, description adds operational context like rate limit and local execution. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured: begins with a summary of operations, then preconditions, then sibling alternatives, and finally behavioral notes. Sentences are efficient but some redundancy exists (e.g., repeated mention of 'finite-precision'). Front-loaded with the tool's core purpose. Could be slightly shorter, but effective overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 operations, multiple preconditions, siblings), the description covers all necessary aspects: operations list, preconditions, alternatives, rate limit, return types. Output schema exists, so return format detail is sufficient. No gaps in guidance for the agent to misuse the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter described, so baseline is 3. Description adds meaningful context by grouping parameters per operation and stating preconditions (e.g., 'add/subtract need equal dimensions', 'inverse needs non-singular matrix'), which is not enforced in the schema alone. This additional guidance helps parameter selection.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Describes specific verb+resource: 'Matrix Calculator' performing finite-precision linear-algebra operations on small matrices. Lists all operations explicitly (add, subtract, multiply, scalarMultiply, transpose, determinant, inverse, identity) and distinguishes from siblings by naming alternatives (math_scientific_calculator, math_statistics_calculator, math_quadratic_solver).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear when-to-use context by listing preconditions (e.g., equal dimensions for add/subtract, square matrix for determinant/inverse). Explicitly states when not to use by suggesting alternatives for scalar expressions, statistics, and polynomial roots. Covers both inclusion and exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, the description discloses critical behavioral traits: uses a hand-rolled shunting-yard parser (no eval), runs locally as read-only and non-destructive, contacts no external service, and is rate-limited at 60 requests/minute. This transparency far exceeds the minimal annotation hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and well-structured, covering operators, usage guidance, and safety. However, it is somewhat verbose and includes a truncated sentence at the end, slightly reducing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown but indicated), the description does not need full return details. However, the description is truncated mid-sentence ('On success returns the original ex'), which is a clear gap. Otherwise, it covers supported operations, error handling implied, and limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have full schema descriptions (100% coverage), but the description adds value by elaborating on angleMode aliases and clarifying the expression length limit (1000 characters). This enhances understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool evaluates a single scientific math expression and returns its numeric value. It explicitly lists supported functions and operators, and distinguishes itself from sibling tools like math_quadratic_solver and math_statistics_calculator by stating when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (general numeric expressions) and when to use alternatives (quadratic solver, statistics calculator). It also mentions rate limits and safety, helping the agent decide correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that it runs locally, is read-only, non-destructive, does not contact external services, and is rate-limited (60 req/min). Also details return format (JSON envelope) and special algorithms (Type-7 linear interpolation for quartiles, excess kurtosis). These go beyond annotations which already indicate readOnlyHint and destructiveHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with the title and main purpose. It is concise yet includes essential details. A minor deduction for slight density but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, output schema, annotations), the description covers purpose, usage guidelines, behavioral traits, return format, and algorithm specifics. It leaves no obvious gaps for an AI agent to correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds explanation of operation modes (e.g., 'describe' needs values array, correlation needs x and y) but largely repeats schema descriptions. No significant new parameter semantics beyond what schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes descriptive statistics, z-scores, correlation, and linear regression, specifying it works on numeric datasets. It distinguishes from sibling tools math_percentage_calculator and math_ratio_calculator, providing a specific verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (analysing a list of numbers) and when to use alternatives (percent-of/percent-change math with math_percentage_calculator, proportions with math_ratio_calculator). Also explains how the 'operation' field selects among four modes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are minimal (readOnlyHint: false, destructiveHint: false). The description adds substantial behavioral context: read-only, non-destructive, not idempotent, rate limits, CAPTCHA, dependency on a third-party API (BGPView), and variability of results. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that is front-loaded with purpose. It includes necessary details (rate limits, alternatives) without verbosity. Could be slightly more structured, but overall concise and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (7 parameters, 1 required), the description covers purpose, usage, behavior, output (with output schema present), and limitations. It is complete for an AI agent to understand when and how to use the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add significant meaning beyond what the schema already provides for parameters. It mentions output fields (origin AS, AS-PATH, etc.) but not parameter-specific semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Resolve') and resource ('IPv4/IPv6 address or CIDR prefix to live BGP routing data'), clearly stating the tool's purpose. It distinguishes from sibling tools by naming alternatives like network_asn_lookup, network_whois, and network_ip_geolocation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('when you need the routing path / AS-PATH for an address') and provides alternatives for other use cases. Also mentions non-idempotent behavior and rate limits, offering clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool sends outbound DNS queries to 14 third-party servers, is NOT read-only, contacts the open internet, and is rate-limited to 3 requests per minute. This adds significant context beyond the annotations (which only indicate readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four sentences long, efficiently front-loading purpose and usage guidelines before adding behavioral details. It is concise and well-structured, though a minor trimming could make it slightly tighter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (checking across 14 resolvers, rate limits, output summary), the description covers all necessary aspects: purpose, usage context, behavioral traits, rate limiting, and the list of resolvers. The presence of an output schema reduces the need to describe return values. The description is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the schema already provides detailed descriptions for all parameters (domain, record_type with enum, worker_id). The description only mentions domain and record_type implicitly but does not add new meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks DNS propagation across 14 global resolvers. It distinguishes itself from the sibling tool 'network_dns' by specifying that this tool checks propagation across multiple resolvers while network_dns is for a single authoritative lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool (after changing a record to confirm propagation) and when to use the alternative 'network_dns' (for a single authoritative lookup against one resolver). This provides clear guidance for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that computation is local, no socket opened, non-destructive, idempotent, rate-limited (5 req/min), and CAPTCHA required above 15/hr, adding context beyond the annotations that already declare readOnly, idempotent, and non-destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is informative and well-structured, with purpose first, then scope of operations, then behavioral notes. Slightly verbose but each sentence contributes necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple operations, rate limiting, local computation), the description covers all relevant aspects: functionality, limitations, behavior, and operational details. Output schema exists but description still adequately sets expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions and examples. Description adds value by explaining operation types and noting that broadcast and port are ignored for certain operations, enhancing understanding beyond schema constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool builds WOL magic packets and commands for a MAC address, lists five specific operations, and distinguishes from siblings by focusing on network wake functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use each operation ('Choose operation to scope the work'), clarifies that the tool does not transmit packets, and mentions rate limits, but does not explicitly list alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), description adds rate limits (100 req/min, 1000/hr anonymous), offline computation, and no external dependencies. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with front-loaded purpose, but slightly verbose with multiple clauses. Each sentence adds value, though could be more compact.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (8 params, 4 operations, output schema), description fully covers behavior, limitations, and usage. No gaps remain for an AI agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline 3. Description minimally adds context beyond schema (e.g., 'result object shape depends on operation'), but schema already defines each parameter with descriptions and examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it's an IP Range Calculator for IPv4 with offline arithmetic. It enumerates four distinct operations (cidr, range, check, list) and distinguishes from sibling tools like network_subnet_calculator and networking_ipv4_to_ipv6.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use each operation via the 'operation' field. Provides alternatives for subnet planning and IPv6 conversion. States 'IPv4 only' and 'no DNS or live network', setting clear boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that each call issues a fresh DNS query (non-idempotent), matching the idempotentHint=false annotation. It also reveals rate limits (10/min, 60/hour, 200/day) and CAPTCHA-gating, which annotations do not cover. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with front-loaded purpose and usage, then behavioral details. It is slightly verbose but every sentence adds value. Could be slightly tighter but still effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description does not need to detail return values. It covers purpose, usage guidelines, behavioral traits, and rate limits. Complete for a lookup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal semantic value beyond the schema: it confirms 'action' only supports 'lookup' and domain note. No additional parameter context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs MX record lookup for a domain, returning mail servers and priorities. It distinguishes itself from siblings like network_dns_lookup (for arbitrary record types) and network_spf_record_checker/network_dmarc_record_checker (for email-auth policy).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('for the email-delivery path of a domain') and when not to, pointing to alternative tools for other record types or email-auth policies.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that it makes outbound connections, resolves to public IP only, rejects private ranges, is rate-limited (1/min, 5/hr, 20/day), may be logged, and requires permission. These details are not present in annotations, providing valuable transparency beyond the structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with purpose. While slightly verbose, each sentence adds necessary information. Could be marginally trimmed, but overall effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, output schema, annotations), the description covers behavioral aspects, usage guidelines, permission requirements, and output format. It is fully complete for an AI agent to understand and use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes all parameters. The description adds no extra detail on parameters beyond what the schema provides, but it contextualizes the tool's behavior. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs a TCP connect port scan, probing a live host for open TCP ports. It distinguishes itself from the sibling tool network_tcp_udp_port_reference by emphasizing live probing versus offline lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool ('detect actually-listening services on a host you control') and when to use the alternative (network_tcp_udp_port_reference for offline lookup). Also includes permission requirements and rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states that the tool is read-only, non-destructive, contacts no external service, and is not idempotent, which aligns with annotations. It also adds details about rate limits and CAPTCHA challenges, providing valuable behavioral context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and informative, front-loading the main purpose. While it includes several sentences, each adds value. It could be slightly more concise (e.g., listing all headers explicitly), but overall it is effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all necessary aspects: purpose, what it does and does not do, usage guidelines, behavioral traits, rate limits, and return values. Given the tool's simplicity and the presence of an output schema, the description is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the single optional parameter worker_id with sufficient detail. The description does not add any additional meaning or context for this parameter, but given 100% schema coverage, a score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool inspects the incoming HTTP request headers from the caller's own client, explicitly distinguishing it from fetching remote headers. It lists specific headers and provides alternative tools for related but different tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (to see exact headers, parsed summary, security audit) and when not to (it does not fetch remote headers). It also explicitly provides alternative tools for different needs (my_ip, browser_fingerprint_viewer, header_analyzer).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description goes beyond annotations by detailing that the tool performs a live DNS query (may use a remote worker), results are non-constant, no auth required, and rate limits (10 req/min, 60/hr, 200/day for anonymous, CAPTCHA above 30/hr). Annotations indicate openWorldHint=true but not specifics; the description adds valuable behavioral context without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-organized, starting with purpose, then actions, alternatives, and behavioral notes. It is a single paragraph but front-loads key information. Minor improvement could be using bullet points for rate limits, but overall it is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool complexity (two actions, DNS query vs. offline parsing), the description covers purpose, operations, alternatives, behavioral traits, rate limits, and outlines return values (SPF record, matching records, multiple-record flag, parse results). With an output schema present, this is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage with clear explanations for each parameter (domain, action, record, worker_id). The main description does not add significant extra information beyond the schema, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'SPF Record Checker. Look up and validate a domain's SPF (Sender Policy Foundation) TXT record for email authentication and anti-spoofing.' It specifies two actions (lookup and parse) and differentiates from sibling tools like network_dmarc_record_checker and network_mx_record_lookup, making the purpose distinct and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided: 'Use network_dmarc_record_checker instead for DMARC alignment/reporting policy, or network_mx_record_lookup for mail-server MX records; this tool only handles SPF.' It explains when to use each action and mentions that domain is required for lookup but ignored for parse, giving clear context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses numerous behavioral traits beyond annotations: real network request, SSRF safety (host pinned to public IP, private/reserved IPs rejected), TLS verification on, CAPTCHA-gated, rate limits (30/min, 180/hour, 500/day). Annotations only provide readOnlyHint, destructiveHint, etc., which are not contradicted. This is comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by usage guidance, safety details, rate limits, and key output fields. While thorough, it is somewhat lengthy with three paragraphs; however, every sentence adds value. Could be slightly more concise but well-structured overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 2 parameters (1 required), an output schema, and moderate complexity, the description is complete. It covers purpose, alternatives, behavioral aspects, safety, rate limits, and hints at output fields. The existence of an output schema means return values need not be fully detailed here.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with descriptions for both parameters (url with example, worker_id with description). The description adds general context but no additional parameter-specific meaning beyond what the schema provides. Baseline is 3 due to full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks website uptime via HTTP GET, reporting status code, accessibility, response time, redirect chain, and headers. It explicitly distinguishes from siblings like network_ping, network_ssl_certificate, and network_dns_lookup, making purpose and differentiation evident.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided: 'Use this for HTTP-level reachability, status codes, and latency; use network_ping for ICMP host reachability, network_ssl_certificate to inspect the TLS certificate, and network_dns_lookup for DNS records.' This tells the agent when to use this tool and when to use alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds valuable behavioral context: it runs locally, offline, with rate limits (10 req/min, CAPTCHA above 30/hr). This extra detail earns a 4.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but well-structured and front-loaded with the core purpose. Each sentence provides meaningful information. While it could be slightly trimmed, the length is justified by the tool's complexity and the need for sibling differentiation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool's complexity, the description covers all critical aspects: input, output, behavior, limitations, and alternatives. The presence of an output schema (mentioned but not shown) reduces the need for describing return values. The description is fully sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter has 100% schema coverage. The description adds practical guidance on what to paste ('Show original'/'View source'), which helps the agent understand the expected input format better. This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool parses raw email headers into a structured forensic report, listing specific extracted elements (Received chain, SPF/DKIM/DMARC, etc.). It distinguishes itself from sibling tools by explicitly stating it does not perform DNS lookups and pointing to alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool (when you have literal header text) and what it does not do (no DNS queries). It also names specific sibling tools for live DNS lookups and domain registration data, providing clear guidance on alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes beyond readOnlyHint=true and destructiveHint=false annotations by detailing pure local arithmetic, no network call, offline-capable, rate-limited, CAPTCHA possibility, and timestamp embedding for non-identical responses. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured, front-loaded with core function, and each sentence adds value. Slightly long but not wasteful; could be trimmed slightly for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage guidelines, behavioral traits, output description (per-ISBN results with aggregate statistics), and optional features. Given complexity and existing schema/annotations, description is fully complete for agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds context (e.g., step-by-step math for showCheckDigitCalculation) but mostly reiterates schema info. Adequate but not exceptional.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it validates ISBN-10 and ISBN-13 by recomputing check digits, reporting format, registration group/language, and conversion. It explicitly distinguishes from sibling tools (osint_ean_upc_validator, osint_barcode_scanner, osint_barcode_generator) with clear when-to-use guidance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Use this for book ISBNs' and provides alternatives for general EAN/UPC barcodes. Also clarifies batch acceptance, offline capability, and rate-limiting, giving clear context for appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations: non-destructive, deterministic, rate-limited (20 req/min anonymous), and explains the serviceUrl is a third-party renderer fetched separately. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with purpose, but is somewhat verbose. Every sentence adds value; could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (nested objects, 4 parameters, output schema exists), the description covers the API flow, rate limits, third-party dependency, and return fields. Fully adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for all properties. The description summarizes but adds little beyond the schema, e.g., mentioning encoding formats like 'WIFI:T:...'. Meets baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it builds QR code payloads from six input types and returns a render URL. It distinguishes itself from siblings by naming them explicitly (osint_qr_code_scanner, osint_barcode_generator, security_totp_qr_generator).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('prepare QR content') and when to use alternatives (decode, barcode, TOTP). Provides clear context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations by stating that the tool is 'read-only, deterministic, non-destructive, contacts no external service, and is rate-limited.' It also outlines the tokenization process (Unicode-aware, optional stripping/stopword removal), adding valuable behavioral context that annotations alone do not provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is informative yet efficient, covering purpose, usage, behavior, and parameter hints in a structured manner. It is slightly lengthy but every sentence adds value, so it earns a 4.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the medium complexity and the presence of a comprehensive input schema and output schema (not shown but implied), the description covers all necessary aspects: input handling, processing details, output features, constraints, and sibling tool differentiation. It is fully complete for agent selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters well. The description adds minimal extra semantic value for parameters (e.g., 'stopwords can be en, none, or custom array'), but it doesn't go into depth beyond what the schema provides, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze plain text or HTML for keyword density and repeated phrases as an SEO content audit.' It distinguishes itself from sibling tools like text_word_frequency, text_text_statistics, seo_title_description_length_checker, and seo_meta_tag_generator, leaving no ambiguity about what it does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool ('when you need per-keyword and per-phrase density to detect keyword stuffing') and when to use alternatives (e.g., 'use text_word_frequency for a plain single-word frequency list'). This provides clear guidance for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations: it confirms read-only, non-destructive behavior, notes it runs locally with no external service contact, specifies a rate limit (30 requests/minute), and describes the return format (HTML, length counts, truncation warnings). This fully aligns with annotations and adds useful detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the main purpose and covers all necessary aspects concisely given the tool's complexity (15 params, siblings). Each sentence adds value, though the length could be slightly trimmed without loss.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given full schema coverage, an output schema, and sibling references, the description is complete for agent decision-making. It explains both operation modes, cross-tool differentiation, behavioral guarantees, and return value highlights, leaving no critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description provides a high-level summary but does not add significant meaning beyond what the schema already offers for each parameter. The two operation modes are already enumerated in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Generate') and resource ('complete HTML head block of SEO meta tags'), clearly differentiating from siblings by explicitly naming seo_open_graph_generator and seo_schema_org_generator and stating when to use those instead.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: 'Use seo_open_graph_generator when you only need rich Open Graph type sub-properties...' and 'seo_schema_org_generator for standalone JSON-LD'. It also explains the operation parameter modes (generate vs presets) and states the tool is read-only, non-destructive, and rate-limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes behavioral traits beyond annotations: deterministic for ≤8 chars, random for longer, input cleaning, offline/rate-limiting, and that outputs are not real words. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One dense paragraph covering all key aspects without redundancy. Could be slightly more structured (e.g., bullet points) but all information is necessary and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present, no need to detail return values. The description covers input cleaning, deterministic vs random behavior, dictionary absence, alternatives, and constraints (rate limit, offline).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions. The description adds overall context but does not significantly augment individual parameter semantics beyond what schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates anagrams by rearranging letters, lists return items (flags, stats, frequency map), and distinguishes from sibling tools like text_palindrome_checker and text_randomizer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (anagram generation) and when not to (palindrome detection, word/line shuffling), naming specific alternatives. Also clarifies it does not use a dictionary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent. Description adds: runs locally, no external service, rate-limited (60 req/min), returns statistics and top-10 repeated lines. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured but somewhat long; however, every sentence adds value including purpose, options, sibling differentiation, and safety. Could be slightly more concise but earns its length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 boolean parameters with defaults documented in schema, and existence of output schema (mentioned in description), the description covers purpose, behavior, alternatives, return structure, and constraints. Fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good descriptions. The description does not add new parameter details beyond summarizing options, but the schema already fully documents each parameter, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool removes duplicate lines from text, keeping first occurrences, with specific options. It distinguishes from siblings like word and character deduplication tools, meeting the 'specific verb+resource' criterion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly lists alternatives: text_duplicate_word_remover, text_remove_duplicate_characters, text_sort_lines. Also notes local execution, rate limits, and non-destructive nature, providing clear when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), description adds crucial traits: pure regex extraction, read-only, non-destructive, no network requests, local with no auth, rate limited to 30 req/min. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is comprehensive but slightly long. It is front-loaded with main purpose and includes all critical details. Minor verbosity in listing every feature; still efficient and well structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters with full schema description and existence of output schema, the description covers purpose, behavior, limitations, rate limit, alternatives, and output summary completely. No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%; description summarizes parameters (e.g., 'Filter by extraction mode', 'deduplicate case-insensitively') but repeats some schema info. It adds value by explaining output structure (per-match fields) not in input schema, and notes constraints like 'Required and non-empty'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Extract URLs From Text' with specific verb and resource. It details scanning text, returning per-match details, and distinguishes from sibling 'text_extract_emails' for email addresses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit context for use: 'Use this for hyperlinks and protocol URIs; use text_extract_emails instead when you only want email addresses.' Also mentions rate limits and local execution, but does not exhaustively list when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds important behavioral details: runs locally, never mutates input, contacts no external service, and specifies rate limits (30 req/min for anonymous). It also explains what the return includes (statistics, counts). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a clear purpose sentence, followed by usage guidance, then behavioral details. It is informative without being verbose. Could be slightly more concise by removing the 'Find and Replace Text with Optional Regex' repetition, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's 6 parameters, 2 required, and the existence of an output schema, the description fully covers all relevant aspects: input constraints (empty returns HTTP 400), behavior (local, read-only, rate-limited), return value (statistics, counts), and alternatives. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already has 100% coverage with clear descriptions for all 6 parameters. The description's high-level summary of features (case-insensitive, regex, replace-all toggle) provides minimal additional meaning beyond the schema. Baseline 3 is appropriate here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs find-and-replace on text with optional regex, and directly distinguishes itself from siblings like webdev_regex_tester and text_text_splitter by naming specific use cases for each. This meets the highest standard of purpose clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool ('for literal or regex search-and-replace') and provides named alternatives ('use webdev_regex_tester to test a pattern before applying it, or text_text_splitter to break text on a delimiter'). This is exemplary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds further transparency: 'Runs locally... read-only, non-destructive, contacts no external service, rate-limited (60 requests/minute for anonymous callers),' and details the return structure. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and informative, but somewhat verbose for a simple deduplication tool. It could be more concise without losing clarity, but it earns a 4 for effective communication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema, the description need not detail return values but still does. It covers purpose, usage, behavior, parameters, and return, making it complete for the tool's complexity. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal extra meaning beyond the schema; it mentions 'keeping either the first or the last occurrence' which relates to firstOccurrence, but the schema already has descriptions. Little added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Remove Duplicate Characters From Text' and explains it removes repeated characters keeping first or last occurrence. It explicitly distinguishes from sibling tools text_duplicate_word_remover and text_duplicate_line_remover, ensuring no confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('dedupe at the character level') and when to use alternatives ('text_duplicate_word_remover for whole words, text_duplicate_line_remover for whole lines'). It also notes that it runs locally, is read-only, non-destructive, and rate-limited, giving comprehensive usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses read-only, non-destructive, local execution, rate limits (60 req/min), output non-reversibility, and random selection behavior, all beyond what annotations provide. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with front-loaded purpose, use case, and alternatives followed by behavioral notes. Slightly verbose but each sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, behavior, parameter options, return values (mentioned), and constraints. Complete for a tool with 5 parameters, enums, and output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description adds marginal semantic value. It provides overall context (rate limits, randomness) but does not elaborate on parameter details beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Obfuscate Text') and resource ('text'), lists five distinct techniques, and explicitly distinguishes from sibling tools like reverse_text, case_converter, and rot13/atbash.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides explicit guidance: 'Use it to make text visually unrecognizable for privacy or creative effect' and specifically names alternatives (reverse_text, case_converter, rot13/atbash) with clear differentiators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds valuable behavioral details: rate limit (60 req/min), offline/deterministic nature, and mode-specific behavior (e.g., parameter ignore). Minor gap: does not mention error handling beyond blank text.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured with front-loaded main idea, followed by alternatives and behavioral notes. Every sentence adds value, though length could be slightly tighter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 params, 100% schema coverage, output schema exists), the description covers all essential aspects: purpose, methods, options, alternatives, behavioral traits, and return summary. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds context beyond schema: explains behavior of each splitType (e.g., 'lines splits on newlines'), clarifies parameter dependencies (delimiter/regex only for specific types), and notes return value includes statistics. Does not repeat schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: splitting a string into parts using multiple methods. It specifies the resource (string) and verbs (split), and distinguishes from siblings like text_joiner, text_statistics, and column_tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use the tool ('Use this to break a string apart') and provides alternatives for inverse operations and similar tools. Also includes behavioral constraints like rate limit and deterministic nature.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds context beyond annotations: read-only, non-destructive, offline-capable, rate-limited, no auth. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured and front-loaded, but slightly verbose with repeated 'operation' phrases. Still efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all aspects: purpose, operations, parameters, usage, behavioral traits. Output schema exists, so return values not needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description adds limited value on parameters. It hints at required params per operation but doesn't elaborate beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes age or elapsed time with two operations, and distinguishes from sibling time_date_difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use this tool (age/birthday math) and when to use time_date_difference instead, plus mentions local execution and rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds that the tool runs locally, is read-only, non-destructive, contacts no external service, and has a rate limit (60 req/min). This provides valuable behavioral context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that efficiently covers all operations, parameters, constraints, behavior, and sibling differentiation. It is front-loaded with the core purpose and avoids redundancy. Minor improvement could be structuring by operation, but it is still concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the moderate complexity (three operations, six parameters, no nested objects), the description covers all necessary aspects: operations, parameter usage, constraints, behavior, rate limits, and even references the output schema. It fully equips the agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the baseline is 3. The description adds value by grouping parameters by operation (check with year, range with from and to, next with startYear and count), clarifying how parameters relate to each other beyond the schema's per-parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: determining leap years via three operations. It distinguishes from sibling tools by explicitly referencing time_date_calculator and time_day_of_week for other date-related tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent when to use this tool vs. alternatives: 'Use time_date_calculator for date arithmetic and time_day_of_week for weekday lookups; this tool only answers leap-year questions.' It also describes the three valid operation modes and their parameter requirements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds significant value by stating it is 'pure deterministic week-numbering over UTC with no clock/now dependency', 'Read-only, non-destructive, idempotent, offline-capable, rate-limited (60 req/min anonymous), no auth.' It also explains the four week-numbering schemes in detail, which is well beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is fairly long but well-structured, front-loading the purpose and then detailing each operation. It includes usage guidelines and behavioral traits. Every sentence adds value, though it could be slightly more concise. Still, it is well-organized and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the tool (4 operations, 4 schemes, 6 parameters) and the presence of an output schema, the description combined with the schema is complete. The description covers all operations and schemes, and the schema provides full parameter details. The rule allows that output schema need not explain return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description provides high-level operation summaries (e.g., what each operation needs) but does not add significant per-parameter meaning beyond what the schema already provides. The schema descriptions themselves are thorough, so the description adds marginal value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a 'Week Number Calculator' and lists four specific operations (fromDate, toDate, weeksInYear, weekRange) with detailed explanations of each. It also distinguishes from sibling tools time_day_of_week and time_date_calculator by specifying their different use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool: 'Use this for ISO week numbers or week-to-date conversion' and when not to use: 'use time_day_of_week for the weekday name of a date and time_date_calculator for adding/subtracting durations or business days.' This provides clear guidance on alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds value beyond annotations by stating it runs locally, is read-only, non-destructive, contacts no external service, and is rate-limited. Also describes return format components.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Slightly long but informative and front-loaded with purpose. Efficient use of words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (7 params, output schema present), description covers purpose, usage, behavior, and output format adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so description doesn't need to repeat parameter details. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it infers a JSON Schema (Draft-07) from a sample JSON document. Distinguishes from sibling tool webdev_json_schema_validator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use this to draft a schema from existing data and to use webdev_json_schema_validator to check an instance against a schema. Provides alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes local execution, read-only, non-destructive, no external service, rate-limited, and specifics of type checks, adding context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Multiple sentences, each serving a purpose (transformation, type check, usage guidance, limitations), with no redundancy, though slightly long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers transformation, type checking, limitations, alternatives, and behavioral traits; output schema exists so return values not needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions, so description adds little new param info; it provides context like 'optional ES5 downleveling' but doesn't enhance semantics beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it transpiles TypeScript to JavaScript via regex stripping, and explicitly distinguishes from siblings like webdev_json_to_typescript and webdev_javascript_beautifier.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use (preview compiled output, catch type errors) and when-not (does not execute code), and names specific alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. The description adds valuable behavior details: local regex tokenizer, no external entity resolution, offline operation, rate limits, and return structure (isValid flag, errors, statistics). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense paragraph that covers multiple aspects efficiently. Every sentence adds value, but it could be more scannable with bullet points or shorter sentences. Still, it is not overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, output schema exists), the description covers all essential aspects: purpose, usage alternatives, behavior, constraints, and return values. The existence of an output schema reduces the need to explain return format, but the description still mentions it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description summarizes key parameters (prettyPrint, attributePrefix, etc.) but adds minimal extra meaning beyond schema descriptions. It does not explain parameter interactions or provide examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's verb ('Convert'), resource ('XML document'), and output ('JSON object'). It distinguishes from sibling tools like webdev_xml_formatter and webdev_json_to_csv by naming them explicitly and advising when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool (XML to JSON conversion) and when to use alternatives (format_json, webdev_json_to_csv, webdev_xml_formatter). It also describes important constraints: XXE-safe, offline, rate-limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true), the description adds important behavior: runs locally, offline, no auth, default rate limit. Also describes return value structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and concise, front-loading purpose and usage, then behavior. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool's complexity (5 parameters, multiple modes, fractional support, signed/unsigned, bit width), the description covers essential usage, behavioral traits, and return value. Paired with output schema and annotations, it's complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good parameter descriptions. The description adds minimal per-parameter meaning beyond the schema, but includes global context. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts a single number between binary and decimal, with specific details about direction, bit width, and fractional support. It distinguishes from siblings by naming alternative tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use this tool (bit-level detail for one number) and when to use alternatives (conversion_base_converter, conversion_number_base, conversion_decimal_hex). Provides clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds behavioral details: runs locally, read-only, non-destructive, rate-limited (60 req/min for anonymous), and auto-detects formats. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded and well-organized, but appears truncated at the end ('...varies between cal'). This indicates the provided text is incomplete, reducing conciseness and structure. Otherwise, it would be a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite truncation, the description covers input format auto-detection, output fields, constraints, behavioral traits, and alternative tools. Given the existence of an output schema, this is comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds useful context: the 'input' parameter also accepts alias keys ('timestamp' or 'text'), must not be blank, and the 'now' parameter is optional for relative phrases. This exceeds baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Unix Timestamp Converter' and explains it converts between Unix epoch timestamps and human-readable dates. It auto-detects input formats and distinguishes itself from sibling tools like time_iso_8601_formatter and time_date_difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool vs alternatives by naming specific sibling tools and explaining differences. Also notes constraints: requires non-empty input and does not fall back to current time.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds critical context: runs server-side, rate limits (5/min, 30/hr, 100/day), CAPTCHA trigger, and return type (match status + parsed parameters). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences: purpose, usage vs alternative, and behavioral details (rate limits, output). Front-loaded with key info; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 required params, output schema exists), the description covers purpose, usage, behavior, rate limits, and output. Annotations and schema are rich, so no gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema covers both parameters fully (100% coverage with descriptions and examples). Description adds that hash includes cost parameters, but this is already in the schema's description of 'hash'. No additional meaningful semantics beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose ('verify a plaintext password against an Argon2 hash') and distinguishes it from the sibling 'crypto_argon2' (generate new hash). The verb 'verify' and resource 'Argon2 hash' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use ('to verify a candidate password') and when not ('use crypto_argon2 instead to generate a new hash'). Also notes behavior: read-only, non-destructive, no external service, and rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds useful context: runs locally, deterministic, rate-limited (5 req/min for anonymous), contact no external service, and details output fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but well-structured, front-loading purpose and usage, then behavioral details, then output. Every sentence adds information, though slightly verbose for a concise tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, and the description details the return fields (digest formats, variant, algorithm, encoding, byte length, bit count, keyed flag). No gaps for this hash tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 100% schema coverage, the description adds significant value: explains variant optimization (64-bit vs 8-32-bit), encoding interpretation, keyed mode behavior, and return metadata (lowercase/uppercase hex, flags).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes BLAKE2b or BLAKE2s digests of a text string, with explicit variant options and keyed mode. It distinguishes from siblings like crypto_blake3, crypto_hash, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when to use (e.g., 'when you want an RFC 7693 digest faster than SHA-2 at SHA-3-level security') and directs to alternatives for other needs (crypto_blake3 for XOF, crypto_hash for MD5/SHA, etc.).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds local execution, determinism, no external service contact, rate-limiting, and return structure, fully disclosing behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences covering purpose, usage, behavior, and return value with no unnecessary words, well structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description adequately explains inputs, outputs, and behavioral context, leaving no gaps for selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all parameters with descriptions, defaults, and enums. The description adds minimal meaning beyond the schema, e.g., noting hex case, but this is already in the outputFormat parameter description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes hash digests of a UTF-8 string, lists supported algorithms, and distinguishes from siblings like crypto_checksum, crypto_hmac, and crypto_hash_identifier.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool vs alternatives: 'Use crypto_hash for general text digests; use crypto_checksum for...', providing clear decision guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations show readOnlyHint=true and destructiveHint=false. The description adds key transparency details: local execution, crypto.getRandomValues, rate limits (30/min, 200/hr, 1000/day), and non-destructive nature. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is 5 sentences, well-organized, front-loading the purpose and usage, with no redundant or unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, optional output schema), the description covers purpose, usage, behavioral details, and links to alternatives. The mention of return structure complements the output schema, making it complete for effective agent selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good parameter descriptions; the tool description does not add additional semantic meaning beyond what the schema already provides, though it does reference the output structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the purpose as generating diceware-style passphrases, specifies the verb 'generate', and distinguishes from sibling tools (crypto_password_generator, crypto_password_generator_pin) by noting their different use cases (dense passwords, numeric codes).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('for human-typable word passphrases') and when to use alternatives ('use crypto_password_generator for dense mixed-character passwords or crypto_password_generator_pin for numeric-only codes'), providing clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the description adds value by detailing non-deterministic output when no salt is supplied, local execution, and return of derived key, encoded hash, salt, and strength analysis. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is 4-5 sentences, well-structured, and front-loaded with the tool's main purpose. Every sentence adds essential information without redundancy or fluff, making it efficient for an AI agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, 1 required, an output schema, and annotations, the description covers purpose, usage guidelines, behavioral traits (non-determinism, local execution, rate limit), and key return fields. It is complete for an agent to decide and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining that if no salt is supplied, a random 16-byte salt is generated, making output non-deterministic. It also mentions the salt length range (8–128 characters) aligning with schema min/max. This enriches parameter understanding beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'PBKDF2 Hash Generator' and explains it derives a hash from a plaintext password, specifying the tool's verb and resource. It distinguishes from siblings by naming crypto_pbkdf2_verify and alternative KDFs (argon2, bcrypt, scrypt).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this to create a new hash; use crypto_pbkdf2_verify to check a password against one.' Provides guidance on when to prefer other KDFs and mentions rate limiting (5 requests/min anonymous), giving clear context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already show readOnlyHint=true and destructiveHint=false. The description adds critical context: runs locally, contacts no database, rate-limited (30 req/min), deterministic vs non-deterministic behavior for different algorithms, and returns hash with metadata (version, algorithm, salt, etc.).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph with front-loaded purpose, then usage, alternatives, behavioral notes, algorithm details, and return structure. Every sentence earns its place; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the description, annotations, and output schema, this is highly complete. It covers purpose, when to use/avoid, behavioral traits, algorithm details, and return value structure. No obvious gaps for a deterministic input-output tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptive parameter fields. The description adds little beyond schema for password and username, but clarifies version algorithm behavior (deterministic for md5, random salt for others). This adds marginal value over schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it hashes passwords into PostgreSQL credential formats, lists use cases (CREATE ROLE statements, pg_hba.conf, test fixtures), and distinguishes from siblings crypto_mysql_password_generator and crypto_password_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use context and alternatives: 'use crypto_mysql_password_generator for MySQL hashes instead, and crypto_password_generator to invent a new random plaintext rather than hash one.' Also notes it runs locally.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond annotations: local execution, read-only, non-destructive, deterministic, no external service, and rate-limited (5 req/min). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single well-structured paragraph with no wasted words: starts with title, outputs, alternatives, properties, and safety features.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description adequately covers return values (hex digest, uppercase, byte length, truncations) and explains safety and rate limiting. Complete for a hashing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description mentions 'text string' and 'byte length' but adds little beyond schema's descriptions of 'text' and 'encoding' parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it is a Whirlpool hash generator, specifies the output (128-character hex digest, uppercase, byte length, truncations), and distinguishes from siblings like crypto_hash and crypto_sha3.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: use crypto_hash for MD5/SHA-1/SHA-256/SHA-512, crypto_sha3 for SHA-3/Keccak, crypto_ripemd for RIPEMD, and notes Whirlpool is for file integrity and digital signatures.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds details beyond annotations: ignores whitespace on decode, validates payload, runs locally, is read-only, rate-limited, and describes return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence is informative, front-loaded with purpose, no redundancy, well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers input, output, behavior, alternatives, constraints; output schema present; no gaps for a text encoding tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description mostly repeats schema info; adds no significant new meaning beyond what is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a Base64 encoder/decoder for UTF-8 text, and distinguishes from sibling tools for files, images, and other bases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (text only) and when to use alternatives (file, image, other bases), providing clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses behavioral traits beyond annotations: it runs locally, is read-only, non-destructive, contacts no external service, and is rate-limited. It also describes the return value (transformed text, character analysis, visual zigzag pattern). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, well-structured, and front-loaded with the purpose. Every sentence adds value, and the information is presented in a logical order without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity, 100% schema coverage, and presence of annotations and output schema, the description is complete. It covers purpose, usage, behavior, parameters, return values, and alternatives adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds some context (e.g., 'rails must be an integer 2-50'), but this is already in the schema. Minimal additional value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a Rail Fence cipher for encoding/decoding, explains the zigzag mechanism, and distinguishes it from other ciphers. It specifies the verb 'Encode or decode' and the resource 'Rail Fence cipher', making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is given: use this tool for zigzag transposition, and choose Caesar or Vigenere for substitution ciphers. It also states the tool is for puzzles, CTFs, and learning, not for protecting secrets, providing clear when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond annotations: local execution, offline, rate-limited, and output details (transformed string, format metadata, escaping analysis, supported formats). Annotations already declare readOnlyHint=true, destructiveHint=false, etc., and description does not contradict them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (4 sentences) and front-loaded with purpose, then usage guidelines, behavioral notes, and return info. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all necessary context: purpose, usage, behavioral traits, and output. With 3 parameters, output schema, and clear sibling differentiation, it is complete for effective tool selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter having description, examples, and enum values. The description echoes the format list but does not add significant semantic value beyond the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool escapes or unescapes string literals for specific syntaxes (SQL, CSV, shell, regex, etc.) and explicitly distinguishes it from encoding_decoding_url and encoding_decoding_html_entities, which are similar sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool vs. alternatives: 'Use this for language/format string-literal quoting; use encoding_decoding_url for percent-encoding and encoding_decoding_html_entities for HTML entity conversion.' Also mentions it runs locally, read-only, non-destructive, offline, and rate-limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses behavioral traits beyond annotations: 'It only BUILDS the command text — it never runs chmod, changes any mode, or touches the filesystem.' It also mentions idempotence, offline operation, and rate limits. Annotations already provide readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds context without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with the most important information first. It is slightly verbose but each sentence adds value. The division into usage, behavior, and alternatives is clear. No wasted words, but could be trimmed slightly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, diverse input formats) and the presence of an output schema, the description is complete. It covers purpose, usage, behavior, parameters, and safety. The agent can correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful detail beyond the input schema. For example, the permissions parameter explanation covers octal vs symbolic notation and special bits. The path parameter is described as 'interpolated verbatim'. The recursive, symbolic, and explanation parameters have clear semantics. Schema coverage is 100%, and the description enriches all parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Chmod Permission and Command Generator. Convert Linux file permissions between octal and symbolic notation and assemble the matching chmod command string.' It distinguishes itself from siblings like linux_command_builder and linux_user_group_manager by explicitly naming alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use the tool: 'Use it to look up or teach permission values and produce a copy-paste command.' It also states when not to use it and suggests alternatives: 'use linux_command_builder for find/grep/rsync/tar commands, linux_user_group_manager for useradd/usermod, and octal/base converters for raw number-base math.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and destructiveHint=false. Description adds that it uses crypto.getRandomValues (CSPRNG) with rejection sampling for bias elimination, optional deterministic PRNG with seed, and rate limiting (60 req/min). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise (3-4 sentences), front-loaded with main purpose, and every sentence adds value. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, output schema exists), the description covers purpose, sibling differentiation, behavioral details, parameter relationships, and return format. Output schema exists but description mentions 'returns generated values as an array', which is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. Description adds context beyond schema: explains that operation determines which fields are required, and warns that seeded output is not cryptographically secure. Provides meaningful guidance not in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates cryptographically secure random values and lists specific value families (integers, floats, booleans, UUIDs, hex, bytes). It distinguishes itself from data_random_data_generator for structured records, providing a specific verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (one numeric/token-style family per call) and when not to (use data_random_data_generator for structured data). Also warns against using seeded output for security-sensitive purposes. Provides clear alternative and context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds rate limiting (60 req/min anonymous), deterministic and local nature, and error behavior (HTTP 400). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise 6 sentences covering all aspects without redundancy, front-loaded with purpose, well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with multiple operation modes and 10 parameters, the description adequately covers purpose, usage, behavior, and error handling. Output schema covers return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already describes all parameters (100% coverage). Description adds minimal beyond explaining decimal minutes format and operation-specific roles, but not enough to warrant a higher score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it converts running pace/speed, computes splits, and predicts race times via operation field. It explicitly distinguishes from siblings by directing general conversions to math_unit_converter and fuel economy to math_fuel_consumption_calculator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides explicit when-to-use for each operation (convert, splits, predict) and when-not-to-use by naming alternative tools for general conversions and fuel economy.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. The description adds valuable runtime behavior: local execution, no external service contact, deterministic, rate-limited (60 req/min), and exact NIST conversion factors. This goes beyond annotations without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, front-loading the core purpose, then providing usage guidance, behavioral details, and parameter examples. Every sentence adds value, and there is no redundancy. The truncated ending is assumed complete; otherwise still concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (5 parameters, 3 operations, many categories) and the presence of an output schema, the description covers all essential aspects: purpose, supported categories, behavioral traits, usage guidelines, and operation semantics. No significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, baseline is 3. The description enhances parameters by listing examples for fromUnit/toUnit (e.g., 'length m/cm/km/in/ft/mi') and explaining the category enumeration. This adds meaningful context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a physical unit converter, specifies the exact operation (converting numeric values between units within a category), lists all supported categories, and differentiates from sibling tools like running pace, file size, and currency converters by naming alternatives explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use this tool versus alternatives (e.g., 'Use math_running_pace_converter instead for running pace/speed splits...'). It also explains the three operations (convert, listCategories, listUnits) and their typical usage contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Explicitly states it is NOT read-only and NOT idempotent, results vary by resolver/caching/TTL, and rate-limited. This goes beyond annotations (which set hints) to provide behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise, front-loaded with primary action, and includes all necessary details in a well-structured manner. No unnecessary sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, description covers return format. It addresses side effects, rate limits, and comparison to siblings, making it complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. The description adds minor context (default resolver, PTR auto-reverse) but does not significantly enhance parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs DNS lookups resolving A, AAAA, MX, etc. records. It distinguishes from sibling tools network_reverse_dns and network_dns_propagation by explicitly comparing usage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (forward/record-type lookups) and when not (use network_reverse_dns for IP->hostname, network_dns_propagation for global prop). Also mentions rate limits (20 req/min) guiding agent expectations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behaviors: pure offline math, never pings or contacts hosts, rate-limited (30 req/min), and read-only. It adds beyond annotations (which already declare readOnlyHint, destructiveHint, idempotentHint) by specifying rate limits and the operations' output structure. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single well-structured paragraph that front-loads the purpose, then details operations and usage. It is dense with information but could be slightly more concise; however, it avoids fluff and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three operations, the description covers all modes, explains output for analyze, mentions rate limits and alternatives. With an output schema present, it doesn't need to detail return values. However, it could mention what happens if no input is provided for analyze, so not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the 'analyze' mode expects latency samples in ms, that non-finite or negative values are invalid, and that 'input' is an alias for 'latencies'. This provides context beyond schema but does not fully detail each parameter's format, so above baseline but not perfect.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes descriptive statistics and performance verdict from latency measurements, and distinguishes three operations (analyze, convert, benchmarks). It explicitly notes it never pings or contacts any host, differentiating it from sibling tools like network_ping or networking_mtu_size_calculator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool: for interpreting ping/speedtest samples, and when to use alternative tools (live Ping, Internet Speed Test, MTU Size Calculator). It also mentions rate limits (30 req/min anonymous) and read-only nature, providing clear context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite annotations already declaring readOnlyHint=true and destructiveHint=false, the description adds valuable behavioral context: outbound network request, dependency on live third-party data, rejection of private/reserved IPs, and rate limits (10 req/min, 300/day anonymous). This goes beyond the minimal annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense paragraph that efficiently conveys purpose, usage, behavioral details, constraints, and output structure. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (external API, rate limits, private IP validation) and the presence of an output schema, the description covers all essential aspects: what it does, how to use it, behavioral caveats, constraints, and output structure. No gaps are evident.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for both parameters (ip and worker_id). The description adds some context (e.g., IP must be public, output objects listed) but does not significantly enhance parameter semantics beyond the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool resolves a public IPv4 or IPv6 address to geographic location and network owner using ip-api.com. It distinguishes itself from sibling network_my_ip by specifying that this tool requires an input IP while the sibling geolocates the caller's own IP.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('when you have an IP and need its country, city, coordinates, ISP/ASN...') and when to use the alternative network_my_ip. This provides clear decision guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description reinforces this by stating it is read-only, non-destructive, does not crawl proxies, and adds concrete rate limits and session scope. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense paragraph that front-loads the core purpose and covers all critical details without unnecessary fluff. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (captcha, session limits, rate limits, output format), the description addresses all key aspects. It mentions the output format (HTML rows, count, done flag) even though an output schema exists. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters have schema descriptions (100% coverage). The description adds meaningful context: token required only on first reveal, filters must match initial view, and alternative header method. This goes beyond schema definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's purpose: revealing additional rows of the Free Proxy List beyond the initial 50. It specifies the resource, action, and constraints (captcha-gated, 200-row cap), and differentiates from the companion tool network_proxy_list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (to load more than 50 rows) and prerequisites (matching filters, reCAPTCHA token on first call). It implies when not to use (e.g., when initial page suffices), though not explicit. Alternatives are implied via sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already set readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds valuable context: pure local parsing, no external contacts, and rate limits (2/min, 10/hour, CAPTCHA after 5/hour). This enriches behavioral understanding without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is four concise sentences: title-like opener, operational detail, usage guidance with alternatives, and behavioral constraints. No extraneous information; every sentence provides essential value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, when to use, behavioral traits (local, rate limits), and output summary (parsed proxies, parse errors, counts). Although an output schema exists, the description adequately summarizes return values without redundancy.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter (proxies) has 100% schema description coverage. The description adds extra meaning by specifying the expected format (protocol://user:pass@host:port, defaults to http, port range 1-65535) and skipping rules (blank lines, # comments), exceeding the schema's examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a parser for proxy lists, specifying the action (parse) and the resource (newline-separated proxy list). It details the output structure (protocol, host, port, optional credentials) and distinguishes from siblings by explicitly naming security_proxy_test for actual connections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (validate/normalize before testing) and when to use alternatives (security_proxy_test for connecting/benchmarking), making the selection decision clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses results not cacheable, makes outbound connections to fixed endpoints, target URLs not configurable, rate-limited with specific limits and CAPTCHA. This goes beyond annotations which only give hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, dense paragraph that is front-loaded with purpose. Every sentence adds value; no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, behavioral traits, rate limits, and alternatives. Output schema exists, so description doesn't need to detail return values. Complete for complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with detailed descriptions for all parameters. The tool description adds minimal extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool batch-tests many proxy servers, listing specific checks (HTTP/HTTPS, speed, anonymity, IP leak, etc.). Distinguishes from siblings by mentioning batch vs single vs stream.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use alternatives: use security_proxy_parse first to normalize input, security_proxy_test_single for one proxy, security_proxy_test_stream for incremental results. Also notes non-cacheable nature and rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true. Description elaborates that it makes outbound connections, measures live network state, varies between calls, and is rate-limited. This adds useful context beyond annotations, though it could mention idempotence explicitly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph efficiently covers purpose, functionality, usage guidelines, and constraints. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (network testing, live results, rate limits, CAPTCHA), the description addresses all key aspects: what it does, how to use it, limitations, and alternative tools. Output schema existence is noted but not needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema defines 2 parameters with full descriptions. Description adds value by linking proxy parameter to security_proxy_parse and clarifying optional originalIp defaults. No contradictions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool tests a single proxy synchronously, returning full results. It specifies measured attributes (reachability, speed, anonymity, etc.) and differentiates from sibling tools like security_proxy_test, security_proxy_test_stream, and security_proxy_parse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises to use security_proxy_parse first, and contrasts this tool with batch and streaming alternatives. Also mentions CAPTCHA and rate limits, providing clear when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly=true, destructive=false, idempotent=true. Description adds specific rate limit (60 req/min for anonymous), confirms local execution, no external service, and describes return value (transformed string plus stats and effective options).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences pack essential info: purpose, use cases, behavior, and output. No fluff, front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 params, 100% schema coverage, annotations, and an output schema (implied by description mentioning stats), the description covers all needed context: what tool does, how to choose granularity, guidance vs siblings, safety/limits, and return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 5 parameters with 100% description coverage, so baseline is 3. Description mentions targetType and implies use cases for affixes but does not add new parameter-level details beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a clear action 'Add Prefix And Suffix To Text' and specifies the granularity options (lines, words, characters). It names exact siblings (text_add_line_numbers, text_joiner) to distinguish this tool's purpose of wrapping elements with fixed affixes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (wrap, indent, comment out, quote, tag) and when to use alternatives (sequential numbering -> text_add_line_numbers, concatenate with separator -> text_joiner). Also notes it runs locally, is read-only, and rate-limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), the description adds that the tool runs locally with no external input, is read-only, non-destructive, offline, and rate-limited. These details align with and enhance the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences plus a practical usage note. It is front-loaded with the main purpose and efficiently covers all key aspects without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, an output schema exists, and the description covers purpose, usage, parameters, behavior, and safety. No gaps are evident.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters. The description mentions format and extended options but does not add substantial meaning beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates the full ASCII character reference table with all code points, values, glyphs, descriptions, categories, and printable flags. It explicitly distinguishes from sibling tools like text_hex_ascii_converter and conversion_number_base.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use and when-not-to-use guidance: 'Use this for a complete lookup table; use text_hex_ascii_converter or conversion_number_base instead to convert a specific string between bases.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds critical context beyond annotations: 'Runs locally', 'read-only', 'non-destructive', 'deterministic', 'contacts no external service', 'rate-limited (60 requests/minute)'. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose. First sentence enumerates styles, second adds guidance and behavior. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, description mentions return value (converted text plus statistics). Annotations provide safety profile. Complete for a text conversion tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description lists the 15 case styles, which is redundant with the enum in schema, adding no new meaning beyond what schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Convert Text Case' and lists 15 specific styles. It differentiates from sibling tools reverse_text and sort_lines by specifying when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use it to reformat identifiers, headings, or prose; use reverse_text instead when you only need character/word/line/sentence reversal, or sort_lines to reorder lines.' Provides clear alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds that it is 'pure local compute: read-only, non-destructive, offline, rate-limited (60 requests/minute)'. It also handles edge cases like empty input yielding zeroed stats, and explains the behavior of showLineNumbers and skipBlankLines parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, starting with the core purpose, followed by outputs, usage guidance, limitations, and non-functional properties. It is efficient and every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, output schema exists), the description covers all necessary aspects: input handling, output details, rate limits, safety profile, and comparisons to siblings. It is complete for agent selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds minimal extra per-parameter detail beyond the schema; it reiterates parameter effects but doesn't provide additional semantic meaning for the parameters. It does mention edge cases like empty input, which is slightly beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool counts and analyzes text lines, providing specific metrics like total lines, non-empty lines, blank lines, line-length stats, and line numbers. It also distinguishes itself from sibling tools by naming alternatives (text_counter, text_text_statistics, text_sort_lines) and explaining what it does not do (deduplication).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is given: 'Use this for line-focused metrics; use text_counter or text_text_statistics for word, character, sentence, and readability metrics, or text_sort_lines to reorder lines.' It also clarifies that it does not deduplicate, helping the agent decide when to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and destructiveHint. Description adds non-deterministic nature, optional fixed opening, and rate limits (60 req/min) without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise, front-loaded with key info (verb, resource, variants), and every sentence adds value. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, 100% schema coverage, annotations, and output schema existence, the description covers purpose, usage, behavioral traits, and output details (character/word counts) comprehensively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so each parameter is described in schema. Description adds minor clarifications like fallback behavior for invalid type and clamping range, but does not significantly enhance understanding beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates random Lorem Ipsum placeholder text, and distinguishes from siblings by mentioning text_lorem_ipsum_variations for themed vocabularies and data_data_faker/data_sample_data_generator for structured fake records.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (neutral placeholder/dummy copy in mockups, UI prototypes, layout testing) and when not to, with specific alternative tools named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses local execution, read-only, non-destructive, rate-limited behavior beyond annotations. No contradiction with annotations; adds value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph, front-loaded with purpose, then guidelines, then behavior. Every sentence adds value. No redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given high schema coverage and output schema existence, description covers usage, behavior, return value, and context. Complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds minimal extra meaning beyond schema; mentions 'optionally preserving per-line layout' which echoes the preserveFormatting parameter. Acceptable but not enhanced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a clear verb 'Reverse Text' and specifies the resource (text block) and granularities. It explicitly distinguishes from siblings like text_palindrome_checker, text_case_converter, and text_randomizer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('flip or mirror text') and names specific alternatives for other operations, providing clear usage context with exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds critical behavioral context: 'Read-only, non-destructive pure computation that runs in-process with no network or storage; rate limited to 60 req/min (anonymous) / 120 req/min (authenticated). Returns the processed text plus before/after line/character/word stats and the resolved options.' No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is thorough yet efficient: a single, well-structured paragraph. It front-loads the purpose, then explains operations, usage conditions, and technical details. Every sentence earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, multiple operations, existing output schema), the description covers all necessary aspects: operations, usage context, behavioral traits, rate limits, and return values. The output schema provides the return format, so the description does not need to repeat it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description briefly ties operations to parameters (e.g., columnNumber for extract) but does not add substantial meaning beyond the schema definitions. It's adequate but not exceptional.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a clear verb+resource: 'Extract, Align, or Analyze Columns in Delimited Text.' It explicitly lists three operations and distinguishes the tool from siblings like text_splitter, text_joiner, and csv_json, leaving no ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: 'Use this for columnar/tabular text (CSV, TSV, space-separated logs) when you need a single column or aligned table.' It also names alternatives for other use cases, making it clear when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive, but the description adds key behavioral details: runs locally, contacts no external service, rate-limited to 60 req/min, and returns statistics along with the randomized text. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two well-structured paragraphs. First paragraph introduces purpose, modes, and sibling differentiation. Second covers behavioral constraints and return info. Every sentence adds value; no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (mentioned in context), the description appropriately summarizes return values. It covers all essential aspects: modes, default, seeding, formatting options, local execution, rate limits, and sibling comparisons.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description reiterates the enum modes and default, and adds that preserveFormatting only applies to words/characters modes (already in schema). It does not add significant new meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool randomizes/shuffles text with five specific modes (words, lines, characters, sentences, paragraphs). It explicitly distinguishes from siblings text_sort_lines and reverse_text by contrasting deterministic vs. non-deterministic behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit use cases: puzzles, test fixtures, anonymizing data. It also contrasts with sort_lines (deterministic) and reverse_text (exact reversal), and explains when to use a seed for reproducibility.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, description discloses local execution, read-only nature, rate limits, non-idempotence of random scheme, and output details (hex, RGB, HSL, contrast). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a concise paragraph with front-loaded purpose, every sentence adds value, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool complexity (3 params, output schema exists), the description covers purpose, usage, behavior, parameters, and output, making it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description adds limited input info beyond schema. It notes random scheme non-idempotence (relevant to paletteType) but otherwise the schema fully documents parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a harmonious color palette from a base hex color using a chosen scheme, distinguishing it from sibling tools like webdev_css_gradient_generator and webdev_hex_color.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when to use this tool (multi-color scheme from one seed) and when to use alternatives (gradient, single color).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint false, idempotentHint true. The description adds specific behavioral context: runs locally, non-destructive, rate-limited (60 req/min anon), and contacts no external service. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise paragraph that front-loads the main purpose, then efficiently covers usage guidelines, behavioral context, and return value details. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, 100% coverage, annotations, output schema present), the description is complete: it explains purpose, when to use, behavioral traits, rate limits, and explicitly states the return value includes JSON string, validity flag, warnings, and statistics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description mentions features like 'custom delimiter/enclosure/escape, optional header row, and array-of-objects or array-of-arrays output' but does not add meaningful detail beyond what the schema already provides with examples and descriptions for each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'CSV to JSON Converter' and enumerates key features like type coercion, custom delimiters, and output formats. It distinguishes from sibling tools by naming webdev_json_to_csv for reverse conversion, json_formatter for pretty-printing, and text_column_tool for column extraction without conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool vs alternatives, providing direct references to reverse tool, pretty-printing tool, and column-alignment tool. It also states it 'runs locally' and 'contacts no external service', and gives rate limits (60 req/min anon).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds valuable operational context: runs locally, no external service, rate-limited. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that efficiently convey purpose, capabilities, usage guidelines, and behavioral traits. Front-loaded with main action. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given tool complexity (multiple formats, palettes, analysis), description covers all key aspects. Output schema exists, but description still details return content. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage 100% with detailed description and examples. Description adds that whitespace and case are ignored, and invalid input returns HTTP 400, enhancing understanding beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it parses a color string and returns multiple formats, palettes, and WCAG analysis. Explicitly distinguishes from sibling tools conversion_color_code and webdev_color_palette.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises when to use alternatives: 'Use conversion_color_code for a focused HEX/RGB/HSL/HSV conversion... or webdev_color_palette when you only want harmony schemes.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false. The description adds critical behavioral context beyond annotations: 'Runs locally on the data you provide: read-only, non-destructive, contacts no external service, and is rate-limited (30 requests/minute for anonymous callers).' No contradiction is present.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: it starts with the core functionality, then lists output features, usage guidance, and safety notes. Every sentence adds value, and the structure is logical without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, nested object, output schema), the description covers purpose, usage, behavior, and output components. It mentions the output fields (hexDump, totalBytes, byteDistribution, fileTypeHint) without needing to detail them further due to the presence of an output schema. It is complete and self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds context about input decoding methods (text, hex, base64) and mentions that blank input yields an empty dump, but does not significantly enhance parameter understanding beyond the schema. The description also summarizes output fields, which is helpful but not directly about parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Hex Viewer And Binary Analyzer' that produces a hex dump with offset, hex bytes, ASCII gutter, byte statistics, frequency distribution, and file-type hint. It explicitly distinguishes itself from sibling tools such as webdev_base64_image_encoder and encoding_decoding tools, specifying alternative use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: 'Use this to inspect or analyze the raw bytes of arbitrary data; use webdev_base64_image_encoder instead to turn an image into a Base64 data URI, or an encoding_decoding tool to convert between encodings.' This clearly states when to use the tool and when not, with specific alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds significant context beyond annotations: runs locally, read-only, non-destructive, deterministic, offline, no external service, rate-limited, and returns specific output structure. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise paragraphs front-loaded with the main action. Every sentence adds value; no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fully covers purpose, behavior, output format, rate limits, and sibling differentiation. Given the tool's complexity and the presence of an output schema, the description is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions and examples. The description does not add new semantic info beyond what the schema already provides for the two parameters. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it converts HTML to Markdown using regex-based rules, lists supported elements, and distinguishes from sibling tools by naming web_dev_markdown_to_html for the inverse and webdev_html_minifier for shrinking HTML.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool (convert web content, emails, HTML documents) and when to use alternatives (web_dev_markdown_to_html, webdev_html_minifier). Also clarifies that options are accepted but ignored for forward compatibility.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds critical behavioral details: runs locally, read-only, non-destructive, offline, no external service, rate-limited, and returns formatted code with stats and syntax warnings. It also clarifies it does not transpile or fully validate, which is valuable beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long. The first sentence states the core purpose and key features; the second covers usage guidance, behavioral transparency, and output. Every sentence adds value, and critical information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description does not need to detail return values. It covers purpose, usage, behavioral traits, and output summary (formatted code, stats, warnings). The parameter schema is comprehensive, and the description complements it well. No obvious gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description mentions configurable options (indent, brace style, etc.) but does not add meaning beyond what the input schema already provides (each option has a description and examples in the schema). No additional parameter guidance is given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a JavaScript beautifier that pretty-prints and re-indents minified or messy JavaScript. It explicitly distinguishes from siblings webdev_js_minifier (reverse operation) and webdev_code_formatter (HTML/CSS in one pass), fulfilling the specific verb+resource+scope requirement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool ('use it to make JS readable') and names alternatives for other scenarios ('use webdev_js_minifier for the reverse... and webdev_code_formatter when you also need HTML/CSS in one pass'). This provides clear selection guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes behavior beyond annotations: 'Runs locally on the input you provide: read-only, non-destructive, contacts no external service, idempotent, and rate-limited (60 requests/minute for anonymous callers). Returns the CSV string plus validity, warnings, the discovered column headers, and row/column/size statistics.' Annotations already include readOnlyHint, destructiveHint, idempotentHint; description adds local execution, no external service, rate limits, and specific output. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. First sentence states purpose, then detailed conversion options, followed by usage guidelines, behavioral transparency, and output summary. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 8 parameters, 100% schema coverage, an output schema (mentioned), and thorough annotations, the description covers all necessary aspects: purpose, usage, behavior, parameter hints, and output. It is complete for an AI agent to correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add significant meaning beyond what the schema provides for each parameter. It lists parameters but does not elaborate on semantics or provide usage examples. Score is adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts JSON to CSV, specifying the input as 'JSON array of objects (or a single object)' and output as 'CSV text'. It distinguishes itself from siblings like webdev_csv_to_json (reverse), format_json (pretty-print/validate), and data_sample_data_generator (fabricate rows).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'turn structured JSON into spreadsheet-ready rows'. Provides clear alternatives: 'for the reverse direction use webdev_csv_to_json, to pretty-print or validate JSON use format_json, and to fabricate demo rows use data_sample_data_generator'. Also mentions 'This tool only converts JSON to CSV (no reverse).'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, non-destructive, and idempotent. Description adds rate-limiting (60 req/min), local execution, and that it returns formatted SQL plus statistics. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with purpose, no unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With rich schema, annotations, and output schema, the description covers the tool's scope, limitations, and behavior completely. It differentiates from siblings and explains what it does and does not do.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description does not add new parameter info beyond what schema provides; statistics mention is about output, not parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it's a SQL formatter/beautifier that reformats SQL with consistent indentation and keyword casing, and reports statistics. It explicitly distinguishes itself from sibling tools webdev_graphql_formatter and webdev_json_formatter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use for SQL formatting, and to use webdev_graphql_formatter for GraphQL and webdev_json_formatter for JSON. Also clarifies it never connects to a database, so it's safe for any SQL text.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true and destructiveHint=false. The description adds valuable context: runs locally, contacts no external service, rate-limited (60 req/min), and details the return fields (optimized markup, sizes, ratio, optimizations list, base64 preview). No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured. It starts with the core purpose, lists operations, provides usage instructions, compares with siblings, mentions behavioral traits, then return values. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters (one nested), the description covers purpose, input format, alternatives, behavioral traits (local, rate-limited), and output fields. With an output schema implied, the description is sufficiently complete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds minimal value beyond the schema, merely reiterating that the svg field receives raw SVG text and that options have defaults. The return value details are helpful but not parameter-specific.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: optimize/minify SVG strings. It specifies operations (strip XML declaration, comments, DOCTYPE, etc.) and distinguishes from siblings by naming related tools for CSS/HTML and data URI generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (for SVG optimization) and when to use alternatives (webdev_css_minifier for CSS, webdev_html_minifier for HTML, webdev_data_uri_generator or webdev_base64_image_encoder for embedding). Also clarifies that it runs locally and is read-only, guiding appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent. Description adds important details: regex-based parser (not full XML processor), rate limit of 30 requests/minute, local execution via Node bridge, and error handling behavior. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, well-structured paragraph covering purpose, features, alternatives, limitations, and performance. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters, full schema coverage, and existing output schema, the description adequately covers purpose, usage context, behavioral traits, and limitations. It is complete for an AI agent to decide when and how to use this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. Description summarizes parameter categories but does not add significant semantic value beyond what the schema already provides for each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it formats and validates XML, listing specific features like pretty-print, attribute sorting, comment removal, and optional declaration. It distinguishes itself from siblings by naming alternative tools for XML-to-JSON conversion and other language formatters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use alternatives: 'Use webdev_xml_to_json when you need to convert XML into a JSON object rather than tidy the markup; use webdev_sql_formatter or webdev_graphql_formatter for those languages.' Also warns about limitations for complex XML.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds beyond annotations: 'Runs locally... read-only, non-destructive, contacts no external service' and 'rate-limited to 60 requests/minute'. No contradiction with readOnlyHint, destructiveHint, or idempotentHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise and well-structured: starts with core purpose, lists features, then usage guidance and technical details. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given high parameter count, full schema coverage, and rich annotations, the description completes the picture by stating return values (formatted YAML, optional JSON, validity flag, errors, warnings, statistics) and behavioral constraints (local, rate-limited).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed parameter descriptions. Description provides a high-level overview of features (e.g., sorting keys, stripping comments) but does not add significant information beyond the schema for individual parameters. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool formats, validates, and beautifies YAML, with optional JSON conversion. It explicitly distinguishes from siblings: 'Use this for YAML; use webdev_json_formatter for JSON or webdev_xml_formatter for XML.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use this tool versus alternatives for JSON and XML. Also describes local, read-only execution and rate limits, providing clear context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses 'Runs locally on the value you provide: read-only, non-destructive, offline, and rate-limited (60 requests/min anonymous).' Describes return structure. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single paragraph but well-organized; each sentence provides essential information. Slightly verbose but not excessive; could be more structured with sections.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers conversion direction, BCD explanation, supported variants, limits, rate limits, return outputs, and sibling differentiation. Output schema exists. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage describing all 4 parameters. Description adds context about BCD encoding and constraints beyond schema, e.g., 'maximum 16 digits' and explanation of outputFormat options.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'BCD Converter (Binary-Coded Decimal). Convert a decimal number to 8421 Binary-Coded Decimal (BCD), or decode BCD nibbles back to a decimal number.' with an example. It also distinguishes from sibling tools like conversion_binary_decimal and conversion_gray_code.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use conversion_binary_decimal for whole-number pure base-2/decimal conversion, conversion_gray_code for reflected binary, or conversion_parity_bit for error-detection bits.' Also notes maximum length constraints and input format requirements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds context beyond annotations: runs locally, no external service, rate limit of 60 req/min, and invalid input returns HTTP 400. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured, front-loaded with purpose. Slightly verbose but clear and provides all necessary information in a single paragraph.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, description covers input format, output, behavior, alternatives, and constraints fully. No gaps for an agent to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% but description adds parsing behavior (fallback to CSS color names), examples, and default behavior for inputFormat, enhancing understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it converts a single color string between HEX, RGB, HSL, and HSV, returning all four representations. Distinguishes from siblings webdev_hex_color and webdev_color_palette with specific use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use alternatives: webdev_hex_color for richer analysis, webdev_color_palette for harmony schemes. Also mentions it's read-only, non-destructive, and rate-limited, guiding proper usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and destructiveHint=false. The description adds that it runs locally, contacts no database or external service, is rate-limited (30 req/min), and explains deterministic vs non-deterministic behavior (SHA1-based formats are deterministic, mysql80 uses random salt). This goes beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single well-structured paragraph, front-loading the main purpose and use cases. It covers key points without excessive verbosity. Could be slightly more concise but overall effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (2 parameters, enum, simple behavior), the description covers purpose, parameters, usage, behavior, rate limits, and output (returns hash, version, algorithm, format, salt, iterations). No output schema provided but description adequately hints at return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters (password and version) with descriptions and examples. The description adds context about version-specific formats (e.g., mysql80 uses caching_sha2_password with random salt) and behavior differences, providing useful nuance beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates MySQL password hashes for a given plaintext across versions. It specifies the exact use case (building CREATE USER/SET PASSWORD statements or test fixtures) and distinguishes from sibling tools like crypto_postgresql_password_generator and crypto_password_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when to use (for MySQL password hash generation) and when not to use (for PostgreSQL, use crypto_postgresql_password_generator; for random plaintext, use crypto_password_generator). Also notes it runs locally, is read-only, non-destructive, and rate-limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses cryptographic randomness source (crypto.getRandomValues), local/non-destructive execution, and rate limits. No contradiction with annotations (readOnlyHint: true).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Mostly concise and front-loaded, though some redundancy (e.g., 'read-only, non-destructive' could be tighter). Still informative without being overly long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Comprehensive given 4 parameters and output schema present. Covers purpose, use cases, behavior, and important parameter constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds clamping ranges (4-20) and noRepeating length cap, providing context beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates numeric-only PINs and explicitly distinguishes from sibling tools crypto_password_generator and crypto_password_generator_passphrase.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when to use (numeric-only codes like device or card PINs) and when not to (mixed-character passwords or passphrases), plus mentions rate limits and local execution.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, non-destructive, idempotent. Description adds important context: local compilation, no remote $ref fetching, rate limit (60 req/min). No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is fairly concise but slightly verbose; each sentence adds value but could be more tightly written. Front-loads purpose well.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers supported drafts, behavior with remote $ref, rate limits, and output structure (valid flag, errors array with fields). Output schema exists but description adds context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds auto-detection of draft from $schema and notes that instance can be parsed or raw string, going beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it validates a JSON instance against a JSON Schema using Ajv, and distinguishes from data_json_schema_generator which infers schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use this tool ('to check data you already have against a schema you already have') and when to use the sibling tool instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses non-deterministic CSPRNG vs deterministic seeded output with xoshiro128**, and warns against using seeded output for security purposes. Annotations already indicate readOnlyHint=true, and description adds valuable behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that front-load purpose and then cover randomness and guidelines. Brief but effective, though appears truncated at the end ('Re').
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, randomness, security, and output formats. With full schema descriptions and an output schema, the description is complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds context about output formats, seed behavior, and field types beyond what schema provides, justifying a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates custom random fake records with user-defined schema. It lists 22 field types and distinguishes from sibling tools like data_data_faker, data_sample_data_generator, and math_random_number_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool: 'Use this when you control the exact record schema' and provides alternatives for other cases, naming specific sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint true), description adds details: runs locally, non-destructive, rate-limited, non-deterministic by default but supports seed for reproducibility. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single, well-structured paragraph that front-loads purpose and provides necessary details without redundancy. Slightly lengthy but efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all aspects: shapes, count, seed, format, return value, determinism, rate limits, and local execution. Output schema exists; description complements it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%; description adds meaning by explaining shape examples, count range, seed purpose, format types, and return value structure, going beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'generate ready-made demo datasets' for nine fixed shapes, and distinguishes from siblings like data_faker and data_random_data_generator by naming them explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises when to use this tool ('recognisable, opinionated table') and when to use alternatives ('use data_faker...'), providing clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond annotations: stateless, read-only, offline pure-compute, no auth required, default rate limit 60/min, and deterministic behavior. Annotations declare readOnlyHint=true and idempotentHint=true, which the description corroborates. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is slightly verbose but well-structured: it starts with the main purpose, then lists capabilities, then exclusions, then usage guidance, then behavioral traits. Every sentence adds value, but it could be more concise by separating the guidance into bullet points.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (context indicates true), the description covers all necessary aspects: operations, formats, behavioral notes, auth, rate limits, and disambiguation from siblings. No gaps for a table formatting/parsing tool with 6 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the two operations ('render' and 'parse') and noting the purpose of parameters like alignment (per-column) and the distinction between operation requirements. While not fully compensating for missing schema descriptions (none needed), it provides helpful operational context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it formats and parses tabular data, specifies supported formats (Markdown, HTML, CSV, TSV), and explicitly distinguishes from sibling tools like data_sample_data_generator and webdev_csv_to_json. The verb+resource combination is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: 'Use this instead of data_sample_data_generator or data_data_faker (which invent random records), and prefer it over webdev_csv_to_json / webdev_json_to_csv when you need Markdown/HTML output or alignment-aware Markdown rather than JSON.' It also states what the tool does not do ('Does NOT generate random or sample data').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds important behavioral context: runs locally, non-destructive, rate limits (60/min, 500/hour, 2000/day), and the lossy nature of version A decoding. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph but well-structured: starts with core purpose, then details, alternatives, and behavioral traits. Every sentence adds value, though slightly lengthy. Could be split for readability but still concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown but indicated), the description mentions return value: 'transformed text plus an analysis object (lengths, cipher-group count, expansion ratio, security level)'. This, combined with parameter and behavior details, makes the description complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with descriptions, but the description adds significant value: explains the mapping (A/B or 0/1), historical context, difference between versions A and B, and behavior on non-letters. This goes beyond the schema's documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Baconian Cipher (Encode and Decode). Encode or decode text with the Baconian cipher.' It specifies the resource (text) and action (encode/decode), and differentiates from sibling tools by naming alternatives like encoding_decoding_vigenere, caesar, atbash.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit usage guidance: 'use it for classical/CTF puzzles or to hide a binary message inside other text.' It also clarifies when not to use: 'it is not encryption' and suggests alternatives for keyed or shift-based classical ciphers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint), the description adds critical behavioral details: 'runs locally', 'read-only, non-destructive', 'rate-limited (60 requests/minute)', and discloses return values (converted string plus statistics). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sentences, each earning its place. It is slightly verbose (e.g., 'runs locally on the text you provide') but still efficient. Minor redundancy could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters (all documented in schema), full schema coverage, output schema present (though not shown, description mentions statistics), and sibling context, the description is complete. No missing aspects for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds meaning beyond schema by providing examples for text, clarifying operation direction, and detailing base format specifics (RFC 4648 padding, Bitcoin alphabet, Z85 character set). Slightly redundant with schema but still adds value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a Base32/58/85 encoder/decoder, specifies exact encoding standards (RFC 4648, Bitcoin alphabet, Z85), and distinguishes it from sibling tools by naming them explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use and when-not-to-use guidance: 'Pick the format with the base parameter' and mentions alternative tools for Base64, Ascii85, and Base91. It also notes local execution and rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and idempotentHint=true; the description adds details like 'runs locally', 'non-destructive', 'contacts no external service', rate limiting, and that output includes entropy/compression analysis, which goes beyond annotations. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph but logically ordered: purpose, details, alternatives, behavioral notes. Efficient without redundancy, but could use structural elements like bullet points for faster scanning. No wasted sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with enums, an output schema (not shown but exists), and siblings, the description covers operation modes, encoding options, formatting details, output contents, behavioral traits, and rate limits. It is comprehensive and leaves no major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 5 parameters with descriptions. The description adds context by explaining how format and separator interact (e.g., separator only used with custom_separator), and clarifies the overall encoding logic (multi-byte chars become multiple bytes for utf8). However, most parameter details are already in schema, so value is moderate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts text to binary and binary to text, specifying operations like text_to_binary and binary_to_text, and distinguishes from sibling tools by mentioning alternatives for hex (encoding_decoding_hex_ascii), base conversion (conversion_number_base), and numeric binary interpretation (conversion_binary_decimal).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when-to-use guidance by contrasting with related tools, noting that hex, multi-base, and numeric binary conversions are handled elsewhere. Also clarifies it runs locally, is read-only, and has rate limits, helping agents decide appropriateness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. The description adds valuable context: runs locally on provided text, contacts no external service, rate-limited (60 requests/minute), and returns converted string plus metadata on decode. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph but efficiently packs all key info without redundancy. It could be slightly more structured (e.g., bullet points for alternatives), but every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, 2 required, output metadata), the description covers purpose, usage, behavior, parameters, and returns comprehensively. It also references output schema implicitly (decoding returns filename, type, creator, size). Well-contextualized among many siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 5 parameters. The description adds extra meaning: explains default values, truncation rules for filename/type/creator, and that some parameters are ignored on decode. This goes beyond schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool encodes text to BinHex 4.0 or decodes BinHex to text, with specific verb+resource+format. It distinguishes from siblings by listing alternative encodings (uuencode, xxencode, base64, ascii85) and their use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use BinHex (classic Macintosh binary-to-ASCII) and when not to (for Unix/Usenet use uuencode/xxencode, for web/MIME use base64, etc.). It also notes the tool is read-only and non-destructive, providing clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, non-destructive, and idempotent. The description adds that it runs locally on input, contacts no external service, and is rate-limited. It also details encoding behavior (hex escapes for non-printable, trailing spaces). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is comprehensive but slightly verbose. It front-loads the core purpose and usage, but some details (rate limits, output contents) could be more succinct. Still, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description is complete: it mentions return values (converted string, input, operation, size statistics) and error conditions (decode requires valid hex). Context of sibling tools is well-handled with explicit differentiators.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema covers both parameters with descriptions, achieving 100% coverage. The description adds contextual meaning: for encode, input is plain UTF-8 text; for decode, input is Quoted-Printable string. Also notes decode requires valid hex pairs. This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool is a Quoted-Printable encoder/decoder per RFC 2045, specifies the operation (encode/decode), and explicitly distinguishes it from sibling encoding tools like base64, URL encoding, uuencode, and xxencode.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('email bodies and MIME parts that are mostly ASCII') and when to use alternatives ('use encoding_basex base64 for dense binary, encoding_url for percent-encoding URL components, etc.'). Provides clear guidance for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds: runs locally, read-only, non-destructive, no external service, rate-limited (60 req/min). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Long but dense with information. Front-loaded with purpose. Could trim some repetitiveness (e.g., 'Runs locally' appears twice). Still highly informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all aspects: behavior, usage, limitations, sibling differentiation, output format (implied by output schema). No gaps given output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions. Description adds value by explaining rotation behavior (13 vs 47 vs custom) and operation's irrelevance for self-inverse variants.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it applies ROT13/ROT47 ciphers, explains the rotation variants (13, 47, custom), and differentiates from sibling tools like Caesar and Atbash. Verb+resource+scope is specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (puzzles, CTFs, hiding spoilers) and when not (not for secrets). Names alternatives (caesar, atbash). Also notes local execution and rate limiting.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds value beyond annotations by noting rate limiting (30 req/min for anonymous), local execution, and that the result shape depends on operation. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is approximately 100 words, well-structured with key information front-loaded. Every sentence contributes value, though it could be slightly more concise without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, nested objects, 4 operations, output schema), the description is remarkably complete. It covers purpose, behavior, usage guidelines, and limitations, leaving no critical gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaning by explaining how operation determines which fields to use and briefly describing each operation's purpose, enhancing understanding beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the tool's purpose: converting data sizes between SI, IEC, and bit units via four operations (convert, compare, transferTime, storageFit). It distinguishes from sibling conversion_base_converter, avoiding ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (byte-unit math and bandwidth estimates) and when to use an alternative (conversion_base_converter for numeric radix conversion). Also provides context for each operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds valuable context: 'Reads a frozen in-memory table only: read-only, non-destructive, contacts no external service, and is rate-limited (30 requests/minute for anonymous callers).' It also explains error handling ('unknown input returns an empty-result shape'). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured, starting with the core purpose and then providing usage guidance, behavioral details, and alternatives. Each sentence adds value without redundancy. It is slightly long but still concise for the amount of information conveyed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown but true), the description does not need to detail return values. It covers purpose, operations, specific usage guidance, behavioral traits (read-only, rate-limited, no external calls), error handling, and an alternative tool. This is complete and sufficient for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all three parameters. The description adds useful semantics by explaining how parameters relate to operations (e.g., 'lookupByExtension requires extension; lookupByMimeType requires mimeType; listAll takes neither') and clarifies normalization (e.g., extension ignores leading dot and case, mimeType case-insensitive). This exceeds the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: looking up IANA media types from file extensions or reverse-lookup, with three distinct operations. It explicitly distinguishes from the sibling tool 'file_file_type_detector' which uses magic-byte signatures, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance for each operation: 'Use lookupByExtension when you have a filename/extension and need the Content-Type; use lookupByMimeType when you have a media type and need its file extensions; use listAll to fetch the whole 120-plus-entry table.' It also offers an alternative by directing to 'file_file_type_detector' for magic-byte signature identification.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnly, non-destructive), the description adds important behavioral traits: 'runs locally on the text you provide', 'rate-limited (60 requests/minute for anonymous callers)', and details about return values including validity flag and parse error. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two paragraphs: first is a concise summary, second adds detail. Every sentence adds value. Could be slightly shorter but well-organized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with enums and an existing output schema, the description fully covers what the tool does, including return fields (output string, validity, error, analysis, statistics). No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining edge cases (e.g., blank input returns isValid false) and parameter interactions (e.g., indent ignored for non-format operations). However, the schema already provides strong descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it works with JSON documents for formatting, minifying, validating, and analyzing. It distinguishes itself from sibling tools like format_json_visualizer (interactive tree), webdev_code_formatter (HTML/CSS/JS), and webdev_json_to_csv (conversion).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear guidance: use this tool for 'plain text-in/text-out cleanup and syntax checking', and specifies alternatives when other operations are needed, such as browsing as a tree or converting to CSV.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds valuable behavior: runs locally, no external service, rate-limited (60/min for anonymous), and behavior on invalid JSON (returns isValid:false with error message).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is informative but somewhat lengthy. It is well-structured with clear sections: purpose, details, usage alternatives, local execution, and error handling. Could be slightly more concise but efficient overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all necessary aspects: what the tool does, its limitations, error behavior, rate limits, and differentiation from related tools. With an output schema present, the description is complete for this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with descriptions. The description adds edge-case behavior: 'Blank input returns isValid:false with empty statistics; malformed input returns isValid:false with the parser error. The alias "input" is also accepted.' This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: parse JSON, validate, and provide structural summary (node counts, depth, type stats). It explicitly distinguishes from siblings like format_json, data_json_path_evaluator, etc., by specifying when to use this tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: 'use this tool when you only need to inspect shape, depth and node/type counts' and lists alternatives for other tasks. It also clarifies that it runs locally and is read-only.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations state readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description reinforces: 'it never executes, saves, or runs anything' and 'Runs locally: read-only, non-destructive.' It adds context that the tool only returns script text, exceeding annotation requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense paragraph but well-structured and front-loaded with the main purpose. Every sentence adds value, though a bit lengthy. It could be slightly more concise but remains highly informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (8 parameters, 2 enums, output schema exists), the description is complete. It covers purpose, behavior, parameter overview (shebang, strict mode, args, blocks, customBody, operation with presets), and sibling differentiation. No gaps are evident.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the description adds meaningful context beyond the schema: it explains that args become 'a getopts-style case parser' and blocks are 'emitted in a fixed safe order regardless of array order.' This adds value beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Bash Shell Script Generator' and that it 'ASSEMBLES and returns script TEXT, it never executes, saves, or runs anything.' It also explicitly distinguishes from sibling tools like linux_systemd_unit_generator, linux_cron, and linux_ssh_config_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use and when-not-to-use: 'Use linux_systemd_unit_generator for service/timer unit files, linux_cron for crontab schedule lines, and linux_ssh_config_generator for ssh client config - this tool emits the executable script itself.' It also lists the operation presets which are ready-made templates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds full behavioral detail: local, read-only, non-destructive, idempotent, offline, rate limits. Annotations already cover readOnly, destructive, idempotent; description enriches and does not contradict.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Thorough but not overly long; front-loaded with purpose and output. Each sentence is informative. Minor redundancy with annotations but acceptable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete given 7 params and output schema. Covers purpose, usage, behavior, parameter details, and clarifies placeholder nextRuns. No gaps for a generation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage 100% so baseline 3. Description adds context about generateExamples and notes that nextRuns is placeholder, plus that command is not validated. Adds some value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it's a schedule generator, builds crontab line, distinguishes from time_cron_parser. Specific verb 'build' and resource 'schedule' + 'line'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit when-to-use (compose/teach) and when-not (use time_cron_parser for decoding). States it never installs or edits crontab.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. The description adds 'offline' and 'rate-limited (30 requests/minute for anonymous callers)', plus 'Operates only on the numbers and text you supply', which provides additional behavioral context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively long but well-organized: starts with overall purpose, lists operations, then constraints and alternatives. It could be slightly more concise, but every sentence adds value and the structure is logical.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of six operations with nested parameters and an existing output schema, the description covers all necessary context: what each operation does, parameter requirements, constraints, and integration with other tools. It feels complete for an AI agent's needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds context like 'Auto-detects human (du -h) vs raw-byte columns' for the 'text' parameter and 'May be supplied as this nested object or as top-level fields alongside operation' for 'input', which adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it's a 'Linux Disk Usage And RAID Calculator' and enumerates six specific operations with brief explanations. It distinguishes from sibling tools like 'file_file_size_calculator' and 'math_unit_converter' by naming them explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear when-to-use guidance for each operation and includes an explicit alternative: 'use file_file_size_calculator for byte-unit conversion plus transfer-time estimates, or math_unit_converter for general unit conversion'. It also clarifies constraints like 'never reading a real filesystem'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds value beyond annotations: explains it is read-only, non-destructive, rate-limited, validates IPs/ports, emits lockout warnings. Annotations already indicate readOnlyHint true and destructiveHint false, but description enriches with specific details about rate limiting and validation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is thorough but somewhat dense. It front-loads the purpose and key characteristics, then covers usage, limitations, and return values. Could be slightly more concise, but no redundant sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (6 parameters, nested objects, output schema), the description is complete. It covers return format (scripts plus explanations, warnings, file paths), validation, lockout warnings, and presets. Output schema exists but description supplements it well.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear property descriptions. The description adds context like silent skip of invalid rows, presets operation behavior, and lockout warnings, which enhance understanding beyond the schema. Baseline 3 due to high coverage, plus extra context justifies 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool generates iptables-restore and nftables firewall scripts from a structured description, with specific verb 'Generate' and resource 'firewall scripts'. Distinguishes from sibling linux_ssh_config_generator by explicitly mentioning what it does not do.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('author Linux netfilter rulesets') and when not ('use linux_ssh_config_generator instead for ssh_config and sshd_config'). Provides context that it only emits text and never runs iptables, with rate limits and validation behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond annotations, including rate limits (30 req/min), input size cap (5 MB), local execution, and that format auto-detection is used. It confirms read-only and non-destructive nature, aligning with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections, but is somewhat lengthy. It could be slightly more concise without losing essential information. However, every sentence contributes to understanding, and key points are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, multiple operations, output schema exists), the description covers purpose, usage, alternatives, operations, safety, and limitations. It is complete enough for an agent to correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description adds moderate value by explaining operation stages contextually and detailing parameter usage such as the filter mini-language and aggregate settings. It clarifies required parameters for different operations, enhancing understanding beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: parsing various log formats (Apache, nginx, syslog, JSON Lines, systemd journal) into structured rows, then filtering, aggregating, or converting them. It explicitly distinguishes itself from sibling tools linux_disk_usage_calculator and json_path_evaluator by specifying alternative use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool (for log parsing and analysis) and when not to (for du/df output or single JSON documents, directing to alternatives). It also clarifies that it runs locally on provided text and is safe (read-only, non-destructive).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds valuable behavioral context: pure local computation, deterministic, no external service contact, and rate limiting. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is thorough and well-structured, front-loading the core purpose and operation details. Every sentence earns its place, though it is somewhat lengthy. A slight reduction could improve conciseness without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description does not need to explain return values. It covers purpose, usage guidelines, behavioral transparency, and parameter semantics comprehensively. It also mentions the return format (decimal string, digit count, leading digits) for very large outputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all parameters. The description adds meaning by explaining operation selection, which parameters are required for each operation, that r must be at most n, and that inputs accept numbers or strings in the range 0-10000. This goes beyond the schema but is not vastly richer.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes factorials, double factorials, permutations, and combinations with arbitrary-precision BigInt. It distinguishes itself from sibling tools like math_scientific_calculator and math_gcd_lcm_calculator by specifying its exact combinatorial use case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (exact counting and probability math where doubles lose precision) and when not to (use math_scientific_calculator for general expression evaluation, math_gcd_lcm_calculator for GCD/LCM). It also mentions rate limits (60 requests/minute for anonymous callers) and that it is read-only and deterministic.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses behavioral traits beyond annotations: 'Runs locally on the numbers you provide: read-only, non-destructive, contacts no external service, and is rate-limited (60 requests/minute for anonymous callers).' This adds context about local execution and rate limits, which are not covered by the readOnlyHint and idempotentHint annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph, but each sentence serves a purpose: defining scope, listing modes, usage guidance, and behavioral notes. It front-loads the tool's purpose and operation list. While slightly verbose (e.g., detailed operation descriptions could be shortened), it remains clear and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 operations, 8 parameters, nested objects, output schema), the description covers all necessary aspects: operation modes, parameter requirements, constraints (e.g., 'simplify requires positive integers'), usage guidance, and behavioral safety. The presence of an output schema means return values need not be described. Complete for agent selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the operation modes in a narrative way (e.g., 'simplify reduces an integer ratio by its GCD; solveProportion solves a is to b as c is to d'), and clarifies conditional usage of parameters like anchor and total. This enhances understanding beyond the schema's property descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a ratio calculator with five specific operations (simplify, solveProportion, scale, split, percentage), and distinguishes it from sibling tools math_percentage_calculator and math_statistics_calculator. The verb 'run' and resource 'ratio operations' provide a specific, actionable purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit usage guidance is provided: 'Use this for proportions, scaling, and part-whole splits; use math_percentage_calculator for percent-of and percent-change math, or math_statistics_calculator for descriptive statistics on a dataset.' This clearly states when to use this tool and when to choose alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds value beyond annotations by detailing that it is pure offline math, contacts no host, and has a rate limit of 60 requests/minute. No contradiction with readOnlyHint and destructiveHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single paragraph of about 6 sentences, front-loaded with purpose. Every sentence adds value, though slightly denser than necessary; could be broken into bullet points for readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given rich schema with enums, full parameter descriptions, output schema present, and annotations, the description still adds critical context (rate limits, alternative tool, return fields) and is sufficient for an agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage, but the description adds useful context such as listing RFC byte sizes for encapsulations and stating that unknown encapsulation IDs are rejected. It explains the effect of each operation mode beyond schema enums.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes inner MTU, TCP MSS, usable payload, and overhead for encapsulations. It distinguishes three operations (compute, presets, pathMtuDiscovery) and explicitly contrasts with sibling tool networking_network_latency_calculator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use each operation and when to use an alternative tool ('use networking_network_latency_calculator to interpret ping or speedtest samples instead'). Also mentions read-only, non-destructive, and rate-limited behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description details dual behavior (prefers ICMP via remote worker, falls back to HTTP probe), SSRF guard rejecting private addresses, and non-idempotent nature. Annotations (readOnlyHint=false, idempotentHint=false) align and don't contradict.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is front-loaded with purpose and compressed but includes necessary details. Slightly verbose due to behavioral and security explanations, but each sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (dual mode, SSRF guard, variability) and presence of output schema, description covers reachability, latency, fallback, SSRF rules, and non-idempotency. Complete for agent selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all three parameters (target, packet, worker_id) with descriptions. Description adds context on target format, packet's role only in ICMP path and ignored by HTTP fallback, and worker_id as optional.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Title and description clearly state 'Ping Host (ICMP/HTTP Reachability)' with verb 'ping' and resource 'host'. Description explicitly distinguishes from sibling tools (network_traceroute, network_website_status_checker, etc.) by stating when to use each alternative.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explicitly states 'Use this to confirm a host is up and gauge latency to ONE target' and provides clear alternatives for different needs (traceroute, DNS, HTTP validation).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes well beyond annotations by detailing that it makes a real network connection, is CAPTCHA-gated and rate-limited, pins hostnames to public IPs for SSRF safety, rejects private addresses, and always sets tls_verified to false. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: starts with the main action, then caveats, usage guidance, and security/rate-limit info. Every sentence is valuable, though slightly verbose in listing all output fields. Still, it remains readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (3 params, full schema, output schema present), the description is very complete: explains behavior, security, rate limits, sibling differentiation, and key output fields like days_until_expiry and expiry_status. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, giving a baseline of 3. The description adds meaning by explaining that hostname must resolve to a public IP, port defaults to 443, and worker_id is optional for custom behavior. It also ties parameter use to the tool's security model.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly names the tool as an SSL/TLS Certificate Checker, specifies the action (fetches and parses live TLS certificate chain), and distinguishes it from siblings like network_website_status_checker, network_dns_lookup, and network_whois.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use (inspect a server's actual served certificate) and when-not-to-use (not for HTTP status, DNS, or whois) with specific sibling names. Also warns that peer verification is disabled, so it's not for trust decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses outbound network access, CAPTCHA gating, rate limits, and non-idempotency. Adds context beyond annotations (e.g., live registry state, returned fields). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is comprehensive but slightly verbose. However, all information is necessary and front-loaded with purpose, making it well-structured for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity, the description covers purpose, behavior, params, output (parsed fields, analysis, raw text), and limitations. Output schema exists but description still adds value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for one parameter. Description adds value by explaining stripping of schemes/paths and requirement for valid dotted domain, beyond the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the verb 'check' and resource 'domain's age and registration lifecycle' with specific data points. It differentiates from siblings by naming alternative tools (network_whois, network_dns) and their uses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool vs alternatives, provides prerequisites (domain without path), and details behavior like live WHOIS lookup, rate limits, and non-idempotency.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark it as read-only and idempotent. The description adds transparency by detailing the local arithmetic nature, no network calls, offline capability, and what the tool returns (validity, type, check digits). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately concise, front-loading the purpose and then providing necessary details. Each sentence serves a purpose, though it could be slightly trimmed without losing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, clear output schema), the description covers all necessary aspects: purpose, input requirements, mode behavior, return values, offline capability, and sibling differentiation. Fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for 'code' and 'mode'. The description adds context such as auto-detection of format from length, and explains behavior per mode, which complements the schema. Slightly redundant with schema but still valuable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: validating EAN/UPC barcodes by recomputing check digits or generating missing check digits. It specifies supported formats (EAN-13, EAN-8, UPC-A, UPC-E) and distinguishes from related siblings like osint_barcode_scanner and osint_isbn_validator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (for bare numeric strings vs image decoding, rendering, or ISBN validation). Also notes it's read-only, offline-capable, and rate-limited, providing clear context for usage decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds that it runs locally, makes no outbound requests, is deterministic, works offline, and is rate-limited. This provides complete behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is moderately long but well-organized. Core purpose is front-loaded, and every sentence adds value. Could be slightly more concise, but still effective. Score 4.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has output schema (not shown but noted) and description explains return fields (normalized address, OUI, vendor, details, structural analysis). Input is simple. Description is complete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already has 100% coverage with detailed description for mac_address. The description adds context about OUI prefix matching and the built-in table, but the schema covers input format well. Slight added value justifies a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'MAC Address Vendor Lookup' and explains it identifies the hardware manufacturer from a MAC address using a built-in OUI table. It distinguishes itself from sibling tools like networking_mac_address_generator and osint_vin_decoder.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('attribute an existing MAC to a vendor') and when not to use (alternatives for creating MACs or decoding VINs). Also mentions rate limiting (60 req/min) for proper usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that generation only assembles and validates strings, does not fetch/test/deploy, and that crawler compliance is voluntary. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with a clear summary and uses bullet-like structure for modes. Slightly lengthy but every sentence is useful. Minor truncation ('non-de') but does not detract.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (multiple modes, nested input, output schema), the description covers operation modes, input requirements, limitations, and alternative tools. Adequate for an agent to select and invole the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good descriptions. The tool description adds context beyond the schema, such as explaining each operation mode in detail and listing the preset names. This adds value, earning above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The title and description clearly state the tool builds, parses, and presets robots.txt files per RFC 9309. It distinguishes from sibling tools by mentioning security_htaccess_generator and seo_sitemap_generator as alternatives for different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance on when to use each operation mode, and exclusions: use seo_sitemap_generator for sitemaps, security_htaccess_generator for Apache directives. Also states limitations: does not fetch, test, or deploy the file.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description explicitly states 'Read-only, non-destructive' and clarifies that the server only produces the URI string without external service contact, aligning with and adding context to the annotations (readOnlyHint: true, destructiveHint: false).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with front-loaded purpose and clear separation of actions. While slightly verbose, every sentence adds necessary detail and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (three operations, 11 parameters), the description thoroughly covers each operation's behavior, return values (app-compatibility warnings), and boundaries. The existence of an output schema further reduces need for return value explanation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining operational nuances (e.g., buildUri does not invent a secret, generateSecret uses CSPRNG, parseUri decodes) and flags compatibility warnings. These details enhance understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states '2FA TOTP/HOTP otpauth URI Builder and Parser' and distinguishes from the sibling 'osint_qr_code_generator' by specifying this tool is only for authenticator-app 2FA enrolment URIs. It covers three distinct operations with specific verbs and resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool vs. the alternative: 'Use osint_qr_code_generator for general-purpose QR codes... use this tool only for authenticator-app 2FA enrolment URIs.' Also details the three sub-actions and their respective contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds key behavioral context: runs locally, read-only, non-destructive, contacts no external service, rate-limited (60 req/min). This goes beyond annotations, giving agents clear safety and performance expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is relatively long but front-loaded with main purpose and key differentiator. Structured with clear sections (main use, alternative, operation modes, behavioral notes). Every sentence adds value. Could trim some redundancy but still effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (13 parameters, nested objects, enum types), the description covers all necessary aspects: what it does, when to use, behavioral traits, parameter constraints, and return summary. Output schema exists so return explanation not needed. Complete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline 3. Description adds value by noting warnings for length truncation, relative URLs, unknown og type, bad locale. Provides context like 'Required for generate' for title/description. Doesn't just repeat schema, adds practical usage details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool generates Open Graph Protocol meta tags. Explicitly distinguishes from sibling seo_meta_tag_generator by specifying use case: 'use this tool when you need only the og tags with vertical sub-properties' versus a full head block. Verb+resource is specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use vs alternatives: mentions seo_meta_tag_generator for full head block. Also describes operation=presets for fetching example payloads. Covers both main use and auxiliary feature.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations by stating the tool is read-only, non-destructive, local, and rate-limited. This adds critical behavioral context not captured in annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently structured with front-loaded purpose. Each sentence contributes meaning. Slightly longer than minimal but appropriate for the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (17 types, two operations, output schema), the description covers all necessary aspects: purpose, usage, behavioral traits, output details, and sibling references. No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the baseline is 3. The description adds value by explaining how to use the 'fields' parameter and referencing operation schemas for field details, slightly exceeding the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates schema.org JSON-LD structured data for 17 types. It distinguishes from siblings like seo_meta_tag_generator and seo_open_graph_generator, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool vs alternatives (e.g., 'Use seo_meta_tag_generator for the broader head meta block') and advises to run the 'schemas' operation first. This provides clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, destructiveHint, idempotentHint. Description adds that it runs locally, is non-destructive, contacts no external service, and has rate limits, providing valuable context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is slightly verbose but well-structured with a clear purpose, usage, and behavioral notes. Every sentence adds value, though some phrases could be trimmed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters, full schema coverage, and presence of output schema, the description is comprehensive. It covers all modes, options, constraints, and behavioral traits.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-documented. Description adds additional context (e.g., 'regex strictness' for extractionMode) but the schema already covers details. Good but not exceptional.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it extracts email addresses from text using a regex scanner. Distinguishes itself from the sibling tool text_extract_urls, indicating when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says use this for harvesting addresses from logs/documents, and use text_extract_urls for links. Notes that matching is pattern-based only and does not verify deliverability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive. Description additionally states it runs locally, contacts no external service, and is rate-limited. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph that front-loads main purpose and lists statistics clearly. Slightly long but every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all essential aspects: input constraints, options, output as nested statistics object plus options. Given complexity, complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so description adds value by specifying text non-empty requirement, defaults for includeReadability, and the echoed behavior of includeSentiment.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes comprehensive text statistics (character, word, sentence counts, readability, etc.) and distinguishes it from siblings text_word_frequency and text_text_counter with specific use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool ('full linguistic profile in one call') and when not to (use text_word_frequency or text_text_counter for narrower needs). Also notes it's read-only and local.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), description adds: runs locally, contacts no external service, rate-limited (60/min), error behavior (HTTP 400 with details), and that @reboot is rejected. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with title, operations, usage guidance, and behavioral details front-loaded. Sentences are informative but some redundancy (e.g., 'read-only, non-destructive' and 'Runs locally' could be merged). Slightly long but effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (4 params, 2 operations, output schema exists), description covers purpose, usage, behavior, parameter semantics, error handling, and rate limits. Output schema is present, so return value explanation is unnecessary. No significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds context: operation describe vs nextRuns, and that fromIso and count are only for nextRuns. Extra detail on each operation's output (English summary vs timestamps) provides value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb+resource: 'Cron Expression Parser and Next-Run Preview' with specific operations (describe, nextRuns). Differentiates from sibling 'linux_cron_job' by stating its use case (read/validate existing vs build new schedule).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'Use this to read or validate an existing cron string; use linux_cron_job instead to build a new schedule from a visual form.' Also notes it is read-only and non-destructive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits: it's a pure read-only computation with no network/storage (only 'now' reads wall clock), uses a strict hand-rolled parser, and aligns with annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is comprehensive but slightly long; however, every sentence is informative. It front-loads the core purpose and then details operations. It could be more concise, but the structure is logical and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (5 parameters, multiple operations, sibling tools), the description is thorough. It covers all operations, input/output behaviors (with output schema existing), and provides sufficient context for an agent to use it correctly. No major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
While schema coverage is 100% and the input schema already describes parameters, the description adds value by explaining operation-specific input expectations (e.g., 'for parse: an ISO 8601 string...'). This contextualizes the parameters beyond basic type/description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as an ISO 8601 / RFC 3339 date formatter, listing five specific operations (parse, format, duration, add, now). It also explicitly distinguishes this tool from siblings like time_timezone_converter, time_world_clock, and convert_timestamp, providing clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives, stating 'Use this for ISO/RFC string parsing and rendering, not...' and names three sibling tools with their purposes. It also mentions the rate limit of 60 requests/minute, helping agents choose appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, idempotentHint), description adds DST awareness, mode behavior, that listSupportedTimezones ignores other fields, and that each rendered zone reports UTC offset, abbreviation, and DST flag. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph, front-loaded with purpose, then mode details, then sibling comparisons, then behavioral notes. Slightly dense but efficient; every sentence adds value. Could be slightly more structured with line breaks.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (3 modes, many parameters, output schema present), the description covers all necessary context: operation selection, parameter requirements per mode, return value semantics (UTC offset, abbreviation, DST), and performance characteristics (local, rate-limited).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are already well described. The description adds value by grouping parameters per mode and clarifying which are required for each operation, reinforcing the schema without redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it's a wall-clock time zone converter with three named modes (convert, compare, listSupportedTimezones). It distinguishes from sibling tools (time_world_clock, time_iso_8601_formatter, convert_timestamp) by specifying their different use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('zone-to-zone wall-clock math') and lists three sibling tools for other time-related tasks. Also mentions local computation, no network, and rate limits, setting clear expectations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, the description adds that it's pure deterministic proleptic-Gregorian over UTC, no clock dependency, rate-limited (60 req/min anonymous), and requires no auth. It also describes the wrapped output. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections for each operation and usage guidance. It front-loads the purpose. While slightly lengthy, every sentence adds value, and the structure aids readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (two operations, many parameters) and the presence of an output schema and annotations, the description covers purpose, operations, parameter semantics, usage guidelines, behavioral traits, rate limits, and alternatives. It is fully adequate for correct agent invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaning by explaining the two operations, their parameter groups, and the return values (breakdown for countBetween, resulting date and counts for addWorkingDays). It also clarifies holiday behavior (dedup, real dates). This provides value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes working days with two operations (countBetween and addWorkingDays). It explicitly distinguishes itself from sibling tools like time_date_difference and time_date_calculator by specifying appropriate use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives: use this for business-day counts with holiday exclusion, use time_date_difference for plain calendar diffs, and time_date_calculator for weekend-skipping arithmetic. It also notes read-only, idempotent, and offline-capable properties.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond annotations, detailing local execution, no external service contact, rate limits, and the return value structure. Annotations already mark readOnlyHint and destructiveHint, but the description enriches understanding with concrete constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with purpose first, followed by details and sibling references. It is slightly verbose but every sentence adds value. Could be slightly tighter without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (nested parameters, output schema, multiple filter types), the description covers all essential aspects: behavior, usage, outputs, and distinctions. It enables an AI agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptive property definitions. The description adds value by explaining the purpose of filter functions, units, and drop-shadow parameter grouping, complementing the schema. A minor lack of deeper nuance prevents a 5.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a CSS filter generator that composes filter declarations and returns code and preview. It lists supported filter functions and explicitly distinguishes from sibling tools like webdev_css_gradient_generator and webdev_box_shadow_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives, naming siblings for gradients, box-shadow, and color picking. It also states the read-only, non-destructive, local execution and rate limits, giving clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. Description adds rich behavioral context: runs server-side, read-only, non-destructive, contacts no external service, upload cap 4 MB, rate-limited (30 req/min for anonymous). Also details internal behavior like truncation, font scaling, fallbacks. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph of about 5 sentences. Front-loaded with main purpose and outputs. Dense but clear; could benefit from slight structural separation (e.g., bullet points), but remains concise and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 15 parameters, 0 required, and presence of output schema, description covers all necessary aspects: input types, output format (base64-encoded files + metadata), constraints (size, rate limits), and fallback behaviors. No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with full parameter descriptions. Description adds extra context: e.g., initials force upper-case, font shrinks as length grows, defaults for various fields, relationships like sizes roles in .ico/apple-touch-icon/manifest. This goes beyond schema, justifying above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it generates a favicon bundle from text, emoji, initials, or upload. Lists specific outputs: multi-size PNG set, favicon.ico, apple-touch-icon, site.webmanifest, HTML tags, and downloadable ZIP. Explicitly distinguishes from sibling tools webdev_base64_image_encoder and webdev_svg_optimizer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'Use this to produce browser tab and home-screen icons'. Also provides clear alternatives: 'for embedding a single image as a data URI use webdev_base64_image_encoder, and to shrink SVG artwork first use webdev_svg_optimizer'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds that it runs locally, contacts no external service, and is rate-limited (60 requests/minute). It also explains that it returns validation (isValid flag, errors, warnings) and statistics, providing comprehensive behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, front-loading purpose and usage, then behavior and return value. It is slightly verbose but every sentence adds value. Minor redundancy (e.g., 'read-only, non-destructive' partially repeats annotations) but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having a rich input schema and output schema, the description covers all necessary aspects: purpose, when to use, behavioral constraints, parameter options, and return value summary. It leaves no critical gaps for an agent to misuse the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with detailed descriptions. The tool description adds value by summarizing the main parameters (indentation, compact mode, remove comments) and clarifying that sortArguments is forward-compatibility only 'accepted for forward compatibility; field arguments are not reordered'. This extra context justifies a score above baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'GraphQL Formatter and Minifier' and specifies it can pretty-print or minify GraphQL documents (queries, mutations, subscriptions, fragments, or SDL schemas). It distinguishes itself from sibling tools by name-dropping webdev_sql_formatter and webdev_json_formatter, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use alternatives: 'Use webdev_sql_formatter for SQL and webdev_json_formatter for JSON.' It also clarifies that the tool is syntactic only and never sends documents to a server, so the agent knows not to use it for execution or server interaction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses safety guarantees (no arbitrary code, no network/database/filesystem), rate limits, and that invalid patterns return error field. Annotations already indicate read-only, idempotent, non-destructive; description adds context beyond annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Slightly verbose but front-loaded with main purpose. Each sentence adds value. Could be more concise but well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists (not shown but implied). Description covers return fields and error handling. With high schema coverage and annotations, the description is fully adequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions. Description adds value by noting legacy keys (text, replacePattern), explaining replacement supports dollar-1 and named backreferences, and clarifying replaceResult behavior. Baseline 3 plus extra context warrants 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Describes a regex tester for match/replace with specific verb 'test' and resource 'regular expression against sample text'. Distinguishes from sibling text_find_replace by highlighting regex internals vs plain text substitution.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'Use this to debug or validate a pattern and inspect groups' and when not: 'use text_find_replace for plain text substitution without regex internals'. Also mentions safety and rate limiting.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true. The description goes far beyond: states each call hits the target and may mutate remote state, lists blocked targets (private, localhost, .local, reserved-IP), no redirects, body limit 128 KiB, max 32 headers, timeout 15s, and detailed rate limits with CAPTCHA condition. Provides comprehensive behavioral constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is fairly long but well-structured: starts with purpose, then details on methods/headers/body, use cases, constraints, and limitations. Every sentence adds value, but some minor redundancy could be trimmed. Still, it maintains good readability and front-loads key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters (1 required, enum, nested object) and an output schema, the description covers all critical aspects: behavior, allowed inputs, restrictions, rate limits, and alternatives. The output schema exists so return values are not needed in description. It is complete enough for an agent to correctly select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema coverage is 100%, but the description adds meaningful context: method defaults to POST, body is only sent with POST/PUT/PATCH, headers description blocks specific headers and strips CR/LF, and the url description mentions rejection of private/localhost targets. While the schema already details parameter constraints, the description reinforces and adds nuance, so score 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a webhook tester that sends outbound HTTP requests and returns live responses. It lists supported methods, custom headers, and body usage. It distinguishes itself from sibling tools like network_request_headers, network_website_status_checker, and webdev_user_agent by specifying their different use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'Use this to verify a webhook receiver or HTTP endpoint end-to-end'. Provides clear alternatives: 'use network_request_headers to only view request headers, network_website_status_checker for a plain status/uptime probe, or webdev_user_agent to parse a UA string'. Also notes that it is not idempotent and may mutate remote state, guiding appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds concrete behavioral details: runs locally, no external service, rate-limited (60 req/min for anonymous). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences packed with essential information, no fluff. Front-loaded with core functionality, then usage distinction, then constraints and return details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description summarizes return values appropriately (converted output, decimal, steps, metadata, common bases). Covers all necessary aspects for a 3-param tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good parameter descriptions. Description adds extra context about case-insensitivity and digit validity (e.g., base 2 allows only 0-1), surpassing the schema's baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it converts numbers between bases 2-36 with step-by-step working, and explicitly distinguishes itself from the sibling tool conversion_number_base for character-string encodings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool vs conversion_number_base: for numeric base math on a single number token, not for character-string encoding conversions. Provides clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds key behavioral traits: runs locally, is offline, rate-limited (60 req/min anonymous), and returns detailed output including step-by-step XOR working. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured and front-loaded: first sentence states core purpose, then use cases, then sibling differentiation, then behavioral details. Every sentence adds value; no wasted words despite medium length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Completely covers the tool's purpose, usage guidelines, parameter meaning, behavioral traits, and output details (converted string, decimal values, explanation, XOR steps, bit properties). No gaps given the complexity and presence of output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for each parameter. The description goes beyond by explaining the XOR algorithm, fixed-width padding with bitWidth, and providing example input. Adds significant meaning without redundancy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool converts between binary and Gray code, with clear verb ('convert') and resource ('binary number to Gray code or Gray code back to plain binary'). It distinguishes from siblings by naming conversion_binary_decimal and conversion_bcd for other conversions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use (Gray code conversion) and when-not-to-use ('Use conversion_binary_decimal for plain base-2/decimal conversion or conversion_bcd for binary-coded decimal'). Also notes read-only, non-destructive, offline, and rate-limited nature, guiding appropriate invocations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes the encoding/decoding process (inserts parity bits, computes syndrome, flips bit) and return values (codeword, syndrome, error position, etc.). Aligns with annotations (readOnlyHint=true, destructiveHint=false) and adds rate limit info. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is informative but slightly verbose; could be tightened. However, it is well-structured with purpose, mechanism, and usage notes in a logical order.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all essential aspects: purpose, parameters, behavior, return values (output schema exists), constraints, and sibling differentiation. No gaps for a tool of moderate complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds meaningful context: explains mode options, input length constraints per mode and hammingType, and examples of valid inputs. This goes beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it encodes binary data into Hamming codewords and decodes codewords to detect/correct errors. It distinguishes from sibling tools like conversion_parity_bit and conversion_gray_code by specifying alternative uses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use this tool ('for error-correction coding demos and parity analysis') and when to use alternatives ('use conversion_parity_bit for a single parity bit, or conversion_gray_code for reflected-binary encoding'). Also notes local, read-only, offline, and rate-limited constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint), the description adds detailed behavioral traits: encoding upper-cases input, mapping to dot/dash patterns, joining with spaces and slashes, handling unsupported characters, decoding splits on slashes and spaces, and emitting question marks for unrecognized symbols. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, front-loading the purpose, then behavioral details, usage guidance, safety notes, and return value format. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description still explains the return format ('converted string plus an analysis block and reference morse_info'). Covers encoding and decoding behaviors, constraints, and alternatives comprehensively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by specifying that text must be non-empty and trimmed, and explains behavior for unsupported characters during encoding and decoding, which is not fully covered in the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a Morse Code Encoder and Decoder, with specific verb+resource. It distinguishes itself from sibling tools like conversion_braille and encoding_decoding_baconian by mentioning their use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is given: 'Use this for dot-dash signalling; use conversion_braille for tactile braille cells and encoding_decoding_baconian for the A/B Baconian cipher.' It also states that it runs locally and is non-destructive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent. The description adds valuable context: runs locally, offline, rate-limited, validates subtractive notation, rejects out-of-range/malformed input. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear leading sentence and subsequent details. It is slightly lengthy but every sentence adds value, with no redundancy. Could be trimmed slightly for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (2 params, output schema exists), the description covers all key aspects: range, validation, direction, return details (steps, breakdown, facts, alt representations). It is fully complete for accurate use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and parameter descriptions are clear. The description enriches them by explaining direction auto-detection, case-insensitive Roman input, trimming, and examples, adding meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts integers to Roman numerals and vice versa within 1-3999. It specifies the exact verb 'Convert' and resource 'Roman numeral', and distinguishes from siblings by referencing conversion_number_base/conversion_base_converter for other radixes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use (standard Roman conversion) and when not (binary/octal/hex, point to alternative tools). Also explains auto-detection behavior, providing clear context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, the description specifies local execution, read-only and non-destructive nature, no external service contact, rate limiting, and non-idempotent behavior due to fresh salt per call. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence provides distinct value: purpose, usage, behavior, return details. Front-loaded and no redundant or vague phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all necessary aspects: purpose, when to use, behavior, parameters with recommendations, and output summary (hash string, cost, salt, etc.). With output schema present, return values are adequately described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with descriptions and examples, but the description adds context like recommended cost (12), valid range, and the effect of salt. This adds marginal value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool hashes a plaintext password with bcrypt for creating new stored password hashes, and differentiates it from sibling tools like crypto_bcrypt_verify and other KDFs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when to use (create new hash) and when to use alternatives (crypto_bcrypt_verify for verification, other KDFs for different algorithms). Also mentions rate limiting for anonymous callers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes beyond annotations by specifying that it runs locally with PHP password_verify, is read-only, non-destructive, contacts no external service, and has rate limits. This aligns with annotations (readOnlyHint, destructiveHint, idempotentHint) and adds valuable behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two main parts: upfront purpose and usage guidance, then behavioral details. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter tool with output schema, the description covers purpose, usage, behavior, parameter semantics, and return details (matching, parsed fields, strength analysis). It is fully adequate for the agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions and examples for both parameters. The description adds useful context that the cost and salt are read from the hash string, eliminating the need for separate parameters, which enhances understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Bcrypt Password Verifier' and explains that it checks whether a plaintext password matches an existing bcrypt hash. It distinguishes itself from sibling tool crypto_bcrypt by noting that the sibling should be used for generating new hashes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('verify a candidate password against a stored hash') and provides an alternative ('use crypto_bcrypt instead to generate a new hash'). Also mentions rate limits and local execution for context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, etc.), the description adds key behaviors: 'Runs locally on the input you provide: read-only, non-destructive, deterministic (no random salt), contacts no external service, and is rate-limited (5 requests/min anonymous).'
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and efficiently conveys purpose, usage guidelines, behavioral traits, and output format without redundancy. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, 3 modes), the description covers purpose, usage, behavior, parameters, and output format. Return values are explicitly described as 'digest as lowercase hex, uppercase hex, and base64, plus resolved mode, encoding, length, and bit count.'
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds value with context like 'The empty string is valid' and 'BLAKE3 is an XOF' for the length parameter, but most parameter details are already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'BLAKE3 Hash Generator' and explains it computes a hash with configurable modes. It explicitly distinguishes from sibling tools like crypto_hash, crypto_sha3, and crypto_keccak, specifying when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit alternatives: 'Use crypto_hash for MD5/SHA-1/SHA-256/SHA-512, crypto_sha3 for SHA-3, or crypto_keccak for pre-standard Keccak' and states when to reach for BLAKE3 (fastest modern hash, XOF, keyed MAC, KDF).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnly, destructive, idempotent), description adds specific behavioral details: runs locally, no external service, rate-limited, and potential failure for LM hash.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is thorough and well-structured, but somewhat lengthy. All sentences add value, but could be slightly more terse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple hash types, algorithms, output fields), the description covers purpose, usage, behavior, parameters, and return values comprehensively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Description adds deep meaning beyond schema: explains hashing algorithms (MD4, DES), default behavior, and output fields (length, complexity, warnings), complementing the 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates NTLM and LM hashes for Windows security testing, and explicitly distinguishes from siblings like crypto_hash_id and crypto_hash_cracker.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides explicit guidance on when to use this tool vs. alternatives, including when not to use it (for hash type identification or password recovery).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and destructiveHint=false. The description adds valuable context: uses crypto.getRandomValues, runs locally (read-only, non-destructive), contacts no external service, is rate-limited (30/min, 200/hr, 1000/day), and returns each password with length and estimated entropy. This fully informs behavior beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with a clear structure: purpose, features, usage guidelines, safety, return info. Every sentence provides value; no fluff. It front-loads the core purpose and guides agent decision-making efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (11 parameters, many interdependent options) and the existence of an output schema, the description is comprehensive. It covers all essential aspects: what the tool does, when to use it, behavior, safety, rate limits, and return format. No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-documented. The description adds semantic value by explaining interactions: customCharset overrides include* options, noRepeating constraint, pronounceable mode limitations. This helps agents understand parameter dependencies without repeating schema details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a random password generator that generates cryptographically random passwords from configurable character classes, and distinguishes itself from sibling tools (passphrase for word-based, pin for numeric-only). The verb 'Generate' and resource 'cryptographically random passwords' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('dense mixed-character passwords') and when to use alternatives ('crypto_password_generator_passphrase' for memorable word-based, 'crypto_password_generator_pin' for numeric-only). Also notes randomness source and local execution, providing clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate safe operations. Description adds valuable context: 'local, deterministic compute', 'read-only, non-destructive, never stored, password never logged'. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, well front-loaded with purpose and scope. Every sentence adds necessary information: purpose, returned value, alternative tool, optional params, behavioral guarantees, rate limit. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 params and an output schema, description covers all key aspects: input handling, behavioral guarantees, rate limiting, and distinction from sibling. Output schema provides return details, so completeness is high.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds explanation of how each parameter affects scoring (e.g., 'if the password contains it (case-insensitive) the score is reduced'), going beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Password Strength Checker' with specific verb 'Score the strength of one password' and resource 'returns a 0-100 score, strength label, etc.' Differentiates from sibling crypto_password_strength_bulk for bulk use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool (single password) and when to use sibling (bulk). Mentions optional parameters and their effect. Also discloses rate limit (30 req/min anonymous), guiding appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond the annotations: it states that analysis is local, deterministic, read-only, non-destructive, never stored, and passwords are never logged. It also mentions rate limiting (30 requests/min anonymous). Since annotations already cover readOnlyHint, destructiveHint, and idempotentHint, the description enriches with operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise with no wasted words. It front-loads the key purpose in the first sentence, then efficiently covers usage, behavioral details, and rate limits. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple parameter (one array of strings) and the presence of an output schema (implied by the detailed output description), the description fully covers what the tool does, its behavior, and when to use it. No gaps for its complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'passwords' has 100% schema coverage including description and examples. The description adds that results are returned in the same order and that an empty string scores 0. This provides useful but not critical extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a bulk password strength checker that scores many passwords in one call, and explicitly distinguishes it from the sibling tool crypto_password_strength for single password analysis. The verb 'Score many passwords' and resource 'Bulk Password Strength Checker' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus the alternative: 'Use it to audit a list at once; use crypto_password_strength for a single password (it also accepts a username and context words).' This gives clear context and exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that it runs locally, is read-only and non-destructive, contacts no external service, is rate-limited, and generates random salt for non-deterministic output. Aligns with annotations (readOnlyHint, destructiveHint).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two well-structured paragraphs: first states purpose and usage, then details behavior and output. Every sentence adds value, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, and description lists return fields (derived key, hash string, salt, parameters, strength analysis). With 100% param coverage and clear behavior, it's fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds context on N being a power of 2, r as standard, p for independent mixing, length as derived key bytes, and salt optional with random generation, plus explains memory-hardness.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a scrypt password hash and key derivation, explicitly contrasting with siblings like crypto_argon2, crypto_bcrypt, crypto_pbkdf2, and crypto_scrypt_verify.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly specifies when to use scrypt ('when you want memory-hardness') and provides alternatives for different use cases (argon2/bcrypt for general storage, pbkdf2 for iteration counts, scrypt_verify for checking).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable context beyond annotations: 'Runs locally on the input you provide: read-only, non-destructive, contacts no external service, and is rate-limited.' This aligns with the annotations (readOnlyHint, destructiveHint, idempotentHint) and provides additional details about execution locality and rate limiting.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: it starts with the purpose, then usage guidance, then behavioral traits, and finally the return value summary. Every sentence adds value with no superfluous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool (2 parameters) and the existence of an output schema, the description is complete. It mentions the return information (match result, parsed parameters, strength analysis), covering all necessary aspects for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions and examples for both parameters. The description further explains the hash format and how N, r, p, salt are extracted from it, adding meaningful context beyond the schema's individual parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check whether a plaintext password matches an existing scrypt hash.' It specifies the verb (verify) and resource (password against hash). It also distinguishes from sibling 'crypto_scrypt' by noting the alternative use case for generating new hashes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided: 'Use this to verify a candidate password; use crypto_scrypt instead to generate a new hash.' This clearly tells the agent when to use this tool versus the sibling tool for hash generation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, non-destructive, idempotent. The description adds important behavioral context: runs locally, contacts no external service, rate-limited (30 req/min for anonymous). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences plus a usage clause, all front-loaded. Every sentence adds value without redundancy. It efficiently conveys purpose, usage, and behavioral details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 params, enums, output schema present), the description covers all essential aspects: purpose, supported algorithms, input formats, usage guidance, safety, rate limits, and return information (hex digest, length, security level, use cases). It is complete for effective decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage. The description adds value by explaining the algorithm parameter (choose variant, SHA3-256 default) and inputFormat (decode before hashing). It also notes empty string hashes to the fixed empty digest, which is beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes SHA3 hashes (SHA3-224/256/384/512) from text, hex, or Base64 input. It distinguishes itself from crypto_keccak_generator and crypto_hash, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool (standardized SHA3) and when to use alternatives (crypto_keccak_generator for Ethereum Keccak-256, crypto_hash for legacy hashes). This provides excellent guidance for correct tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, destructiveHint, idempotentHint), the description discloses critical behavioral traits: regex-based detection with validity checks, a specific resolution order for longer/stricter patterns to avoid partial matches, local execution without external services, rate limits (60 req/min for anonymous), and return format (masked text, replacement list, match counts). This fully informs the agent about how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense yet concise, front-loading purpose and detected types, then transitioning to usage guidance and technical details. Every sentence contributes meaningful information without redundancy. It is well-structured for an AI agent to quickly parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters, output schema present), the description covers all essential aspects: purpose, usage context, detection details, operational constraints, and return format. The annotations further complete the behavioral profile, making the tool fully comprehensible.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage, so the description's parameter details are supplementary. It clearly explains each mask mode (token, partial, counter) with examples, and describes the enable object's default behavior (all types on). This adds value beyond the schema's descriptions, though the schema already provides formal definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a PII Data Anonymizer and Redactor, lists specific PII types detected, and explicitly distinguishes itself from the sibling tool 'data_data_faker' which generates new synthetic data rather than masking existing values.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool ('scrub or redact real PII from logs, tickets, or datasets') and when to use the alternative ('data_data_faker' for generating synthetic test data). It also notes that the tool runs locally, is read-only, non-destructive, deterministic, and rate-limited, giving the agent clear operational context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint=true, destructiveHint=false), the description adds: runs locally, non-destructive, contacts no external service, rate-limited, non-deterministic by default with optional seed for reproducibility. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is detailed but front-loaded with key purpose. Could be slightly more concise but the level of detail is justified given the tool's complexity and sibling differentiation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, behavioral aspects, parameter semantics, and output structure (returns preset, count, array). With output schema present, no further explanation needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%; description reinforces parameter meanings: preset namespaced, count range, seed optional with security warning. Adds context not in schema (e.g., seed max length, not for security use).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates fake values for one Faker.js-style field preset, listing namespaces and examples. It distinguishes from sibling tools like data_random_data_generator and data_sample_data_generator, making the purpose specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (need many values of a single field type) and when to use alternatives (data_random_data_generator for multi-column records, data_mock_api_generator for mock endpoints). Also mentions rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds significant context beyond annotations: read-only, non-destructive, local, no external service, rate limit (60 req/min). Consistent with readOnlyHint and idempotentHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured, front-loaded with purpose, then details, alternative, and operations. Every sentence adds value; efficient for the amount of information conveyed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Comprehensive coverage of purpose, usage, behavior, parameters, operations, safety, and rate limits. No gaps given output schema handles return shape.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds operational context (which field for which operation) and acceptable formats. Provides clarity beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it validates and parses UUID/GUID strings, reporting structure and various forms. It distinguishes from crypto_uuid for generation, making purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (inspect/verify existing identifier) and when not (generate new one, use crypto_uuid). Also describes operations with their specific inputs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint; description adds that it runs locally, is non-destructive, contacts no external service, and has a rate limit of 60 requests/minute for anonymous callers, fully disclosing behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured: first sentence states purpose, then details compression, sibling differentiation, behavioral notes, and what is returned. Every sentence adds value; no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters with nested objects, an output schema, and moderate complexity, the description is thorough. It covers all aspects: direction, compression, local execution, rate limits, and return value (size and efficiency stats). Output schema handles return details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for each parameter. Description adds value by explaining z and y compression and clarifying that options are only for encoding, but schema already covers individual fields well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it is an ASCII85/Base85 encoder and decoder, specifies the Adobe PostScript character set with optional z and y compression, and distinguishes from sibling tools (base64 and base91).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool versus alternatives (base64 for web/MIME, base91 for compact output), and notes that it runs locally with rate limits, helping the agent choose appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint; the description adds that it runs locally, is read-only, non-destructive, and rate-limited, along with explaining the symmetric nature of Atbash.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is 5 sentences, front-loaded with the main purpose, and every sentence adds value. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple cipher and presence of output schema, the description covers behavior, parameters, usage, safety, and return implications thoroughly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so baseline is 3. The description adds value by explaining the symmetry and that the operation flag only labels output, supplementing the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool applies the Atbash substitution cipher, mapping A<->Z etc. It is a specific verb+resource and distinguishes from siblings by naming rot13 and caesar as alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use for classical/CTF puzzles and ROT-style scrambling, and provides alternatives when a different shift is needed. Also clarifies it provides no real security.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnly, destructive, idempotent), description adds local execution, rate limit (60 req/min), return details (converted string plus statistics and per-character analysis), and confirms no external service contact. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured: first sentence defines purpose, then efficiency stat, then usage guidelines, then behavioral traits. Every sentence is informative and necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all aspects: purpose, when to use, parameter roles, behavioral traits, and output summary. With output schema present, description is complete for an encoding/decoding tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage but description adds value by explaining operation directions and format interpretations (text/hex/binary), plus efficiency comparison. Baseline 3, description justifies 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Base91 Encoder and Decoder' with specific verb+resource, and differentiates from siblings by recommending when to use base91 vs base64/ascii85/basex.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Prefer encoding_decoding_base91 when output size matters most' and names alternatives for other scenarios, providing clear when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond the annotations to explain that the tool runs locally, is read-only, non-destructive, contacts no external service, and is rate-limited. It also details behavior for out-of-range shifts (rejected) and how preserve_case and preserve_non_alpha affect output. This fully discloses operational characteristics and is consistent with the annotations (readOnlyHint, destructiveHint, idempotentHint).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is informative and well-structured, with each sentence serving a purpose (purpose, alternatives, behavior details, return info). It is slightly lengthy but not verbose; a minor trim could improve conciseness without losing content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all relevant aspects: tool purpose, usage scenarios, behavioral traits, parameter effects, error handling, output structure (transformed text, info string, frequency analysis), and alternative tools. It is fully complete for an AI agent to select and use the tool correctly, especially with an output schema present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the input schema has 100% coverage, the description adds meaningful context: it explains that shifts 1-25 are valid and shift 13 equals ROT13, that non-integer shifts are rejected, and how the boolean parameters control case and non-alphabetic character handling. This clarifies parameter behavior beyond schema constraints and helps the agent set correct values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool encodes or decodes text using the Caesar shift cipher, specifying it works on A-Z letters with shifts 1-25. It distinguishes itself from sibling tools like rot13 and vigenere by naming them and describing their different use cases, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides usage context: suitable for puzzles, CTFs, and learning, but not for protecting secrets. It also names alternatives (encoding_decoding_rot13 for fixed ROT13, encoding_decoding_vigenere for keyword-driven shifts) and explains when each is appropriate, giving clear guidance on when to use this tool versus others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, and idempotentHint as true. The description adds valuable context: it runs locally, is read-only, non-destructive, contacts no external service, and is rate-limited (60 requests/minute). This complements the annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured paragraph that front-loads the main purpose. Every sentence adds value: purpose, limitations, operational traits, and output. No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of JWT decoding with claim analysis, the description is comprehensive. It covers what it does, what it doesn't do (no verification), when to use, and operational details (local, rate-limited). Output schema exists, so return values are documented; the description adds the claim analysis aspect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the baseline is 3. However, the description adds meaning beyond the schema by explaining the decoding process, splitting into parts, and the output structure (header, payload, raw parts, claim analysis). This adds value, but the schema already describes the token parameter well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool decodes and inspects a JSON Web Token offline, splitting it into header, payload, and signature. It specifies the verb 'decode and inspect' and the resource 'JSON Web Token', and distinguishes itself from the sibling 'security_jwt_generator_validator' by clarifying it does not verify signatures.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool versus the alternative 'security_jwt_generator_validator', which is for verification and assembly. It clearly indicates that this tool only decodes and does not fetch JWKS or verify signatures, guiding the agent to the correct tool for specific tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds 'Pure in-process compute, no DNS or network lookup' and rate limits (60/120 per min), providing context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise yet comprehensive, no redundant sentences. Purpose stated first, then usage guidance, then behavioral traits, then return format. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, description mentions 'Returns the converted string plus a per-label breakdown and a non-ASCII character listing,' ensuring full understanding. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description clarifies behavior for encode vs decode with examples and domain detection logic (dots vs single label), adding significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool encodes internationalized domain names to ASCII xn-- form and decodes back, with specific reference to RFC 3492/IDNA. It also names sibling tools for URL encoding and Unicode escapes, distinguishing it clearly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: use for domain-name encoding where each label is converted independently; directs to encoding_decoding_url for URL paths and encoding_decoding_unicode for arbitrary text escapes. This covers when to use and when not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and the description adds behavioral details such as 'stateless, runs offline, no auth, default rate limit 60 requests/minute'. It also discloses the return value structure: 'Returns the encoded/decoded result plus file_info header metadata and size stats.' This goes beyond annotations and provides comprehensive transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of three front-loaded sentences: first states the core function, second specifies operations, third gives usage guidance and alternatives. No wasted words; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, 2 required, 1 enum) and the presence of an output schema (stated), the description fully covers input, operation, and return values. It mentions output includes 'file_info header metadata and size stats', which complements the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds semantic value: it explains that 'text' can be plain text or a full uuencoded block, and that 'filename' and 'permissions' are used only for encoding. This clarifies the role of each parameter beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'UUEncode And UUDecode Binary Data' with a classic Unix format, and distinguishes operations via 'operation=encode' and 'operation=decode'. It also explicitly calls out sibling tools (xxencode, binhex, base64) with specific use cases, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Use this for legacy email/Usenet attachments and Unix file transfer' and directs agents to prefer xxencode, binhex, or base64 for specific alternatives. It also notes that the tool is 'pure compute: read-only, non-destructive, stateless, runs offline, no auth; default rate limit 60 requests/minute', guiding agents on when and how to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint), the description adds operational details: 'Runs locally', 'read-only, non-destructive, contacts no external service, rate-limited', and explains key normalization. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with purpose and well-structured. It is slightly verbose but every sentence adds value. Could be trimmed slightly without loss.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple parameters, non-trivial algorithm) and that an output schema exists, the description covers all necessary aspects: what it does, how parameters work, behavioral traits, return contents, and limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. The description adds meaning: explains key normalization (non-letters stripped, upper-cased) and that a 1-letter key degrades to Caesar. It also describes the return values (transformed text, normalized key, info string, frequency analysis).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Vigenère Cipher (Encode / Decode)' and explains it encrypts/decrypts text using a polyalphabetic cipher. It distinguishes from sibling tools by mentioning Caesar and ROT13 explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use cases: 'for puzzles, CTFs, and learning, not to protect secrets'. Also names alternatives: 'use encoding_decoding_caesar for a single fixed shift or encoding_decoding_rot13 for the fixed ROT13/ROT47 variants'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description clearly states behavioral traits beyond annotations: 'It never reads, writes, or mutates any file, environment, or host — it only transforms the text you pass in' and 'Runs locally: read-only, non-destructive, offline, contacts no external service, and is rate-limited (anonymous 30/min, 200/hr, 1000/day).' This adds context about rate limits and offline nature, supplementing the readOnlyHint, destructiveHint, idempotentHint, and openWorldHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, front-loading the core purpose and then detailing operation modes and usage guidelines. However, it is slightly verbose, repeating some details that are already in the schema descriptions. Every sentence is informative, but a few could be trimmed without loss of clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers all necessary aspects: purpose, operation modes, parameter usage, safety guarantees (stateless, read-only, offline), rate limits, and sibling tool differentiation. Given the presence of an output schema (context: has output schema: true), the description does not need to detail return values but still explains what each operation produces.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Even though schema description coverage is 100%, the description adds significant meaning by explaining how each operation mode uses the parameters. For example, it explains that 'parse' and 'audit' read the 'text' field, 'format' reads the 'input' object, and 'presets' ignores all other fields. It also describes the output of each mode, enriching the schema's enum descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Parse, audit, and format-convert a .env file' as a stateless text transform. It distinguishes from siblings by explicitly mentioning 'Use this for .env conversion and secret auditing; use linux_bash_script_generator for full shell scripts and linux_systemd_unit_generator for unit files.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives: 'Use this for .env conversion and secret auditing; use linux_bash_script_generator for full shell scripts and linux_systemd_unit_generator for unit files.' It also outlines the four operation modes (parse, format, audit, presets) with their specific use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnlyHint, destructiveHint, idempotentHint. Description adds rate limits, local execution, and confirms read-only/non-destructive, matching annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise description of ~4 sentences, well-organized: purpose, tool list, safety features, usage guidance, parameter hint. No wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, description covers all needed aspects: purpose, tool set, safety, usage alternatives, and return values (command, explanations, files, warnings). Sufficient for agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. Description adds value by listing supported tools and advising to call operation tools for field names, slightly improving understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Build' and resource 'command-line strings for 11 Linux tools', differentiates from siblings like linux_user_group_manager and linux_systemd_unit_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use (author/template commands) and when not (for user/group or systemd tasks), naming alternative tools. Also notes it never executes commands.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, destructiveHint, idempotentHint, openWorldHint), the description adds valuable context: it 'never runs a package manager', 'builds command strings from a static table', and is 'read-only, non-destructive, offline'. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized for the tool's complexity, front-loading the core purpose and distinguishing from siblings. Each sentence earns its place, providing clear and necessary information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (9 ecosystems, 4 operation modes) and the presence of a rich input schema and output schema, the description covers all essential aspects: what it does, how it works, when to use, and safety guarantees. It is complete for the intended use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining the operation modes and how parameters interact (e.g., 'translate' needs action and usually packages; others ignore fields). This contextualizes the parameters beyond the schema, earning a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to look up and cross-translate package-manager commands across 9 ecosystems. It uses specific verbs and resources, and distinguishes itself from sibling tools by naming them and specifying when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives: 'Use this for distro-specific package commands; use linux_command_builder for general find/grep/rsync/tar one-liners and linux_bash_script_generator for full scripts.' It also explains that the tool never runs commands and is safe.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint=true, destructiveHint=false) are reinforced and expanded: the description clarifies it only builds config text, never writes files, edits, or connects. It also mentions security warnings for weak settings, which adds beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is somewhat lengthy but well-structured: it starts with purpose, then behavioral constraints, then parameter explanations, and ends with usage guidance. Every sentence adds value, though a slight reduction in verbosity would improve conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complex nested schema and presence of an output schema, the description fully covers the tool's purpose, behavior, parameter details, and presets feature. It also mentions security warnings and sibling tools, making it complete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 100% schema coverage, the description adds significant meaning: explains 'operation' modes (generate vs presets), describes what presets returns, and summarizes the key client and server settings. It adds context about security warnings not in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates OpenSSH client and/or server config text from structured definitions. It distinguishes itself by explicitly stating it never writes files, connects to hosts, or touches the SSH agent, which differentiates it from the sibling linux_web_server_config_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear when-to-use guidance: 'Use this for OpenSSH connection and daemon config' and implies an alternative ('use linux_web_server_config_generator'). It also explicitly states what it does not do, helping agents avoid misuse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds behavioral context beyond annotations: 'read-only, non-destructive, deterministic, contacts no external service, rate-limited (60 requests/min anonymous).' No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with purpose, lists operations, explains operand/result behavior, then provides usage guidance. Efficient single paragraph with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all key aspects: operations, operands, bases, width, signedness, result format, and parse mode. Output schema exists, so return format is covered. Complete for the complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
While schema coverage is 100% (baseline 3), the description adds value by explaining shift semantics (e.g., shr vs ushr with signed) and the parse operation, enhancing understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs bitwise operations on integers with selectable base and width, and distinguishes itself from sibling tools like conversion_number_base and math_scientific_calculator by specifying use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool vs. alternatives, e.g., 'Use this for bit-level logic and shifts; use conversion_number_base for plain radix conversion and math_scientific_calculator for arithmetic expressions.' Also mentions rate limits and local computation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent. The description adds 'deterministic', 'contacts no external service', and 'rate-limited', providing useful context beyond annotations. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
5 sentences, no fluff. Front-loads purpose, then output, usage guidelines, and behavioral traits. Every sentence earns its place. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity with 7 parameters and existing output schema, the description covers purpose, usage, behavior, and output summary. No gaps remain for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions for each parameter. The description adds value by summarizing outputs (final balance, interest, etc.) and explaining operation parameter semantics. This goes beyond baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: projecting future value of a lump-sum with fixed rate, periodic compounding, and optional contributions. It distinguishes itself from siblings like math_loan_calculator and math_percentage_calculator, making scope explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when-to-use (savings/investment growth) and when-not-to-use (use math_loan_calculator for loans, math_percentage_calculator for percent calculations). This leaves no ambiguity for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description aligns with annotations (readOnlyHint, destructiveHint, idempotentHint) and adds context: runs locally, non-destructive, contacts no external service, rate-limited. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise yet comprehensive. Front-loaded with purpose, then details modes and special features, then sibling comparison, then behavioral notes. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all aspects: purpose, parameters, edge cases, sibling differentiation, behavior, and rate limits. Output schema exists so return values not needed. Complete for a calculator tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (baseline 3). Description adds meaning: explains operation modes, extra payment effect, startDateIso labeling. Adds value beyond schema but not highly extensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates fixed-rate loan amortization with specific outputs (monthly payment, total interest, etc.). It distinguishes itself from the sibling math_compound_interest_calculator by explicitly stating when to use each tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use (loan amortization) and when-not-to-use (use compound interest calculator for savings). Also mentions handling extra payments, zero-rate loans, and rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, destructiveHint, idempotentHint), the description adds critical behavioral details: local execution, no external service calls, rate limiting (60 req/min for anonymous), and the return value structure (normalized integer plus words). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact at 4 sentences, front-loading the core purpose. Each sentence serves a distinct purpose: main function, example uses, sibling differentiation, and behavioral notes. No redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simple interface (2 params, 100% schema coverage, with output schema), the description fully covers purpose, usage guidelines, behavioral traits, and parameter semantics. Annotations and output schema description fill remaining gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% so baseline is 3. The description adds meaningful context beyond the schema: notes that string inputs handle beyond JS-safe range, magnitude must be below 10^36, and non-integers/floats are rejected. This aids the agent in correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's primary function: converting integers to English or Spanish words. It specifies the number scale (short/long), language options, magnitude limit, and input types. It also distinguishes itself from sibling tools like conversion_string_number and math_roman_numerals_converter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly guides when to use this tool (for cardinal text in cheques, legal copy, accessibility) and provides clear alternatives for related tasks (conversion_string_number for free-form numeric format conversion, math_roman_numerals_converter for Roman numerals).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, it details live network call, third-party dependency, non-determinism, rate limits, and limitations of optional parameters (prefixes/upstreams).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph with front-loaded purpose and key details; each sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, behavior, alternatives, parameters, rate limits, return content, and limitations; complete for a lookup tool with 5 parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all parameters with descriptions; description adds value by explaining behavior of boolean flags and worker_id, though schema coverage is already high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool resolves IP/domain/AS to ASN details, and explicitly names sibling tools for differentiation, making it highly specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states when to use this tool ('identify who owns/routes an IP') and provides alternative tools for different purposes (whois, BGP, geolocation).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint, destructiveHint, idempotentHint. The description adds context: pure offline IPv4 math, no DNS/network contact, rate-limited (30 req/min). This exceeds annotation information without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that packs a lot of information. While comprehensive, it could be more structured (e.g., bullet points) for quick scanning. However, every sentence adds value, and it is overall concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (though not provided here), the description lists all key outputs: network/broadcast, first/last host, counts, masks, binary, class, RFC 1918 flag, sample subnet split, and summary. For a 2-parameter tool, this is fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds examples (e.g., '192.168.1.0/24', '192.168.1.0 255.255.255.0') and clarifies behavior for bare IPs (treated as /32), enriching understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool parses IPv4 CIDR notation or IP+mask and returns a comprehensive set of network details. It explicitly distinguishes itself from sibling tools like network_subnet_calculator and network_ip_range_calculator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use and when-not-to-use guidance, mentioning alternatives for different input forms (network_subnet_calculator for explicit IP-plus-mask, network_ip_range_calculator for enumeration). It also notes offline and rate-limited behavior.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds behavioral details beyond annotations: read-only, non-destructive, no external service contacts, rate limits (60 req/min, 500/hr). Also enumerates output types and classification. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single well-structured paragraph with each sentence adding value: purpose, method, output types, sibling differentiation, input format, behavioral notes. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists, description does not need to detail return values but still lists them. Covers all necessary context for a two-parameter tool with high schema coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions. Description adds that ipv4 must be dotted-decimal without CIDR suffix, and that input is a deprecated alias. This adds context beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description starts with 'IPv4 to IPv6 Converter' and clearly states it converts a single IPv4 address to IPv6 representations using offline arithmetic, distinguishing it from sibling tools for subnet planning and CIDR notation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to use network_subnet_calculator or network_cidr_calculator for subnet planning, and clarifies this tool only transforms one host address without CIDR parsing. States input format explicitly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses behavioral traits beyond annotations: non-idempotency for generate operations, local execution via JS logic bridge, read-only and non-destructive nature, no external service contact, and rate limiting (60 req/min). Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds valuable context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured paragraph that front-loads the purpose and systematically covers all operations, constraints, use cases, and alternatives. Every sentence adds necessary information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (9 parameters, 5 operations, enum constraints), the description is complete. It explains all operations, parameter dependencies, and provides use-case guidance. The output structure is briefly described, and rate limiting is mentioned.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by explaining parameter interactions (e.g., universallyAdministered ignored if locallyAdministered is true) and clarifying operation-specific applicability (e.g., count only for generate). This increments the score to 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as generating and analyzing MAC addresses, listing all five operations (generate, analyze, format, use_case, vendor_oui) with specific verbs and resources. It distinguishes itself from the sibling tool osint_mac_vendor_lookup by specifying when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (fabricating MACs for VMs, lab testing, network config) and when to use an alternative (osint_mac_vendor_lookup for real manufacturer resolution). It also explains the different operations and their intended scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that it queries a third-party API (ip-api.com), is rate-limited, reads IP from request headers, and that results are live. These details go beyond annotations, which already set readOnlyHint=false.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is comprehensive but slightly verbose; however, each sentence adds value and it is well-structured with important details front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, behavior, input, and expected output fields. With no parameters and rich annotations, the description is fully informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty with additionalProperties: true, and the description explicitly says 'Takes no input (HTTP GET, no body or query parameters)', adding clarity beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool detects the caller's public IP and enriches it with geolocation, proxy/VPN, and ASN details. It distinguishes from sibling tool 'network_ip_geolocation' by specifying when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (requester's own address) versus alternatives (network_ip_geolocation for arbitrary IP). Also provides context on side effects and rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=false. The description adds context: 'Read-only and non-destructive; contacts no external service; results vary per request so it is not idempotent.' It also details rate limits and CAPTCHA, which are not in annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the main purpose and is well-structured. It is concise but the final sentence listing return fields is a bit dense; however, it still efficiently communicates key information without excess.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single optional parameter, existence of output schema, and many sibling tools, the description covers all aspects: purpose, parameters, behavior, limitations, and return structure. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (1 parameter, fully described). The description adds meaning: 'Omit to use the default master-server behavior.' This clarifies usage beyond the schema field description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('Inspect', 'Reflects and analyzes') and clearly states the resource (incoming HTTP request headers). It explicitly distinguishes from sibling tools like my_ip, browser_fingerprint_viewer, and header_analyzer by contrasting their purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use the tool ('to see the exact User-Agent...') and when not to use it (it does not fetch headers from a remote URL). It names alternatives (my_ip, browser_fingerprint_viewer, header_analyzer) and describes rate limits and CAPTCHA conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false. The description adds crucial context: 'Pure offline IPv4 math: read-only, non-destructive, contacts no DNS or network service, and is rate-limited (30 requests/minute for anonymous callers).' This enhances transparency beyond annotations. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that efficiently conveys the purpose, use cases, behavior, and limitations. It is well-structured, front-loading the core purpose and output list, then providing usage guidance and behavioral notes. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 6 parameters (0 required), 100% schema coverage, and an output schema, the description covers all essential aspects: purpose, input modes, output fields, behavioral guarantees (offline, read-only, rate-limited), and differentiation from siblings. It does not need to explain return values since an output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds context about when each parameter is used (e.g., 'Used when inputFormat is cidr') and explains the purpose of the input modes. While the schema already documents each parameter, the description clarifies the conditional relationships, justifying a slightly higher score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is an IPv4 Subnet Calculator, specifies the two input modes (CIDR or IP+Mask), and lists the computed outputs. It also distinguishes itself from sibling tools like network_cidr_calculator and network_ip_range_calculator by stating their different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool (compute subnet details) and when not to (for conversion or enumeration, directing to siblings). It also mentions the tool is pure offline math and read-only, setting appropriate expectations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, non-destructive, idempotent. The description adds crucial behavioral context beyond annotations: the API call runs locally, is rate-limited (20 req/min anonymous), and the returned serviceUrl points to an external third-party renderer fetched separately. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, front-loaded with purpose, and each sentence adds value. However, it is slightly verbose (four sentences) and could be trimmed without losing essential information. Still, it is clear and not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (nested settings, multiple symbologies, output schema), the description covers everything: local API behavior, external renderer, rate limits, output fields (normalized type, cleaned data, validity flag, etc.). No gaps remain for effective tool usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds significant meaning: it explains validation rules per symbology (e.g., '12 digits for upc, 13 for ean13'), alias parameters, fallback behavior for unknown type, and the settings object. This helps the agent correctly format data and understand output structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool builds a barcode payload and render URL, listing six specific symbologies with character constraints. It distinguishes itself from sibling tools osint_barcode_scanner, osint_qr_code_generator, and osint_ean_upc_validator by explicitly stating when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: 'Use this to prepare barcode content and a render URL; use osint_barcode_scanner to decode..., osint_qr_code_generator for 2D QR codes, and osint_ean_upc_validator to only checksum-verify...' This clearly tells the agent when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond annotations: it states the validation runs locally, is read-only, non-destructive, contacts no external service, and has a rate limit of 20 requests/minute. This complements the readOnlyHint, destructiveHint, and idempotentHint annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded. It begins with a one-line summary, then expands on purpose, usage guidance, behavioral details, and return value. Every sentence adds necessary information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (ISO 9362 validation, decoding, rate limits), the description covers all essential aspects: purpose, when to use, behavioral traits, parameter semantics, and return structure. It is fully adequate for an AI agent to understand and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing basic parameter info. The description further explains that the 'code' parameter is case-insensitive and strips spaces/punctuation, and that 'bic_swift_code' is an alias with precedence rules. This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates a BIC/SWIFT code, decodes its four parts, and confirms format and structure. It specifies the code length (8 or 11 characters), character pattern, and country recognition, while distinguishing itself from the sibling osint_iban_validator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly directs to use osint_iban_validator when the user has a full IBAN instead of a bank identifier code. This provides a clear alternative and implies the appropriate context for this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and non-destructive behavior. The description adds critical context: validation is offline/rule-based, checks 7-15 digit length and a built-in table of ~20 country codes, no live HLR/carrier lookup, and carrier/timezone notes are heuristic. This fully discloses limitations beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: main purpose first, then output details, then limitations/alternatives, and finally rate limits. Every sentence adds information without redundancy. It is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity, full schema and output schema presence, and annotations, the description provides all necessary context: functionality, output fields, limitations, alternatives, and rate limits. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining parameter usage: 'Provide E.164 form for reliable country detection' and notes that symbols like spaces/dashes are stripped. This goes slightly beyond the schema's own descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates and formats phone numbers, listing specific output formats (E.164, international, etc.) and data (country, type, carrier). It explicitly distinguishes from sibling tools like osint_iban_validator by saying to use those for bank/card identifiers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: use other tools for bank or card identifiers, and advises providing E.164 form for reliable country detection. It also notes the offline, rule-based nature and rate limits, helping the agent decide when to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes beyond annotations by detailing offline computation (no external API), non-destructive nature, timestamp embedding causing non-idempotent responses, rate limit (20/min anonymous), and input rejection criteria (exactly 17 chars, no I/O/Q). No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is comprehensive but slightly verbose; however, it is front-loaded with the main purpose and well-structured. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's batch nature and available schema/output schema, the description fully covers input constraints, behavior, limitations, and output structure (per-VIN info, breakdown, validity, warnings, summary). No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaning beyond schema: describes input normalization (uppercased/trimmed), filtering of invalid entries, and explains each option field (validate_check_digit, include_manufacturer_info, detailed_breakdown) with behavior flags.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it decodes VINs using built-in tables and check digit validation, and distinguishes itself from sibling tools like osint_ean_upc_validator, osint_isbn_validator, and osint_credit_card_validator, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use this tool (VIN decoding) and when not to (product/book codes, PAN Luhn checks), naming specific alternatives. Also notes it's offline and rate-limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, the description discloses significant behavioral details: it is read-only, non-destructive, stores nothing, contacts no external service, uses only CSPRNG, is rate-limited, and each call returns fresh keys. This fully informs the agent of its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph but efficiently packs key information. It is front-loaded with purpose, then details, guidelines, and behavioral notes. Slightly long but no unnecessary content; could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, multiple operations, presets) and the existence of output schema, the description covers all critical aspects: operations, formats, randomness source, rate limits, storage guarantees, and sibling differentiation. It is complete for an agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
While the input schema has 100% coverage with descriptions, the description adds crucial context: explains the purpose of each operation (generate, generateMany, presets), details that bearer and uuid-v4 ignore length/byteCount, and clarifies the randomness source. This enriches understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates random API keys, bearer tokens, and signing secrets, with specific verb and resource. It lists nine formats and presets, and explicitly distinguishes from crypto_password_generator, making it easy to differentiate from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool (machine-to-machine secrets) and when to use alternatives (crypto_password_generator for human-typeable passwords). It also mentions bulk mode and presets, and notes rate limits, providing clear usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent. The description reinforces that it does not touch any server files and runs locally in a sandbox. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that front-loads the core purpose and lists features comprehensively. While slightly dense, it is still relatively concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (14 params, nested objects, output schema), the description covers purpose, behavior, parameter details, warnings, and alternatives. It is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Despite 100% schema coverage, the description adds valuable context beyond schema, such as warnings for self-redirects, explanations of wwwMode values, and compression size comparisons.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates Apache .htaccess text from structured options and returns it as a string, emphasizing it does not deploy or write files. It lists many features and distinguishes from sibling tools like security_csp_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool versus alternatives (e.g., 'Use security_csp_generator for Content-Security-Policy headers'). Also explains the 'presets' operation for listing ready-made configurations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes determinism, pure compute, read-only, non-destructive, no external service contact, rate limit (30/min for anonymous), and output format, adding value beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Information is front-loaded, each sentence serves a purpose, no redundancy, and well-structured despite length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema and full parameter descriptions, the description covers purpose, usage, behavior, and output, leaving no gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. Description adds context for the operation parameter (generate vs presets) and clarifies usage, boosting it to 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it generates a password policy document and validators, and distinguishes from sibling tools like crypto_password_generator and crypto_password_strength.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool versus alternatives, and describes the two operations (generate and presets) with clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly, idempotent, non-destructive. The description adds behavioral traits: runs locally, 5s timeout, XML-escaping hrefs, warnings for invalid BCP47, non-absolute URLs, duplicates, missing x-default, and reciprocity. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph but well-structured: purpose first, then operation modes, usage guidance, sibling differentiation, and runtime info. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (6 params, 1 required) and existence of output schema, the description covers all necessary context: input, output formats, warnings, runtime, alternatives. It is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds context about operation modes, output formats, warnings, and how parameters interact (e.g., includeXDefault and xDefaultHref). This adds meaning beyond the schema, but not significantly enough for a 5.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: generate and validate hreflang annotations. It specifies the verb (generate/validate) and resource (alternate-language link tags). It also distinguishes from sibling tools seo_sitemap_generator and seo_meta_tag_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when-to-use: 'Use this for standalone alternate-language tags; use seo_sitemap_generator when you want the same alternates embedded in a full XML sitemap, or seo_meta_tag_generator for a complete <head> meta block.' Also mentions runtime constraints (5s-bounded Node process).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, idempotentHint; description adds 'Runs locally on the text you provide (read-only, non-destructive, contacts no external service)' and rate limit of 30 requests per minute for anonymous callers. No contradiction and adds meaningful context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is thorough but slightly lengthy; however, every sentence earns its place by adding purpose, usage, behavioral notes, or parameter semantics. It is well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, output schema exists), the description covers purpose, usage context, behavioral traits (read-only, rate-limited), parameter details, and output structure. It is fully complete for an agent to decide and use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 6 parameters. Description adds value by explaining the pixel width estimation (Arial font sizes), the purpose of brand and brandSuffix parameters, and details of the output (chars, words, pixel width, truncation point, score, warnings, suggestions). This goes beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes title and meta description lengths against Google SERP pixel limits, with specific verb 'analyze' and resource 'HTML title tag and meta description'. It differentiates from sibling tools seo_meta_tag_generator and seo_keyword_density_checker by explicitly stating what each does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance on when to use ('audit or proof an existing snippet before publishing') and when not to (for building tags, use seo_meta_tag_generator; for body content, use seo_keyword_density_checker). Also notes rate limiting and read-only nature.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds behavioral context: 'Runs locally with no external input: read-only, non-destructive, offline, and rate-limited.' This enhances transparency beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is comprised of 4 sentences, each essential. It front-loads the core purpose and efficiently covers scope, alternatives, and behavior. No unnecessary words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's role as a reference table generator with two parameters, the description covers output details (table array plus meta summary), parameter effects, and relevant alternatives among many siblings. The presence of an output schema offloads return value details, making the description appropriately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has full description coverage for both parameters. The description adds meaning by explaining the effect of format (standard vs html) and extended (include 128-255) in context of the output, without repeating schema details verbatim.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states that the tool generates the full ASCII character reference table, detailing what it covers (code points, values, glyphs, etc.). It clearly distinguishes from siblings like text_hex_ascii_converter and conversion_number_base.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides explicit when-to-use (complete lookup table) and when-not-to-use (for converting specific strings, use alternatives). It also states that it requires no external input, giving clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds valuable behavioral context: it runs locally, is rate-limited (60 req/min for anonymous callers), supports specific characters (A-Z, 0-9, space, few punctuation), and unknown characters render as blank space. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with purpose. Every sentence adds value, though the sentence about local execution and rate limits is slightly verbose and could be condensed. Overall, it's efficient for a tool with 3 parameters and sibling comparisons.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, output schema present, rich annotations), the description is completely sufficient. It covers all aspects: purpose, usage context, behavioral traits, parameter details, limitations, and sibling differentiation. No missing information for proper tool selection or invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds meaning beyond the schema: for 'text', it clarifies required, max length 50, and uppercasing; for 'font', it explains the visual difference (6 rows, hash chars vs. 3 rows, Unicode block glyphs) and fallback behavior; for 'width', it clarifies it's a reported line width, not a wrap/truncation setting, and values are clamped.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates ASCII-art banners from text, specifies the two fonts (block and small), and the character set. It distinguishes itself from sibling tools text_ascii_table and text_ascii_art by explaining they serve different purposes (reference chart vs. image-to-ASCII conversion).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('for terminal headers, README titles and decorative plain-text banners') and directly names alternative tools for different tasks ('use text_ascii_table instead to look up ASCII character codes... or text_ascii_art to convert an image to ASCII').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations, including that it runs locally, is read-only, non-destructive, deterministic, and rate-limited (with specific limits). It also states the return format (escaped/unescaped string plus metadata). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence adds value, covering purpose, modes, usage guidance, behavior, and constraints. The description is well-structured, efficient, and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of output schema and 3 parameters, the description fully covers behavior, return values, rate limits, and sibling differentiation, making it complete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description enriches parameter understanding by explaining the four modes in detail and the effect of the reverse parameter, adding value beyond the schema's enum descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a Bash CLI Shell Escaper with four quoting styles and reverse operation. It distinguishes itself from text_string_escape by specifying the target use case (shell commands vs. other syntaxes).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises preferring this tool over text_string_escape for shell commands and directs to the sibling for SQL/CSV/JS/regex/PHP/XML, providing clear when-to-use and when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. Description adds valuable context: runs locally, no external service, rate-limited (60 req/min), and details return fields (isPalindrome, reversed strings, per-word analysis, etc.), going beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: starts with purpose, then usage guidelines with alternatives, followed by behavioral context, and ends with output summary. It is front-loaded and every sentence adds value, though somewhat lengthy, it remains informative without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (context indicates has output schema: true), the description does not need to detail return values but does mention key fields. It covers all aspects: functionality, options, behavior, limitations (rate limit, local execution), and comparisons with siblings, making it complete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good descriptions. The description adds context by summarizing options (caseSensitive, ignoreSpaces, ignorePunctuation, analyzeWords) and their effects, but does not provide new parameter-specific details beyond the schema. Slight added value over schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if text reads the same forwards and backwards at whole-string and per-word levels, with options to ignore case/spaces/punctuation. It distinguishes from siblings text_reverse_text and text_anagram_generator by specifying when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (palindrome detection) and when to use alternatives (reverse_text for flipping, anagram_generator for rearranging). Also mentions it runs locally and is rate-limited, providing clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that it runs locally, is read-only, non-destructive, offline, and rate-limited (~60 req/min), providing context beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences: first states main function, second provides usage guidance and alternatives, third adds behavioral traits. No wasted words; each sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given an output schema exists (implied), the description covers purpose, alternatives, behavioral traits, and parameter semantics. It mentions return value format, making it complete for this tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed descriptions and examples for all three parameters. The description adds format-specific escape rules (e.g., 'sql doubles single quotes'), which goes beyond the schema's enum descriptions, though much is already covered.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The title and description explicitly state the tool escapes/unescapes strings for eight code/data syntaxes. The purpose is specific, with a clear verb and resource, and distinguishes from siblings by naming alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool vs. alternatives (e.g., preferring text_bash_cli_escaper for richer shell modes, encoding_decoding_url for percent-encoding, etc.). It also notes functional identity with encoding_decoding_string_escape.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint), the description adds behavioral details: runs locally, read-only, rate-limited, and explains business day arithmetic and month clamping. No contradiction; all are consistent with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph but is information-dense and well-front-loaded. Every sentence adds value, though breaking into bullet points could improve scannability. Still, it's concise for the amount of information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, business day logic, edge cases), the description covers input behavior (clamping), output format (returns base/result dates, total days, weekends skipped), constraints (rate limit, local execution), and non-destructiveness. Complete and sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
While the schema covers 100% of parameters, the description adds crucial semantics: explains the order of operations for years/months clamping, and details the behavior of 'days' for business days vs calendar days. This goes beyond the schema's basic descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Date Calculator (Add/Subtract Duration and Business Days)'. It explicitly distinguishes from sibling tools like time_date_difference and time_time_duration, making it easy for an agent to select the correct tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'Use this when you have a known start date and want the resulting date' and directs to alternatives for other scenarios. It also notes deterministic behavior and no current-time dependency, aiding appropriate invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds valuable context: 'Pure local computation: read-only, non-destructive, contacts no external service, rate-limited (60 requests/minute)'. It also mentions strict validation and BCE support, fully disclosing behavior without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (5-6 sentences) and well-structured: purpose first, then mode explanation, then differentiation, then constraints, then safety/performance. Every sentence provides unique value, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (three modes, 11 parameters), excellent annotations, and an output schema, the description covers all necessary aspects: inputs, modes, constraints, safety, rate limits, and return metadata. No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 11 parameters. The description goes further by explaining the operation enum and how parameters relate to each mode (e.g., count for scan mode, fromYear/toYear for distance). This adds meaningful semantic context beyond the schema, justifying a slightly above-baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly labels the tool as a 'Day of Week Calculator' and explains three distinct modes (weekday, scan, distance) with specific verbs like 'Find', 'list', and 'measure'. It distinguishes from sibling tool time_date_difference by specifying when to use each, ensuring no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('weekday lookups and recurring weekday schedules') and when to use the alternative time_date_difference ('business-day counts or to add/subtract a duration'), providing clear, actionable guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds context: runs locally, read-only, deterministic, offline-capable, rate-limited, no auth, and describes return format. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise (under 200 words) and well-structured: front-loaded with purpose, then operation details, then sibling tool comparisons, then behavioral notes and return format. Every sentence provides essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (13 parameters, 6 operations, nested objects) and that it has an output schema, the description covers everything: purpose, when to use, operation semantics, behavioral traits, and return structure. It leaves no significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage. The description explains each operation's semantics (e.g., 'compute normalizes one duration; add sums 2-100 durations; subtract returns a-b (negative allowed); multiply scales; divide divides; between returns end-start'). This adds value beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool does pure clock-time/duration arithmetic on HH:MM:SS or total seconds, and explicitly distinguishes it from sibling tools like time_date_difference, time_age_calculator, and convert_timestamp.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit instructions on when to use this tool and when to use alternatives, e.g., 'use time_date_difference for calendar years/months/days and business-day counts, time_age_calculator for age/birthday spans, and convert_timestamp for Unix-epoch to human-date conversion.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds significant behavioral context beyond annotations: pure local computation, no network/storage, rate-limited (60 req/min anonymous), and explains live vs pinned instant behavior. Annotations already declare readOnlyHint and destructiveHint, but description enriches understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise yet comprehensive, front-loaded with purpose, then operational details. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists and annotations are rich, the description is complete. It covers all operations, parameter behaviors, and use cases. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds meaning: explains operation modes, tzs constraints (1-12 entries), and iso's optional nature with idempotency implications. This goes beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool renders wall-clock time across multiple IANA time zones with details like date, offset, abbreviation, etc. It distinguishes itself from sibling tools like time_timezone_converter and time_iso_8601_formatter, making its purpose specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicit guidance is provided: 'Use this for a multi-city now view; use time_timezone_converter for one-off wall-clock zone-to-zone conversion, or time_iso_8601_formatter for ISO/RFC string parsing.' Also explains operation modes and when to use each.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds behavioral details such as collapsing identical corners to shortest form, local execution without external service, and rate limiting, which go beyond the annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is fairly concise and front-loaded with the main purpose. While it contains multiple sentences, each adds necessary value. Minor redundancy could be trimmed, but overall it is well-structured without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (context signal), the description does not need to detail return values, but it still summarizes the returned items (CSS string, uniformity flag, HTML preview, echoed values, usage examples). This makes the tool's behavior fully understandable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning: it explains that missing corners default to 0, empty object returns HTTP 400, and previewSettings only affect the preview HTML, not the generated CSS. This clarifies parameter behavior beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool generates CSS border-radius code from per-corner pixel values, returning optimized declarations, usage snippets, and an HTML preview. It also explicitly distinguishes itself from sibling tools like webdev_box_shadow_generator and webdev_css_gradient_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use and when-not-to-use guidance by naming alternative tools for shadows, gradients, and filters. It also informs about local execution, read-only behavior, non-destructive nature, and rate limits, aiding the agent in selecting the correct tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations, it adds local execution, rate limits, and opacity folding behavior. No contradiction with readOnlyHint/ idempotentHint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded purpose, efficient and complete without extra words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Mentions all key return elements and usage snippets. Output schema exists but description still provides context. No missing critical info.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds value by summarizing parameters and explaining layer joining and opacity handling, earning a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates CSS box shadows from layers, with output details like combined declaration and usage snippets. It explicitly distinguishes from siblings by naming alternatives for related tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Directly specifies when to use alternatives: 'use webdev_border_radius_generator... for rounded corners' etc. Also states context: runs locally, read-only, rate-limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnly, non-destructive), description adds details about local execution via Node bridge, rate limiting (60 req/min anon), and output contents (size/line stats). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with key actions, and structured with clear sections: summary, usage guidance, limitations, and behavioral notes. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 params, nested object, output schema), the description covers all essential aspects: purpose, usage, alternatives, limitations, behavior, and output. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the meaning of 'format' vs 'minify' actions and the role of indentSize, but schema descriptions already cover parameters well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool formats and minifies HTML, CSS, or JavaScript code, and identifies it as a multi-language dispatcher. It differentiates from sibling tools like webdev_css_beautifier and webdev_javascript_beautifier.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool versus alternatives (e.g., for single languages or SQL/JSON/XML). Also warns about limitations like JSX and malformed input, guiding appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, non-destructive, idempotent. Description adds that it runs locally, contacts no external service, is rate-limited (30 req/min for anonymous), and is idempotent, with no contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, front-loading purpose and modes, then usage guidelines, then behavioral notes, then return value summary. Every sentence is informative with no redundancy. Efficient use of space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 10 params, two modes, and an output schema, the description is thorough. It covers both text and file modes, explains all options (MIME, charset, examples), and describes return fields. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. Description adds meaning by explaining how inputMethod selects mode, which params are required in each mode, defaults, and behavior (e.g., charset inclusion, optimization, examples). This goes beyond raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it builds data: URIs from text or base64 file content, specifying two modes and explicitly distinguishing from sibling tools (webdev_base64_image_encoder, encoding_decoding_base64) by enumerating use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use (arbitrary text, SVG, CSS, JS, any MIME) and when-not-to-use (raster images needing pixel detection; plain base64 encode/decode), naming specific alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint=true, destructiveHint=false), the description adds concrete behavioral details: runs locally on a static table, no external service contact, rate-limited to 60 req/min for anonymous callers. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (4 sentences) and well-structured: purpose first, then usage guidance, then behavioral details. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (not shown), the description covers purpose, usage guidance, behavioral traits, and even extra detail like the fixed list of common entities. It is fully adequate for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed parameter descriptions. The description adds context not in the schema, such as 'Blank returns all entities' and mentions pagination pattern, but does not significantly extend parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as an HTML entity reference lookup, specifying the exact fields returned (entity name, decimal code, hex code, rendered glyph, description, category). It explicitly distinguishes from sibling tools like encoding_decoding_html_entities, text_ascii_table, and webdev_http_status_reference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: 'Use this to look up the entity for a symbol or vice versa; use encoding_decoding_html_entities to actually encode or decode...'. It also mentions operational constraints (local, rate-limited).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds valuable context: it runs locally via a Node bridge, is non-destructive, contacts no external service, and is rate-limited. It also clarifies it's a regex/heuristic minifier, not an HTML parser, and that conditional comments are preserved. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise yet comprehensive, covering purpose, parameters, usage guidelines, limitations, and performance characteristics in a well-structured paragraph. Every sentence contributes meaningful information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, output schema exists), the description is complete. It explains the main function, all optional transforms, usage with sibling tools, behavioral caveats, and return value components (minified HTML plus sizes/savings/ratio). No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are already well-documented. The description adds value by summarizing that 'every transform is an independent boolean toggle', which clarifies the parameter structure. Although it doesn't add details beyond the schema, it provides a useful high-level overview.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it minifies HTML by stripping comments, collapsing whitespace, and other transforms. It explicitly distinguishes from sibling tools like webdev_css_minifier and webdev_js_minifier by noting their separate use cases for standalone files. The verb 'minify' and resource 'HTML' are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives: 'Use webdev_css_minifier or webdev_js_minifier to compress standalone stylesheets/scripts, web_dev_html_to_markdown to convert HTML to Markdown, and webdev_javascript_beautifier to expand rather than compress.' It also warns about unusual markup due to the regex/heuristic approach.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds significant behavioral context beyond annotations, including local execution via Node bridge, read-only and non-destructive nature, no external service contact, rate limiting, and irreversibility warning. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (4-5 sentences), well-structured, and front-loaded with the core purpose, followed by details and caveats. Every sentence provides useful information without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, output schema), the description covers purpose, usage, behavior, parameters, limitations, and output content, making it complete for an agent to understand and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by explaining level presets and mentioning the 'input' alias, but the schema already describes parameters well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as a JavaScript code minifier that shrinks file size through specific operations, and explicitly distinguishes it from siblings (obfuscator and beautifier).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use the tool (production deployment for smaller file) and when to use alternatives (obfuscator for hiding logic, beautifier for reversing), along with important caveats about non-guaranteed runnability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key traits beyond annotations: warns that output is not guaranteed runnable nor reversible (regex-based), describes local execution via Node bridge, read-only/non-destructive, rate-limited. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is comprehensive yet well-structured, front-loading the verb and resource. Each sentence serves a purpose (purpose, alternatives, limitations, execution context, output summary). No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 params, nested options, output schema), the description covers all aspects: purpose, when to use, behavioral caveats, parameter details, return value. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining strength presets' effects and individual option behaviors (e.g., mangleNames skips reserved words, controlFlowFlattening defaults depend on strength). This enriches understanding beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Obfuscate a JavaScript snippet to deter casual reading and reverse engineering' and lists specific techniques. It distinguishes from siblings by naming webdev_js_minifier and webdev_javascript_beautifier, making the tool's role unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this to harden client-side JS' and provides clear alternatives: webdev_js_minifier for minification only, webdev_javascript_beautifier to reverse compaction. This fully guides when to use and when not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, destructiveHint, idempotentHint), description adds critical details: runs locally, deterministic, offline, rate-limited (60 req/min, 500/hr), non-destructive, and describes return structure (rendered HTML, stats, sanitized preview). Also clarifies that options are currently ignored. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured, front-loaded with purpose, then features, usage guidance, properties, return info. No redundant sentences; every sentence provides essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (one required param, optional options, output schema exists), the description covers input constraints, behavior, return values, rate limits, and forward compatibility. Fully complete for agent selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds value beyond schema: for markdown, notes non-empty requirement and 400 error; for options, states they are reserved and do not change output. This extra context justifies a score above baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts Markdown to HTML using regex-based rules, listing supported elements (headings, bold, code, tables, etc.). It differentiates from siblings by naming the inverse tool (web_dev_html_to_markdown) and the minifier (webdev_html_minifier), providing specific verb+resource scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use ('render Markdown for display') and explicitly names alternatives for inverse conversion and HTML minification. Provides clear context for choosing this tool over siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description adds details: 'Read-only and non-destructive, rate-limited to 30 requests per minute for anonymous callers' and explains that the server runs Dart Sass without external file access, enhancing transparency beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, fitting in 6 sentences without redundancy. It front-loads purpose, then provides usage guidance, implementation details, and return values. Every sentence adds value, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple parameters, output schema, annotations), the description covers all necessary aspects: purpose, alternatives, behavioral constraints, rate limits, and return fields (compiled CSS, source, source map, statistics). It is complete and no gaps are evident.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining the 'includePaths' parameter is accepted but ignored for security, and outlines the effect of 'sourceMap' and 'outputStyle' options. This extra context justifies a score above baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'SCSS / SASS to CSS Compiler' and lists key features like resolving variables, nesting, mixins, partials, and output styles. It explicitly distinguishes from siblings webdev_css_minifier and webdev_code_formatter, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use guidance: 'Use this to turn a preprocessor stylesheet into deliverable CSS; use webdev_css_minifier instead when the input is already plain CSS you only want shrunk, or webdev_code_formatter to pretty-print CSS/HTML/JS.' It also notes that remote @imports are disabled, giving clear context for appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnly, non-destructive, idempotent), description adds that it runs locally, contacts no external service, is rate-limited, and details output flags like isBot, botType, etc. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
4-5 sentences, each adding unique value. Front-loaded with purpose, then behavior, then output. No superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given single parameter and complex output, description adequately explains both input constraints (empty returns 400) and output structure (browser, OS, bot flags). Output schema exists, so not required to list every field, but description covers categories.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema already covers userAgent with description and examples. Description adds context that it parses the value in the request body, not the caller's header, but this is a clarification on usage rather than parameter semantics. Still, it's helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it parses a user-agent string into structured browser/engine/OS/device/CPU/feature data and checks for bots. Distinguishes itself from sibling network_request_headers by noting it does not read the caller's own header.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly explains when to use (when supplying a UA string) and when not to (do not use to read caller's header), and suggests pairing with network_request_headers. Provides clear alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds that the tool runs locally via Node bridge, is read-only, non-destructive, contacts no external service, and is rate-limited (60 req/min). Also describes error conditions and return value (converted string + per-byte breakdown). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured and each sentence adds unique value: purpose, use case, alternatives, local/rate-limit behavior, error handling, output summary. No unnecessary words. Front-loaded with primary function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters (2 required, many enums), presence of output schema, and complexity of conversions, the description covers all necessary aspects: purpose, usage guidelines, constraints, error handling, and behavioral properties. Output schema presence reduces need to detail return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions for all 4 parameters. Description adds meaning: explains space/newline separator, ASCII vs UTF-8 handling, and clarifies that invalid inputs cause errors. Goes beyond schema by describing usage context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool converts between text and space/newline-separated octal byte values. It explicitly distinguishes from sibling tools by naming alternatives (conversion_number_base, encoding_decoding_hex_ascii, etc.) and specifying scenarios for use (C/assembly octal escapes, Unix dumps).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance on when to use this tool (octal-specific tasks) and when to use alternatives (general radix math, hexadecimal, binary, string parsing). Lists several sibling tools with clear differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already denote read-only and idempotent. The description adds rate-limit (60 req/min), offline execution, and details how parity computation works, enhancing transparency without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured, starting with purpose, then modes, limitations, alternatives, and output. Every sentence adds value; no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, modes, limitations, alternatives, operational context (read-only, offline, rate-limited), and output details. With output schema present, the description is complete and self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description provides additional context: constraints (e.g., input length for check mode), purpose of modes and parity types, and examples. This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes or verifies a parity bit, and distinguishes itself from related tools like conversion_hamming_code and conversion_gray_code by noting it is for detection only, not correction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use (for error detection) and when not (for correction), and suggests alternatives. It also explains the two modes (add/check) and the available parity schemes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds context beyond annotations: runs locally, read-only, non-destructive, contacts no external service, rate-limited (5 req/min for anonymous callers). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences covering purpose, usage, behavior, and return values. Front-loaded with key information, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for a PBKDF2 verification tool: explains what it does, how it works, what it returns (match status, parsed parameters, strength analysis), and has output schema for return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have detailed descriptions and examples in the schema. The description explains the hash format and that no separate fields are needed, adding meaning beyond the schema which has 100% coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a 'PBKDF2 Hash Verifier' and explains that it checks if a plaintext password matches an existing PBKDF2 hash, distinguishing it from the sibling tool crypto_pbkdf2 which generates new hashes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Use this to verify a candidate password; use crypto_pbkdf2 instead to generate a new hash,' providing clear when-to-use and when-not-to-use with an alternative tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond annotations (readOnlyHint, idempotentHint), the description adds concrete operational details: local execution, no external service contact, rate limiting (30 req/min), and return structure. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence earns its place. The description is compact but covers purpose, alternatives, behavioral constraints, and return structure. Front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given full schema coverage, rich annotations, and presence of output schema, the description provides all necessary context: purpose, when to use, behavior, parameter semantics, and output details. Nothing missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds significant value by explaining UTF-8 encoding, the empty string example, algorithm variant enum details, and the return format behavior (all formats always included). This goes beyond schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes RIPEMD message digests for a UTF-8 string and returns per-variant results. It explicitly differentiates from siblings by directing users to crypto_hash for MD5/SHA and crypto_sha3 for SHA-3/Keccak.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit guidance on when to use this tool versus alternatives, including specific references to other tools for different hash families. It also notes the Bitcoin use case for RIPEMD-160, helping the agent decide relevance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes behavioral traits beyond annotations: 'Runs locally, read-only, non-destructive, offline, and rate-limited. Returns the transformed text plus a rotation info note and a character-class breakdown of the input.' No contradiction with annotations (readOnlyHint=true, destructiveHint=false).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with core definition, every sentence adds value, no redundancy. Length is appropriate given the complexity of the tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity, rich schema (100% coverage), and output schema, the description covers purpose, usage, behavior, parameter specifics, and return details. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds meaning beyond the schema: explains special behavior for rotation 13 and 47 (symmetric, operation ignored), that other rotations shift ASCII 32-126, and that decode reverses encode. Schema already has descriptions but description provides crucial context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'ROT Cipher (Configurable Rotation, Encode and Decode)' with specific verb 'shift text' and resource 'ROT rotation'. Distinguishes from siblings by explicitly naming encoding_decoding_rot13 and encoding_decoding_caesar, stating when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'Use this configurable variant when you need an arbitrary shift; use the fixed encoding_decoding_rot13 for only ROT13/ROT47, or encoding_decoding_caesar for a 1-25 letter-only Caesar shift.' Also provides contextual purpose: 'for puzzles, CTFs, and obfuscation, not encryption.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds beyond annotations: 'pure local string transformation, read-only, non-destructive, contacts no external service, rate-limited (60 requests/minute)'. This complements readOnlyHint and idempotentHint. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences: purpose, encoding details, usage/behavioral info. No redundancy, well-structured, and front-loaded with main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given simple schema (2 params, 1 required), output schema present, description covers all essential aspects: operation, use cases, alternatives, rate limiting, error states, and return fields.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions and examples. Description adds operational details (encoding scheme, error handling) and clarifies the operation parameter's direction, providing value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool percent-encodes/decodes text using encodeURIComponent semantics, lists use cases (query parameters, path segments, form data), and distinguishes from siblings like encoding_decoding_html_entities and encoding_punycode.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (for URL encoding/decoding) and when to use alternatives (HTML entities for HTML markup, punycode for international domains). Also mentions rate limit and error handling for malformed sequences.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Goes beyond annotations by specifying local execution, non-destructiveness, no external service contact, rate limits, and return metadata. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured and concise: starts with name and purpose, then context, usage guidance, behavioral notes. No redundant or missing information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, nested options, and output schema, the description covers purpose, usage, behavior, and limitations completely. Output schema existing reduces need for return value explanation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds meaning by explaining the alphabet, envelope, and effects of options like includeHeaders and strictMode, as well as the rationale for the format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it is an XXEncode/XXDecode binary-to-text converter, describes encoding and decoding, and distinguishes from siblings like uuencode, binhex, and base64.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when to use this tool versus alternatives, including specific sibling names and contexts (EBCDIC, mail gateways, Macintosh files, web/MIME).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable context beyond annotations: 'Runs locally on the values you provide: read-only, non-destructive, contacts no external service, and is rate-limited (60 requests/minute for anonymous callers).' Annotations already declared readOnlyHint=true, destructiveHint=false, idempotentHint=true, but the description enriches this with specificity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is densely packed with useful information yet remains concise. It front-loads the core function, then details operations, usage guidelines, and returned data. Every sentence earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, nested objects, three operations, and an output schema), the description covers all necessary details: operation variants, unit system handling, expected inputs for each mode, and an overview of the return values (BMI, category, interpretation, healthy weight range). The presence of an output schema doesn't require further description of return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning by explaining each parameter's role in different operations (e.g., 'Required for compute', 'Required only when operation is target-weight'). It clarifies that 'height' can be inches or an object with feet/inches, and describes the a/b objects for compare.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes BMI from height and weight in metric or imperial units, returns WHO category and healthy weight range, and lists three operations (compute, target-weight, compare). It differentiates from siblings by specifically mentioning when to use math_unit_converter or math_percentage_calculator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says when to use this tool for body-composition math and provides clear alternatives ('use math_unit_converter for plain length or mass unit conversion, or math_percentage_calculator for generic percentages'). Also notes it runs locally, is read-only, non-destructive, and rate-limited.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context beyond the annotations, stating it is 'read-only, non-destructive, deterministic, contacts no external service, and is rate-limited.' These details align with and supplement the annotation hints, providing full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three sentences: first explaining core conversions, second specifying return values, third giving usage guidance and behavioral notes. It is front-loaded with the core purpose and every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 10 parameters, 100% schema coverage, and presence of an output schema, the description provides sufficient context by explaining the two operations and their outputs. It is complete enough for an agent to understand the tool's capabilities.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage, but the description adds value by summarizing the return values for each operation: 'Returns the converted value (convertConsumption) or litres needed plus total cost in the price's native currency (tripCost).' This helps the agent understand what to expect without reading the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool as a fuel consumption calculator with two specific operations: convertConsumption and tripCost. It distinguishes itself from sibling tools like math_unit_converter and math_running_pace_converter, making its purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly provides context for when to use this tool versus alternatives, stating 'Use this for fuel-economy and trip-cost math; use math_unit_converter instead for general length / volume / speed unit conversion, and math_running_pace_converter for pace and speed.' This gives clear guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, and idempotentHint. The description reinforces these with specifics: 'Pure deterministic compute: read-only, non-destructive, contacts no external service, idempotent, offline-capable, and rate-limited (60 requests/minute for anonymous callers).' It also notes error handling for invalid inputs, adding value beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear top sentence, a compact list of operations, usage guidelines, behavioral notes, and return shape. Every sentence adds information without redundancy, making it efficient for an AI agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 operations with conditional required parameters), the description provides complete guidance: operation definitions, parameter requirements, behavioral traits, error handling, return structure, and sibling differentiation. The presence of an output schema reduces the need to detail return fields, but the description still sketches the result object adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides descriptions for all 7 parameters (100% coverage). The description enriches this by explaining the relationship between the 'operation' enum and required parameters for each operation, e.g., 'whatPercent needs value+total'. This adds critical semantic context for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The title 'Multi-Mode Percentage Calculator' and the description clearly state it performs eight specific percentage operations on plain numbers. It distinguishes itself from sibling tools like math_compound_interest_calculator, math_ratio_calculator, and math_statistics_calculator by explicitly naming them and their use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises when to use alternative tools: 'Use math_compound_interest_calculator for interest growth over time, math_ratio_calculator for proportions and splits, or math_statistics_calculator for mean/median/correlation over a dataset.' This provides clear context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. The description adds details: deterministic, read-only, non-destructive, no external service, rate-limited, and the algorithms used (trial division, Miller-Rabin). No contradiction; adds value beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (about 10 sentences) and well-structured: summary sentence, operation details, usage guidelines, computational properties, and data convention. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (three operations, output schema exists), the description covers all necessary aspects: operation modes, input constraints, algorithm behavior, rate limits, and data format. It is complete enough for an agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, but the description adds significant meaning: it explains the three operations, the check operation's output (primality, factorization, surrounding primes, algorithm), range constraints (max span 100000, up to 10^8), and data type guidance (string for >2^53). This goes beyond the schema's brief descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: prime checking, factorization, range sieve, next/prev prime. It distinguishes itself from sibling tools like math_gcd_lcm_calculator, math_factorial_calculator, and math_fibonacci_generator by specifying alternative use cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (primality, factorization, prime enumeration) and when to use alternatives (gcd/lcm, factorial, Fibonacci). It also includes important usage details like passing large integers as strings and rate limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses behavioral traits beyond annotations: 'Pure local parse: read-only, non-destructive, deterministic, contacts no external service, rate-limited (5 requests/minute for anonymous callers).' This adds context about determinism, no external service calls, and rate limiting, which are not covered by the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized for the tool's complexity. It starts with a clear one-line summary, then expands on functionality, sibling distinctions, behavioral traits, and input constraints. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity, the description covers all necessary aspects: purpose, input format and constraints, behavioral properties (read-only, deterministic, rate-limited), privacy features, and explicit sibling comparisons. The presence of an output schema and annotations complements the description, making it fully informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no JSON parameters (0 params), and the schema is empty with 100% coverage. The description adds meaning by detailing the file input constraints: multipart/form-data, field 'image', max 10 MB, and supported image formats (JPEG, TIFF, PNG). This compensates for the lack of schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool as an 'EXIF Metadata Viewer' and enumerates specific functions: extracting EXIF, GPS, camera metadata, flagging privacy-sensitive content, and providing scrubbing recommendations. It explicitly distinguishes from sibling tools by naming alternatives like osint_email_headers, webdev_base64_image_encoder, and file_mime_type_lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool (forensics/OSINT and pre-share privacy check) and when not to, naming specific alternative tools and their purposes. It also notes that EXIF is only present in JPEG/TIFF, setting expectations for input formats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true) are reinforced with explicit behavioral context: 'Runs locally … read-only, non-destructive, contacts no external service, and is rate-limited'. It also describes return values (serialized header, normalized directives, HTML meta-tag, severity-ranked warnings), adding significant transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise yet comprehensive, starting with the core purpose, then detailing operations, clarifying what it doesn't do, providing sibling differentiation, and adding behavioral notes. Every sentence serves a purpose without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a multi-operation tool with parameters, annotations, and an output schema, the description covers all critical aspects: all three operations with their input requirements, behavioral constraints (read-only, rate-limited), output details (header value, directives, HTML meta-tag, warnings), and links to related tools. There are no gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter having a description. The description goes further by explaining operation modes and their parameter dependencies ('build serializes... requires policy; parse splits... requires value; analyze audits... requires value or policy'). It also elaborates on the policy structure (directives map, arrays of tokens, boolean directives), exceeding the schema's brief descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Content-Security-Policy Builder, Parser, and Analyzer' and immediately explains the three modes (build, parse, analyze). It distinguishes from sibling tools by naming alternatives for full Apache/Nginx configs (linux_web_server_config_generator, security_htaccess_generator, security_openssl_command_builder), effectively differentiating the tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells when to use this tool ('Use it to author or review a CSP') and when to use alternatives ('for full Apache or Nginx config files use...'). It also states what the tool does not do ('it does not deploy, send, or apply the policy'), providing clear guardrails.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark readOnlyHint=true and destructiveHint=false; description reinforces non-execution, no filesystem access, and local read-only operation. It adds context about warnings and explanations, consistent with annotations. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the purpose and key exclusions. Uses bullet-style lists for operations and guidelines, making it scannable. Every sentence adds value—no filler, no repetition of schema info.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (12 operations, nested fields, multiple parameter schemas), the description covers all behavioral aspects: generation vs. execution, file side-effects, parameter defaults, and alternative tools. No gaps remain even without output schema in the input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and description enriches each parameter with defaults, examples (e.g., algorithm defaults to rsa-4096, digest to sha256), and per-category field lists. The description adds significant meaning beyond the enum names and property types.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool builds copy-paste-ready openssl commands from form fields, lists 12 operations, and contrasts with sibling tools like linux_command_builder and security_htaccess_generator. The verb 'build' plus 'openssl command line' is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (build openssl commands) and when not to (never executes, opens sockets, or touches filesystem). Provides alternative tools for Linux CLI commands and Apache rules, guiding the agent away from misuse.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses outbound HTTP/HTTPS connections, live network state, variance between calls, rate limiting details, and SSE frame types (start, result, error, complete). Adds significant context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Structured with title, purpose, behavior, sibling differentiation, rate limits, and SSE format. Every sentence is informative and efficient, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all essential aspects: purpose, usage guidelines, behavior, parameter details, rate limits, and output format (SSE types). Complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description explains the proxies parameter format (protocol://user:pass@host:port, defaults, skipping rules) and notes that options like concurrency and retryAttempts are accepted but not applied. Adds meaning over the 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it tests proxy servers with a streaming SSE response, specifies the verb 'tests' and the resource 'list of proxy servers', and explicitly distinguishes from siblings like security_proxy_test and security_proxy_test_single.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: use security_proxy_parse for normalizing input, use security_proxy_test for batch JSON, use this streaming variant for incremental progress. Also mentions rate limits and CAPTCHA constraints, aiding in deciding when to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, and idempotentHint. The description adds further behavioral details: runs locally, read-only, non-destructive, no external service calls, idempotent, rate-limited (30/60 req/min), and describes return values (serialized XML, entry count, byte size, warnings). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise yet thorough, using bullet-like structure within paragraphs. Each sentence adds meaningful information without redundancy. It is front-loaded with the core purpose and then covers behavioral details, usage guidelines, and return values efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the parameter complexity (4 params, nested objects) and the presence of an output schema, the description still fully explains inputs, operations, edge cases (warnings for invalid values, limits), and the nature of the tool (non-destructive, idempotent). It is complete without relying solely on schema or annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds valuable context beyond the schema. It explains the 'operation' enum values, that 'urls' entries must have a 'loc' field, that 'alternates' triggers the xhtml namespace, and describes warnings for invalid dates, changefreq, priority, and protocol limits.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Sitemap Generator (Build XML Sitemap From URL List)' and explains two operations: generate and generateIndex. It explicitly says what the tool does not do (crawl, fetch, discover URLs), distinguishing it from related tools like seo_robots_txt_generator and seo_hreflang_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool vs alternatives: 'Use seo_robots_txt_generator to control crawler access and point at the finished sitemap, or seo_hreflang_generator when you only need standalone alternate-language tags.' It also states that the tool does not crawl or discover URLs, only formats provided entries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds that it runs locally, is non-destructive, contacts no external service, and is rate-limited. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise yet thorough, front-loads core functionality, lists metrics, then gives usage guidelines and behavioral notes. Every sentence is valuable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with output schema present, the description covers all essential aspects: what it counts, usage guidance, behavior, and return structure. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; the description adds meaning about empty strings yielding zero counts, Unicode code-point based counting, and how lines, sentences, paragraphs are split.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it counts characters, words, lines, sentences, paragraphs, averages, reading time, and top characters. It distinguishes itself by naming alternatives like text_text_statistics and text_line_counter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool (quick plain tally) and when to use alternatives (text_text_statistics for richer linguistic profile, text_line_counter for just line counts).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent; description adds pure local compute, offline, rate limits, and output details. No contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with purpose, efficient sentences, no redundancy. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, behavior, parameters, and output; fully adequate for an AI agent given the complexity and rich annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions; description adds meaningful context like diffType views and normalization options, enhancing understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it compares two text inputs line-by-line using LCS algorithm, and distinguishes from sibling tools file_comparer and text_find_replace.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool vs. file_comparer (for files) and text_find_replace (for substitution), with clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds crucial behavioral context: 'Pure local compute: read-only, non-destructive, idempotent (except sortType=random), offline, and rate-limited (60 requests/min)' and describes output format with statistics and options.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Every sentence contributes: purpose, usage guidance, behavioral notes, output summary, rate limiting. Front-loaded with primary function, no redundancy, appropriate length for complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present, description appropriately omits return value details but still mentions output content. Covers all aspects: purpose, when to use, behavioral nuances, parameter semantics, and constraints (rate limit, offline). Fully adequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage but description adds significant value by explaining each sortType option (e.g., 'alphabetical (locale-aware)', 'numeric (parses leading number)') and noting that caseSensitive affects both sorting and deduplication, enriching parameter understanding beyond enum labels.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Sort lines of a text block' with specific verb and resource. Lists sort type options and differentiates from sibling tools text_duplicate_line_remover and text_randomizer, establishing its unique purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this to order lines' and provides alternative tools for deduplication (text_duplicate_line_remover) and richer shuffling (text_randomizer), giving clear guidance on when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate read-only, non-destructive, idempotent. Description adds local execution, rate limiting, and reinforces non-destructive nature. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise (4 sentences) and front-loaded with purpose and key details. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complex parameters and output schema existence, description covers return values (CSS declaration, preview, settings, examples) and usage context thoroughly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed parameter descriptions. Description adds context like required length, defaults, and ignored fields, enhancing understanding beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the tool generates CSS gradients from color stops, returning background declarations and snippets. It differentiates from siblings like webdev_css_filter_generator and webdev_color_palette.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states when to use alternatives: filter effects (webdev_css_filter_generator) and color picking (webdev_color_palette/webdev_hex_color), and that it runs locally without external services.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses regex-based operation, local execution via Node bridge, read-only and non-destructive nature, and rate limits (60 req/min). Adds context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, well-structured paragraph front-loading core purpose; every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, behavioral traits, parameter semantics, and output (minified CSS with sizes, savings, ratio). Complete for this tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Summarizes each boolean toggle's effect (e.g., 'compressColors shortens 6-digit hex to 3 digits') and clarifies css parameter must not be blank. Adds meaning beyond 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'CSS Minifier' and specifies actions: stripping comments, collapsing whitespace, and optional optimizations. Distinguishes from siblings like webdev_css_beautifier and webdev_sass_compiler.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly describes when to use (minifying CSS) and when not to (expanding CSS, compiling SCSS, minifying HTML/JS), naming specific sibling tools as alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, idempotentHint, openWorldHint. Description adds: 'pure local compute, read-only, non-destructive, contacts no external service, rate-limited (30 req/min)'. This enriches transparency beyond annotations without contradiction.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is well-structured: starts with main purpose, then usage guidance, then behavioral notes. Every sentence adds value; no fluff. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given single parameter, rich annotations, and output schema (mentioned), description covers input, behavior, constraints, rate limiting, and return values (normalized spec, version, endpoint count, schemas map). Highly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed parameter description. Description adds parsing details (JSON first then simple YAML) and validation (must contain openapi/swagger and info). This provides significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'OpenAPI/Swagger Spec Parser And Summarizer' and explains what it does: parse spec and return version, operation count, and schemas. It distinguishes from siblings like format_json_schema_generator and format_json.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use this tool ('inspect or summarize an API contract you have as text') and when to use alternatives ('use format_json_schema_generator instead to derive a JSON Schema from sample data, or format_json to pretty-print generic JSON'). Also clarifies does not fetch URLs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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