ToolSnap MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It lists operations but fails to disclose behavioral traits such as read-only nature, error handling, or performance characteristics. Basic safety information is missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two short sentences that front-load the purpose. No extraneous information or wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 8 parameters and no output schema, the description is too minimal. It lacks details on filter format (partially in schema), sort direction constraints, and result format. The tool's functionality is not fully covered.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 13%, with only 'filter' having a description. The description adds context for 'csv' and 'url' but does not explain 'select', 'limit', 'sort_by', 'sort_dir', or 'format'. For a tool with 8 parameters, this is insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool queries a CSV with operations like select, filter, sort, and limit. It specifies the resource (CSV) and distinguishes it from sibling tools that work with other formats like JSON or HTML.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'One of url or csv' as a constraint but does not provide explicit guidance on when to use this tool versus alternatives like json_query or fetch_extract. No exclusion criteria or context for selection is given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description discloses key traits: it's free, reduces tokens by 98% median, and cannot handle JS SPAs. However, it omits error handling, rate limits, or specifics of 'clean text' extraction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise: three sentences with clear front-loading of purpose. Each sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity (two parameters, no output schema, no annotations), the description covers core purpose and limitations but lacks behavioral details (e.g., timeouts, return format) and parameter documentation, missing some completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 parameters (url, maxChars). The only mention is implicit in 'Fetch a URL', but no details on usage or constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool fetches a URL and returns clean text. It distinguishes from JS SPA usage with 'Not for JS SPAs' but does not explicitly differentiate from siblings like fetch_html or fetch_structured.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions benefits (free, token reduction) and a limitation (not for JS SPAs), which implies when to use, but provides no explicit guidance on alternatives or when not to use compared to sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden. It states the output (clean HTML) and mentions 'Free', but does not disclose rate limits, error behavior, or other behavioral traits like content size limits. It 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short (two sentences) and front-loaded with the verb 'Fetch'. Every sentence adds value, though it could benefit from slightly more structure. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (2 params, no output schema), the description covers the main purpose but lacks explanation of the 'maxChars' parameter and return format details. It is minimally viable but incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 'maxChars' parameter. It only mentions 'clean HTML' without linking to parameters. The description adds minimal meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: fetch a URL and return clean HTML with structure kept and scripts/styles stripped. It mentions 'Free' and 'Site migration' as context, effectively distinguishing from sibling tools like fetch_metadata or fetch_structured.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for getting clean HTML for tasks like site migration, but it does not explicitly state when to use this tool vs alternatives, nor does it mention when not to use it. There is no exclusion guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description must cover behavioral traits. It states the tool extracts metadata but does not disclose potential issues like rate limits, handling of redirects, or authentication requirements. The description is straightforward but lacks depth on side effects or constraints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the primary action and extracted items. No redundant words. The structure is optimal for the tool's simplicity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

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 and no output schema. The description lists all extracted fields (title, description, OG, Twitter, canonical, JSON-LD), which is sufficient for an AI to understand the return type. Minor omission: does not mention that the output is JSON, but implied by 'extract' and common practice.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 only describes the parameter implicitly via the tool's purpose; it does not specify that the URL must be fully qualified, supports protocols, or any validation rules. Since 'url' is the only parameter and its meaning is obvious, the lack of additional semantics is a minor gap but still insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the action (Fetch a URL) and the specific data extracted (title/description/OG/Twitter/canonical/JSON-LD). This distinguishes it from siblings like fetch_html (which retrieves full HTML) or fetch_structured (which may return other structured data).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly notes what the tool does not do ('Not for body text.'), providing a clear negative usage guideline. However, it does not explicitly state when to use this tool over alternatives like fetch_structured or csv_query, leaving some ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description mentions 'Deterministic' as a behavioral trait, but with no annotations provided, it should disclose more (e.g., that it is read-only, no side effects). It fails to specify rate limits, authorization needs, or what happens on fetch failure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short (one sentence), which is concise but omits essential details like output format and parameter behavior. It is front-loaded with the core operation but lacks structural elements that would aid quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and only partial parameter descriptions, the description fails to explain return values, error handling, or the exact relationship between the schema parameter and extracted data. It is incomplete for a tool with two required parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%; the 'url' parameter has no description in the schema or the description. The description vaguely says 'extract JSON Schema fields' but does not clarify how the 'schema' parameter is used (e.g., to filter fields or validate structure). The schema parameter's description ('JSON Schema string.') is minimal and not enriched by the tool description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool fetches a URL and extracts JSON Schema fields from JSON-LD/OG/microdata, using the verb 'fetch' and specifying the resource and operation. It distinguishes from siblings like fetch_html and fetch_extract by explicitly mentioning structured data extraction and deterministic behavior.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 (e.g., fetch_extract or json_query). The description omits any context for appropriate usage, such as prerequisites or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description bears full responsibility for behavioral disclosure. It correctly indicates the tool does not support JavaScript Single Page Apps. However, it does not explain behavior for missing/conflicting parameters, nor does it describe the maxChars parameter or any error/rate-limit handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences: first states the action, second adds a key constraint. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 3 parameters (none required, no enums) and no output schema. The description covers the core conversion and the SPA limitation but omits details on maxChars, default behavior, error cases (e.g., both params missing), and output format. It is adequate for a simple tool but leaves gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 33% (only 'html' has a description). The tool description adds that one of 'url' or 'html' should be provided, clarifying their relationship. The 'maxChars' parameter remains unexplained. The description adds some value but does not fully compensate for the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Convert a URL or raw HTML to Markdown.' It specifies the input types (URL or raw HTML) and adds a constraint ('Not for JS SPAs.'), distinguishing it from sibling tools like fetch_html or fetch_extract.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description notes that one of 'url' or 'html' should be provided, implying mutual exclusivity. It also warns against using with JS SPAs. However, it does not explicitly name alternatives or provide when-to-use/not-use guidance relative to sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 describes the query syntax and input alternatives but does not disclose behavior like error handling, performance implications, or what happens if both url and json are omitted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, very concise with no redundancy. It front-loads the core purpose. However, it could be slightly restructured to better separate the query syntax from input options.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters and no output schema, the description lacks important context such as optionality of url/json, default behavior of 'limit', and error scenarios. It is too minimal to fully inform an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25% (only 'query' has a description). The description adds meaning by explaining the query syntax and stating that url or json are alternatives, but does not cover the 'limit' parameter. It partially compensates for the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Query JSON with JSONPath-lite ($.a[*].b, ..key)', specifying the exact syntax and resource (JSON). It distinguishes from siblings like csv_query and fetch_extract, which operate on different data formats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'One of url or json', hinting at exclusive usage, but does not provide explicit guidance on when to use this tool vs alternatives like fetch_extract or csv_query. It lacks when-not-to-use or alternative recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Mentions pricing ($0.04 USDC/call) which is a behavioral trait, but does not disclose whether it is read-only or any authorization needs. With no annotations, the description carries full burden but provides only partial transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise single sentence plus pricing, no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and 4 parameters, the description lacks crucial context about return values, parameter usage, and behavior. It is insufficient for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the description adds no meaning to the parameters (language_code, location_code, include_suggestions). It only says '1-20 keywords' but does not explain the format or the other fields.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it provides Google Ads volume, CPC, and competition for 1-20 keywords, distinguishing it from sibling tools which are generic fetch/query tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives, no context on prerequisites or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits. It only mentions 'save instruction' without explaining side effects, permissions, or what 'harness's memory' entails. This is insufficient for an agent to understand 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short but lacks clarity. It is not concise in conveying meaningful information, as it uses jargon ('ToolSnap habit block') without explanation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one optional parameter and no output schema, the description should provide sufficient context. It fails to explain the tool's purpose, return value, or how it integrates with the system.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

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 'harness' parameter or its enum values. The meaning of the parameter is entirely opaque.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'ToolSnap habit block + save instruction for your harness's memory' is vague and does not clearly state what the tool does. It lacks a specific verb and resource, making it hard to distinguish from siblings like csv_query or fetch_extract.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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. The description offers no context for appropriate usage scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It discloses the critical constraint of no OCR, but does not mention auth needs, rate limits, output format, or error handling for non-text PDFs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, fully front-loaded with verb and constraint. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Sufficient for a simple tool with 2 parameters and no output schema, but lacks detail on 'maxChars' parameter and output format, leaving room for agent confusion.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so description must explain parameters. It does not explain 'url' (trivially) or 'maxChars' (likely max characters to extract, but ambiguous). The description adds minimal value for parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Fetch' and 'extract', the resource 'PDF by URL', and the limitation 'No OCR — text-based PDFs only', which distinguishes it from tools like fetch_extract or screenshot_url.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'No OCR — text-based PDFs only', guiding that this tool should not be used for scanned PDFs, but does not name specific alternative tools among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description must disclose behavior. It only says 'Free' and 'Machine-readable', lacking details on side effects, authentication needs, 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, no wasted words, front-loaded with key information. Highly concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequate for a simple pricing tool with no parameters, but lacks description of return value format or structure, which would be helpful without an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist, and schema coverage is 100% trivial. According to guidelines, baseline score is 4 for 0 parameters, and the description does not need to add param info.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool provides a 'Machine-readable pricing menu' covering free vs paid tools, pricing, and deposit/spend flow. It distinguishes itself from sibling tools, none of which are pricing-related.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. The description does not mention context, prerequisites, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 discloses the cost ($0.03/call) but lacks details on whether the operation is destructive, idempotent, processing time, or URL expiration. The return value description is minimal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the main action and output, and includes the cost. Every word is meaningful with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

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 functionality, output, and cost. It could mention URL expiration or image format requirements, but overall it is reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single parameter 'image_url'. The description adds value by mentioning the cost and return type, but does not provide additional parameter constraints like allowed URL formats or maximum file size. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Remove' and resource 'image's background', with a specific output 'transparent PNG URL'. This is a specific verb+resource combination that distinguishes it from any sibling tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives. There is no mention of prerequisites (e.g., acceptable image formats, size limits) or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided; description lacks details on network behavior, error handling, authentication, or side effects. Only mentions token savings but not operational aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Very concise single sentence with front-loaded purpose. Token saving claim adds value but could be restructured to include more utility without bloat.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, no annotations. Description does not inform agent about return format, error behavior, or feed structure, leaving significant gaps for a tool that fetches external data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50% (only maxItems has a description). Tool description adds no meaning to parameters: does not explain url format or maxItems purpose beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the verb (fetch/parse), resource (RSS or Atom feed), and output format (JSON). Distinguishes from sibling tools like fetch_html or fetch_structured by specifying the feed type.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus siblings. Does not mention alternatives or provide context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations present, the description must fully disclose behavioral traits. It only mentions cost per call, omitting important aspects like potential failure modes, rate limits, authentication requirements, or whether the tool modifies any state. This is minimal disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise (one sentence plus cost), which is efficient but at the expense of necessary details. It front-loads the key purpose but omits parameter and behavioral info, making it borderline insufficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, no output schema, no annotations), the description is incomplete. It does not describe the return value format, error handling, or constraints like maximum URL length or allowed domains. It fails to provide a complete picture for correct usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 17%, yet the description does not explain any parameters. It fails to clarify the meaning of url, width, format, height, quality, or fullPage beyond what the schema provides. With low coverage, the description should compensate but does not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool's function: taking a screenshot of a web page and returning a public image URL. This is a specific verb-resource pairing that clearly distinguishes it from sibling tools like fetch_html or remove_background.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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 (e.g., fetch_html for HTML extraction or remove_background for image processing). The description lacks any conditional usage advice or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided; description fails to disclose behavioral traits such as rate limits, authorization needs, or error handling beyond the maxUrls constraint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no wasted words; front-loaded with verb and resource.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Simple tool with few parameters, but description lacks details on output structure and error scenarios, making it minimally adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%; description implies url is the sitemap URL and maxUrls has a short description, but no added semantics beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb 'fetch/parse' and resource 'XML sitemap' with output 'into JSON' and action 'enumerate a site's pages'. Distinct from sibling rss_parse.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like rss_parse or fetch_extract. Lacks 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.

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 mentions 'Free' and the return type (menu or prompt). There is no disclosure of side effects, authentication needs, or rate limits. For a tool that appears to be read-only, more detail on what happens when a recipe is executed would be helpful.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that packs essential information: purpose, usage pattern, and parameter behavior. No wasted words, front-loaded with key details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one optional parameter and no output schema, the description covers the core functionality: two modes of operation. It does not specify how to discover recipe IDs or the format of prompts, but the menu mode likely provides that. Overall adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage for the only parameter 'recipe'. The description adds meaning by explaining that with no args it shows a menu and with recipe='<id>' it returns a prompt. This clarifies the parameter's role beyond just being a string.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool provides multi-tool workflow prompts for tasks like cloning a site or SEO audit. It distinguishes from sibling tools which are individual operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description tells when to use the tool (for multi-step workflows) and mentions the two modes (no args → menu, recipe arg → prompt). It implicitly suggests using other tools for single actions, but does not give explicit when-not-to-use or alternative tool names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, but the description explains the mapping from arguments to output levels (families, tools, detail). It mentions 'Free' and 'Full catalog' implying no cost and completeness. No side effects or destructive actions expected.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, using a compact notation that conveys all essential information in a single sentence. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers all parameter combinations and output levels. It does not specify output format or error handling, but given the tool's simplicity, it is nearly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description fully explains each parameter's purpose and the resulting behavior (family='<id>' → tools, tool='<name>' → detail). This adds all necessary information beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly defines the tool as a catalog of available tools/families, with specific usage patterns for different arguments. It distinguishes itself from sibling tools by being a meta-tool for discovery.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Three clear usage patterns are given (no args, family, tool) indicating when to use each. No explicit when-not-to-use instructions, but the patterns are self-explanatory. Alternatives not mentioned, but it's a unique tool among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must cover behavioral traits. It only mentions pricing and that it is free, but omits details on error handling, authentication, rate limits, or side effects. This is insufficient for a generic tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short (two sentences) and front-loaded with the core purpose. No superfluous content. However, it could be restructured to include key behavioral details while remaining concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's generic nature, lack of annotations, nested parameters, and no output schema, the description is critically incomplete. It does not explain how 'name' and 'args' work, error scenarios, or how results are returned.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% coverage, and the description adds no information about the 'name' or 'args' parameters. It fails to explain what values are expected or how they are used, leaving the agent without useful guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Run any tool not in tools/list' which clearly identifies the tool as a generic fallback for calling tools outside the standard list. This distinguishes it from the specific sibling tools. However, it could be more precise about what 'run' entails.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a tool is not in tools/list, referencing tool_catalog for alternatives. However, it does not explicitly state when not to use it or provide clear alternatives beyond the vague mention of tool_catalog.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.