ZapifyAPI MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a distinct resource and action, with no two tools overlapping in function. Even the multiple convert_* tools target different domains (currency, units, timezone, image format, color).
Naming Consistency4/5
Most tools follow a verb_noun snake_case pattern (convert_currency, generate_password, validate_email), but a few break the pattern (csv_to_json, markdown_to_html, ip_geolocation, http_headers, base64_encode_decode). The deviations are minor and the set remains readable.
Tool Count2/5
With 32 tools, this server far exceeds the typical 3-15 tool range for MCP servers. The large number is overwhelming and suggests a lack of focus, though each tool is individually useful.
Completeness3/5
The tools span a wide range of utilities but are shallow within each category. For example, image processing is limited to WebP conversion and watermarking, and network tools lack ping or HTTP request functionality. There are notable gaps for a general-purpose utility API.
Average 3.4/5 across 32 of 32 tools scored. Lowest: 2.5/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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.
Add a glama.json file to provide metadata about your server.
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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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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits but only states 'secure random passwords.' It does not explain what the function returns, whether it is deterministic, or whether it relies on a secure random source. This leaves significant uncertainty about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief, but this is under-specification rather than appropriate conciseness. For a tool with six configurable parameters, a single sentence is insufficient to be useful, and it does not earn its place by conveying necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's six parameters, lack of annotations, and missing output schema, the description is far from complete. It provides no information about the output format, parameter semantics, or any behavioral nuances, making the tool effectively impossible to use correctly without additional documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has six parameters with zero description coverage, and the description does not mention any of them. Nothing beyond the parameter names (count, length, numbers, etc.) is provided, so the description fails to add any meaning to the 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 'Generate secure random passwords' clearly states the tool's function with a specific verb and resource. It distinguishes itself from sibling tools like generate_hash and generate_uuid by explicitly targeting passwords.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. No context is given about appropriate use cases, prerequisites, or scenarios where a different tool might be preferable. The description offers no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it only states the action without revealing how errors are handled, what 'format' outputs (e.g., indentation, minification), or any side effects. The presence of an `indent` parameter is not mentioned, so the tool's behavior regarding formatting remains opaque.
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 short sentence with no wasted words, making it concise and front-loaded. However, it is so brief that it omits critical details, so while structure is good, the content could be more descriptive without hurting conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two parameters and no output schema or annotations, the description should at least clarify what 'format' does, mention the `indent` parameter, and describe behavior for invalid JSON. The current text leaves these gaps, making it incomplete for an agent to invoke correctly without external assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 50% coverage (only 'json' is described, not 'indent'). The tool description adds no clarity for the 'indent' parameter—it only reinforces 'JSON string.' Since schema coverage is low, the description should compensate by explaining the second parameter, but it does not.
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 states a specific verb+resource: 'Validate and format a JSON string.' It clearly indicates the tool processes JSON input and suggests both validation and formatting. However, 'format' is somewhat ambiguous (pretty-print vs minify), and it doesn't distinguish from similar tools like csv_to_json, though the resource is explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any sibling tools, exclusions, or prerequisites. The lack of any context leaves the agent to infer applicability purely from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only states the basic purpose and does not explain the optional 'time' parameter's default behavior, timezone format expectations, error handling, or return value.
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, clear sentence with no redundancy, front-loading the purpose efficiently. While it is brief, it is not empty or tautological; however, the extreme brevity may under-serve a tool with three parameters and no annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description should compensate by explaining the return value, optional parameter behavior, and timezone formatting. It does none of these, leaving important gaps for reliable usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33% (only 'time' has a description). The description adds no meaning for 'from_tz' or 'to_tz', nor does it clarify the optional 'time' parameter or its default value, leaving significant semantic gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 action (convert) and the resource (time) with the scope (between timezones). This uniquely identifies the tool among siblings like convert_currency and convert_units, satisfying 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no exclusions, and no mention of specific use cases or prerequisites. The only context is the name and sibling tools, which is implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description holds the full burden of behavioral disclosure. It only states the core action and does not describe the output format, supported languages, input length limits, or whether it returns a label, score, or both. This leaves significant ambiguity about the tool's 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?
The description is a single sentence with no redundant words. It is appropriately concise for a simple tool and includes the essential information about purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description should explain what the tool returns. It does not, so the agent cannot know the structure of the result. This is a clear gap that leaves the description incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema contains a single 'text' parameter with no description and 0% schema coverage. The description references 'text' but provides no additional semantic detail such as examples, encoding, length, or domain. It does not compensate for the lack of parameter 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 function: detecting positive/negative/neutral sentiment in text. It uses a specific verb and resource, and while it doesn't explicitly differentiate from siblings, there are no other sentiment analysis tools among the siblings, so 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There is no mention of exclusions, prerequisites, or contextual examples. It simply states what the tool does without addressing usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description only states functionality. It adds category support but does not disclose accepted unit formats, precision, or return value behavior, leaving significant gaps.
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 concise sentence that is front-loaded and contains no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple converter with no output schema and no annotations, the description provides minimal context. It doesn't specify unit string formats, supported units per category, or error handling, making it insufficient for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the 'value', 'from', or 'to' parameters or provide unit format examples, failing to compensate for the schema's lack of 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?
Clear verb 'convert' with resource 'units' and explicitly lists supported categories (length, weight, temperature), distinguishing it from sibling converters like convert_currency and convert_timezone.
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 implies usage for length/weight/temperature conversions but does not explicitly state when to use or mention alternatives/exclusions. No guidance for non-supported conversion types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states the basic action, omitting information about redirect following, response status handling, rate limits, or output 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?
The description is a single concise sentence with no unnecessary words. It is well-structured and immediately understandable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema and no annotations, the description is insufficient. It does not explain what the returned headers include or how errors are handled, leaving the agent to infer critical details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, and the description adds minimal meaning beyond the parameter name 'url' by saying 'for a URL.' It does not specify URL format requirements (e.g., absolute vs. relative, supported protocols).
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 resource ('HTTP response headers') clearly indicating what the tool does. It is distinct from sibling tools like extract_url_metadata, which focuses on broader metadata extraction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of scenarios where fetching headers is appropriate, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates a read operation ('Get') but does not disclose the return format, potential for IPv6 support, rate limits, or any prerequisites. The minimal description leaves the agent guessing about the tool's 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?
The description is a single clear sentence with no extraneous content, making it highly concise and front-loaded. Every word 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?
For a simple tool with one fully documented parameter and no output schema, the description gives the essential purpose but lacks detail about the nature of the geographic location (e.g., country, city, coordinates). Given the minimal schema and absence of annotations, the description could provide more context to be fully actionable.
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 single parameter 'target_ip' is described as 'IP address to look up.' The tool description adds only that the result is a geographic location, which is somewhat redundant with the tool name. No additional parameter semantics beyond the 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 uses the specific verb 'Get' and identifies the resource as 'geographic location of an IP address,' clearly stating what the tool does. However, it does not distinguish itself from sibling tools like dns_lookup, whois_lookup, or get_country_info, which could overlap.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. It merely states the action, leaving usage entirely implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions language support (50+ languages) but does not disclose behavior such as auto-detection, error handling, rate limits, or whether the operation is safe and reversible. This is minimal and insufficient for a tool with no annotation safety signals.
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 and every word earns its place. It is front-loaded with the core purpose and adds a brief capability claim. There is zero fluff or redundancy, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and no annotations, the description is too sparse. It does not explain expected input formats, output structure, or any constraints. The agent would need to infer too much, making the tool risky to invoke without additional information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes 'to' and 'from' but leaves 'text' undocumented (67% coverage). The description adds no parameter meaning beyond the schema; it does not clarify that 'text' is the content to translate or explain language code formats. It fails to compensate for the underscore-documented 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 the tool's function: 'Translate text between languages.' The verb 'translate' and resource 'text' are specific, and the phrase 'between languages' adds scope. It distinguishes from all sibling tools, none of which are translation-related.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There are no mentions of exclusions, preferred use cases, or distinctions from other text-processing tools like analyze_sentiment or extract_keywords. The agent is left without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states what is checked but does not disclose network dependency, potential timeouts, return format, or error handling. For a tool that likely makes external requests, this is insufficient.
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, front-loaded sentence with no filler. Every word adds meaning, making it highly concise and well-structured.
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?
For a simple one-parameter tool, the description minimally conveys what the tool does and what aspects it checks. However, without an output schema or annotations, it lacks details on return value structure, SSL/TLS edge cases, and external network behavior, making it only minimally viable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema lists a single 'domain' parameter with no description. The tool description adds only 'for a domain', which does not clarify expected format (e.g., bare domain vs URL, whether protocols are accepted) or any validation rules. With 0% schema coverage, the description does not compensate adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 ('Check') with a clear resource ('SSL certificate') and lists the aspects checked (validity, issuer, expiry). This distinguishes it from sibling tools like dns_lookup and whois_lookup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description does not mention any exclusions, prerequisites, or contrasting tools that perform similar checks, leaving the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it only states the core function. It does not mention return format, error handling on invalid input, or any limitations, making the tool's behavior partially opaque.
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 sentence that is appropriately sized and front-loaded. Every word contributes meaning, with no filler or redundancy.
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 tool is simple (one parameter, no output schema), so the description provides a basic understanding of purpose and likely output fields. However, it lacks details about return structure, invalid input handling, or any special behaviors, leaving some gaps for a fully complete picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter with no description, and the description adds no additional semantic detail beyond what the parameter name 'user_agent' already implies. There is no example, format specification, or clarification of edge cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 ('Parse'), a clear resource ('User-Agent string'), and states the resulting outputs (browser, OS, device info). This clearly distinguishes the tool from all siblings, none of which handle user-agent parsing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives, nor are any prerequisites or exclusions mentioned. The intended usage is only implied by the description, not stated directly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full behavioral disclosure. It only states 'return matches' without specifying the regex flavor, flag handling, output format, or error behavior for invalid patterns. This lacks the detail needed for an agent to understand side effects or special cases.
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, concise sentence with no filler words. It is well-structured and front-loaded. However, it is almost too minimal; a brief mention of flags or return format could be included without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and 0% schema description coverage, the description alone must be complete. It is not: it fails to explain the 'flags' parameter, the structure of matches, or behavior with invalid regex. This is inadequate for a tool with three parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, so the description must compensate. It explains the role of 'pattern' and 'text' implicitly, but does not mention the 'flags' parameter at all, nor does it specify accepted flag formats or defaults. The description adds minimal meaning over the raw parameter names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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: 'Test a regex pattern against text and return matches.' It uses a specific verb and resource, and the outcome is clear. It is distinct from all sibling tools, none of which involve regex testing.
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 implies usage for testing regex patterns, but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or context. Since there is no sibling regex tool, an alternative reference is not critical, but more guidance on usage context (e.g., testing one pattern at a time) would improve it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states a simple read operation without disclosing behavioral traits such as network dependency, rate limits, error scenarios, or return format. With no annotations, the description carries the full burden but provides minimal 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?
A single sentence, no filler, front-loads the purpose. Very concise and well-structured.
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 is sufficient for basic understanding but lacks usage guidance and behavioral details. Given the absence of annotations and output schema, it could be more thorough, yet the simplicity of the tool (one parameter, read-only) makes it minimally viable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema parameter 'domain' has no description (coverage 0%), and the description's 'for a domain' merely restates the parameter name. It does not specify required format, examples, or constraints (e.g., whether to include 'https://' or subdomains).
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 the verb 'Get' with resource 'WHOIS registration data for a domain', clearly specifying the tool's function. It distinguishes from sibling tools like dns_lookup and ip_geolocation by focusing on WHOIS registration data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as dns_lookup or extract_url_metadata. There is no mention of prerequisites, typical use cases, or when to avoid this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations and no output schema, the description carries the full burden of disclosing behavior. It lacks details on whether the tool returns a censored string, a boolean, or both, and does not mention language support, error handling, or side effects. This is a significant gap for a function.
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, front-loaded sentence with no redundancy or unnecessary words. Every word contributes to the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (one parameter, no output schema), but the description still leaves essential unknowns: what the return value looks like, whether it modifies input, and how it handles edge cases. The description is too sparse for an agent to use it confidently without further explanation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. However, it only says 'text' without adding any additional meaning about format, encoding, length limits, or expected content. The parameter name and type in the schema already convey that it takes a string of text.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 'detect' and 'censor' with resource 'profanity in text', clearly stating what the tool does. It is distinct from all sibling tools (e.g., translate_text, analyze_sentiment, validate_email), leaving no ambiguity about its function.
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 implies usage for filtering or checking profanity but provides no explicit guidance on when to prefer this tool over alternatives or any exclusions. Since no sibling tool covers profanity, the context is clear but still only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full disclosure burden. It mentions 'real-time exchange rates' but does not clarify whether the operation is read-only, how errors are handled, or what data source is used. This is a notable gap for a simple converter.
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 sentence of six words, with no redundancy. It front-loads the purpose and is appropriately sized for a simple conversion tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and low parameter coverage, the description is too sparse to fully guide an agent. It does not state what the result is (e.g., the converted amount) or how the 'amount' parameter is interpreted, leaving important context missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is only 33% (only 'from' is described). The description does not help explain the 'to' or 'amount' parameters, their formats, or how they relate to the conversion. It adds minimal 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 uses a specific verb 'convert' with the resource 'currencies', clearly distinguishing it from sibling tools like convert_units and convert_timezone. The phrase 'real-time exchange rates' adds a specific and accurate scope.
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 implies the tool is for currency conversion, but it does not explicitly state when to use it over alternatives or provide exclusions. The context of sibling tools makes the intended use somewhat clear, but the description itself offers no direct guidance.
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 present, so the description carries the burden. It discloses a behavioral trait ('relevance scoring'), which adds value, but it does not explain sorting, return format, or language behavior, leaving meaningful gaps.
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?
A single sentence with no filler, immediately stating the action and key feature. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema or annotations, and the description doesn't explain return structure, ordering, or edge cases. For a tool that returns scored keywords, this leaves the agent guessing about what it will receive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50% (max has a description, text does not), and the description does not compensate. It adds no parameter-level meaning, relying entirely on the schema's minimal info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 uses the specific verb 'extract' with resource 'keywords from text', and adds 'relevance scoring' as a distinctive feature. This clearly separates it from sibling tools like extract_url_metadata or analyze_sentiment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any exclusions or when-not-to-use conditions. The agent is left to infer usage from the name and siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not explain the behavior of the 'all' algorithm option (e.g., whether it returns a single string or a collection of hashes) or the output format (e.g., hex encoding). This leaves ambiguity for non-trivial usage.
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, front-loaded sentence that directly states the action and supported algorithms. It contains no filler, repetition, or unnecessary details, making it highly concise and effective.
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?
For a simple hash generation tool, the description covers the core purpose. However, it omits details about the 'all' algorithm option, which is a notable feature, and does not specify the return format. Given the lack of annotations and output schema, the description is adequate for typical cases but incomplete for edge scenarios.
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 schema documents the 'algorithm' parameter with allowed values, and the description reinforces these by listing MD5/SHA1/SHA256/SHA512. The 'text' parameter is indirectly described as 'hash of text', but the description adds no explanation of the 'all' option's effect. With 50% schema coverage, the description provides some value but does not fully compensate for the gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 'Generate' and clearly identifies the resource as 'hash of text' with explicit algorithm names (MD5/SHA1/SHA256/SHA512). This distinguishes it from sibling tools like generate_password and generate_uuid, 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It simply states what the tool does, without any contextual cues, prerequisites, or exclusions. There is no mention of use cases like verifying data integrity or comparing hashes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden of behavioral disclosure. It discloses the 20-port limit but omits other relevant behaviors such as timeout handling, scan methodology (e.g., TCP connect vs SYN), or potential intrusiveness. The description does not contradict any annotations since none exist.
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, front-loaded sentence that conveys the core function and a key constraint without wasted words. Every element earns its place, making it highly concise and efficiently structured.
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?
With no output schema and no annotations, the description leaves out return value format, error handling, and scan specifics. However, for a relatively simple tool with only two parameters, this minimal description is barely adequate, though it could do more to clarify outcomes.
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 schema has 50% coverage (ports has a description, host does not). The description adds the 'up to 20 ports' constraint for the ports parameter and clarifies that the target is a host, but it does not elaborate on host format or what 'common ports' means. This is a moderate addition over 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 action ('Scan') and object ('ports on a host'), making the tool's purpose unambiguous. It distinguishes itself from sibling network tools like dns_lookup and whois_lookup by focusing specifically on port scanning. The 'up to 20 ports' limit is an additional useful constraint that does not obscure the core purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like dns_lookup, http_headers, or whois_lookup. It does not mention any prerequisites, such as host reachability or scan type, and only hints at the 20-port limit, which is more a constraint than usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It fails to mention that the tool returns a new watermarked image, any input format limitations, or side effects. The description simply restates the operation without adding 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?
The description is a single sentence with no filler words, front-loading the purpose. It is appropriately compact for the operation it describes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with two parameters and no output schema, the description leaves out the return value format and any constraints like maximum image size. This is a significant gap for an agent to know what to expect, so it is incomplete.
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 thoroughly describes both parameters ('Base64 encoded image' and 'Text to overlay'), so schema coverage is 100%. The description adds no additional parameter information, meeting the baseline of 3 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 'Add a text watermark to an image' uses a specific verb and resource, clearly distinguishing from sibling tools like convert_image_to_webp or generate_qr_code. It immediately clarifies the tool's function.
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?
No explicit guidance is provided on when to use this tool over alternatives. However, the function is self-evident and no sibling tool directly competes, so the usage is implied by the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what information is returned, but does not mention whether it makes a network request, handles missing countries, has rate limits, or any other behavioral traits. This is a significant gap for a tool with no annotation support.
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 sentence that front-loads the primary action ('get country information') and then specifies the key result fields. It is appropriately sized with no wasted words.
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 simple tool with one parameter and no output schema, the description adequately covers what the tool does and what it returns. However, it omits important contextual details such as accepted ISO code formats (e.g., alpha-2 vs alpha-3) and behavior for invalid or unrecognized country names, which would improve 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?
The schema already covers the parameter semantics with a description of 'Country name or ISO code' for the 'country' parameter, giving 100% coverage. The tool description does not add any additional meaning to the parameter beyond what the schema provides, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 'Get' and the resource 'country information', and specifically enumerates the data types covered (capital, population, languages, flag). This is specific enough to distinguish from sibling tools like convert_currency or ip_geolocation, which are clearly different in scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. While the tool name implies a purpose, the description itself does not offer any decision-making context for an AI agent deciding between tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It only states the core function but omits details about input validation, error handling (e.g., invalid Base64), or behavior for edge cases (e.g., empty input). This is insufficient for a tool with no 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, front-loaded sentence that efficiently communicates the tool's purpose with no redundancy. Every word contributes to understanding.
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 tool's simplicity (2 parameters, no output schema, no annotations), the description is adequate but misses important context such as error handling for invalid actions or malformed Base64. It is not complete enough to prevent misuse in edge cases.
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 50% (only 'action' is described). The description adds meaning to 'input' by implying it accepts text for encoding or Base64 for decoding, but does not clarify the exact format of 'action' beyond what the schema already states. The description partially compensates for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 'Encode' and 'decode' with a clear resource ('Base64'), and comprehensively covers both operations. It fully distinguishes itself from sibling tools, as no other tool handles Base64 conversion.
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 implies usage for encoding text to Base64 or decoding Base64 to text, but does not explicitly state when to prefer this tool over alternatives or mention any exclusions. No direct comparison with sibling tools is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions conversion between three formats but gives no details on input validation, return format, or error handling. The schema only lists HEX and RGB, creating ambiguity about HSL support, which reduces 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 a single, front-loaded sentence of just 9 words. It conveys the essential purpose without any filler or redundancy, making it highly concise and well-structured.
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 tool is simple with one parameter, but the description is minimal. It does not clarify the HSL inconsistency with the schema, and with no output schema or annotations, it omits details about return values or behavior on invalid inputs. Adequate but with clear 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% (the single 'color' parameter is described in the schema). The description adds no parameter-specific information beyond what the schema already provides, so the 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 uses the specific verb 'Convert' with a clear resource ('color') and explicitly names the three target formats (HEX, RGB, HSL). This fully distinguishes it from sibling conversion tools like convert_currency or convert_units.
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?
Usage is implied by the clear purpose, but the description does not explicitly state when to choose this tool over alternatives or provide any exclusions. It simply says what it does without contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only specifies the input format (base64 encoded image) but does not disclose output format details, error behavior, or side effects. For a conversion tool, such information is important for safe invocation.
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 extremely concise: two short sentences that directly state the operation and input requirement. No filler or redundancy.
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 tool's simplicity (one parameter, no output schema), the description covers the core input and intent. However, it does not state what the output is (e.g., WebP binary data) or how errors are handled, which would be beneficial for a complete usage 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%, and the description echoes the parameter's purpose ('base64 encoded image data'). The description adds minimal value beyond the schema, 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 states a specific action ('Convert a PNG or JPEG image to WebP format') with a clear resource and target format. It distinguishes this from sibling conversion tools (e.g., currency, units) by explicitly naming image formats.
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?
Usage is implied from the name and description—it is for converting images to WebP. However, there is no explicit guidance on when to prefer this over alternative tools or any exclusions, so it relies on the reader inferring the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full behavioral disclosure responsibility. It only states the function without mentioning return format, side effects, safety (e.g., read-only), or possible errors. This is insufficient for a tool with zero 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, front-loaded sentence with no extraneous words. It is appropriately sized for the tool's simplicity and 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?
For a simple tool with no parameters, the description covers the core purpose, but it lacks details about the return value structure (e.g., plain string vs object) and any error conditions. Given the absence of annotations and output schema, this is a minor gap that could confuse an agent expecting a specific response format.
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 tool has 0 parameters, so parameter semantics are not applicable. Per the rubric, a baseline of 4 applies for 0-parameter tools, and the description adds value by specifying the 'programming' domain of the joke without redundant parameter detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 'Get' and a specific resource 'a random programming joke', which clearly differentiates it from the sibling tool get_random_quote (general quotes vs programming jokes). It is unambiguous and directly states 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like get_random_quote. The description simply states the function without indicating preferred use cases, exclusions, or context (e.g., 'use for programming-related humor').
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It only states the core transformation and does not address edge cases, header handling, delimiter behavior, or error conditions, leaving significant gaps.
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, direct sentence that conveys the essential purpose without waste. Every word contributes to the meaning.
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?
For a simple transformation tool, the description is minimally sufficient, but it lacks crucial context such as input expectations, default delimiter, and output structure details. With no annotations or output schema, this falls short of full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description fails to explain the meaning or usage of the 'delimiter' parameter. While the schema lists types, the description adds no semantic value, requiring the agent to infer delimiter behavior independently.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 'Parse' with a clear resource 'CSV text' and output 'structured JSON'. This is distinct among sibling tools, which focus on other conversions (e.g., convert_currency, base64_encode_decode).
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 implies usage: use when you have CSV text and want structured JSON. No explicit alternatives are mentioned, and none of the sibling tools directly compete, so guidance is clear though not exhaustive.
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 present, so the description carries the burden of behavioral disclosure. It states that the tool generates random v4 UUIDs, which is a clear behavioral fact. However, it omits additional context such as whether the randomness is cryptographically secure or whether the result is a string, though these are somewhat implied by the tool's purpose.
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 sentence, 'Generate random v4 UUIDs.', which is perfectly front-loaded and free of any redundant wording. Every word contributes to the core purpose.
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 simplicity (one optional parameter, no output schema), the description and schema together adequately cover usage. The only minor gap is that the return type is not explicitly stated, but it is strongly implied by 'generate UUIDs'.
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 schema describes the only parameter 'count' with 'How many UUIDs (max 50)', providing 100% coverage. The description adds no extra parameter information, so the baseline of 3 is appropriate since the schema fully documents the 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 uses the specific verb 'Generate' with the resource 'random v4 UUIDs', clearly distinguishing this tool from siblings like generate_password and generate_hash. It explicitly specifies UUID v4, leaving no ambiguity about the output type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as generate_password or generate_hash. There is no mention of use cases, prerequisites, or exclusions, leaving the agent to infer when a UUID is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It lists the extracted fields but does not mention that this involves a network request, how failures are handled, whether redirects are followed, or any access requirements. This is a significant gap for a tool that fetches remote content.
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 short sentence that immediately states the action and target. Every word earns its place, with no filler or redundancy.
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?
For a simple, single-parameter tool, the description is mostly complete: it names the input and the expected outputs. However, with no annotations and no output schema, it lacks important context about failure modes, network behavior, and response format, making it only minimally viable.
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 0% and there is only one parameter, 'url'. The description adds meaning by indicating that the URL is the source from which to extract metadata, but it does not specify accepted formats (e.g., must include http/https) or any validation constraints, leaving room for ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 ('Extract') and names the resource ('URL') along with the precise data returned (title, description, OG tags). This clearly differentiates it from sibling tools like http_headers or extract_keywords.
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 implies the tool is used when you need metadata (title, description, OG tags) from a URL. It provides clear context but does not explicitly mention alternatives or exclusions, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not mention the output format (e.g., image file, base64), whether it's a safe read-only operation, or any constraints. 'Generate' could imply a file creation, but specifics are absent.
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 clear sentence with no extraneous information. It is front-loaded and perfectly sized for a simple one-parameter tool.
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?
For a simple tool with one parameter and no output schema, the description is minimally adequate but lacks crucial details about the return value. Knowing whether the QR code is returned as an image URL, binary data, or another format would be important for trustworthy 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% and the description repeats the 'text or URL' wording. No additional meaning beyond the schema is provided, so the 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 action (generate) and the resource (QR code), with the input specified as text or URL. It is distinct from sibling generation tools like generate_password or generate_uuid.
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 implies when to use the tool (when a QR code is needed) and the input type. There are no alternatives in the sibling list, so explicit exclusion is unnecessary, giving clear context.
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 carries full responsibility. It discloses two key behaviors (format validation and disposable domain check) but does not mention return format, potential side effects, or whether actual domain verification occurs, leaving some ambiguity.
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, front-loaded sentence with no redundant words. Every word adds meaning and the structure is optimal for quick comprehension.
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?
For a simple tool with one parameter and no output schema, the description covers the core purpose but omits information about the return value or result format, which an agent would need to process the output 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?
With 0% schema description coverage, the description must compensate. It implicitly identifies 'email' as the address to validate, but does not explicitly describe the parameter or any constraints beyond the schema's string type.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 email format and checks for disposable domains, which is specific and distinguishes it from sibling validation tools like validate_json or test_regex.
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 implies when to use the tool (whenever email validation is needed) but provides no explicit guidance on alternatives or exclusions. It is clear but lacks explicit context beyond the immediate function.
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?
With no annotations, the description carries the burden of safety disclosure. It does disclose the key behavioral trait of not verifying signatures, which is a critical security caveat. However, it does not mention error handling, malformed tokens, or what exactly is returned (e.g., JSON object vs. separate fields), leaving some gaps.
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?
A single, direct sentence with no unnecessary words. The information is front-loaded and every word adds value, making it highly concise and well-structured.
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 simple utility with one parameter and no output schema, the description covers the core function and the key limitation (no verification). It does not detail return format or error behavior, but given the tool's simplicity and clarity, it is nearly 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 0%, so the description must compensate. It identifies the parameter as a 'JWT token', which gives semantic meaning to the otherwise bare 'string' type. But it does not elaborate on token format (e.g., three dot-separated parts) or how the token should be provided, so compensation is partial.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 the specific verb 'decode' with the resource 'JWT token' and explicitly states the scope ('header + payload') and an important distinction ('without verification'). This clearly distinguishes it from any potential verification tool and aligns with the tool's function.
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 phrase 'without verification' implies this tool is for inspection only, not for validating tokens, giving some context on when to use it. However, it does not explicitly state use cases or alternatives, so guidance is implied rather than explicit.
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?
With no annotations provided, the description must carry the burden of behavioral transparency. 'Query' implies a read-only operation, but it does not disclose potential behaviors such as error handling, rate limits, default type behavior, or what is returned if a domain has no records. The description adds minimal context beyond the basic action.
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 sentence that front-loads the action and resource ('Query DNS records for a domain') and lists the record types. Every word earns its place; there is no redundancy or filler.
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 simple DNS lookup tool with two parameters and no output schema, the description provides the core functionality sufficiently. However, it lacks details on default record type when 'type' is omitted and the structure of the response, which an agent might need for robust invocation. Minor gaps but not critical for a simple 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 50% ('type' has a description, 'domain' does not). The tool description lists the valid record types, which reinforces the 'type' parameter semantics. However, it does not add additional meaning for the 'domain' parameter or mention that 'type' is optional and what the default behavior might be.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 'Quer[ies] DNS records for a domain' and lists the specific record types (A, AAAA, MX, TXT, NS, CNAME). This is a specific verb+resource that distinguishes it from sibling tools like whois_lookup or 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when DNS records are needed, but it does not explicitly state when to use this tool versus alternatives. There is no mention of exclusions or when not to use it. The context is clear enough but relies on the tool name and obvious purpose.
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?
With no annotations provided, the description carries the full burden. It states the primary action but does not disclose details like Markdown flavor support, output handling, potential errors, or side effects. For a simple conversion tool, this is adequate but not rich.
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, clear sentence with no wasted words. It is front-loaded and directly conveys the tool's purpose.
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 simple single-parameter conversion tool, the description is largely complete. It lacks an output schema, but the return value is implied by the tool's purpose. No significant gaps are present for typical 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?
The schema has no descriptions for the parameter, so the description must compensate. It does mention 'Markdown text,' which aligns with the 'markdown' parameter, but adds no additional format or usage details beyond what the parameter name and type already imply.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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: converting Markdown text to HTML, using a specific verb and resource. It is distinct from sibling tools like convert_currency or csv_to_json, which perform different conversions.
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 intended use is implied by the purpose, but no explicit guidance is given about when to use this tool versus alternatives, nor are any exclusions or prerequisites mentioned. It lacks clear context for selection among the many converter siblings.
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 carries the responsibility for disclosure. For a simple, side-effect-free operation like fetching a random quote, the description is arguably sufficient, but it adds no extra context about behavior such as network usage or randomness source.
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 sentence that contains all necessary information 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?
Given the tool's simplicity (no parameters, no output schema), the description is fully complete. It explains the core functionality without needing additional 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?
The tool has zero parameters, and the schema coverage is 100% (empty properties). Per the rubric, a baseline of 4 is appropriate when there are no parameters to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 with a specific verb ('Get') and resource ('random tech/programming quote'). It naturally distinguishes itself from the sibling tool 'get_random_joke' by specifying the content type.
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 usage context is implied: use it when you need a random tech/programming quote. However, it does not explicitly mention alternatives or when not to use the tool, so it falls short of providing full guidance.
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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