docs

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

Annotations already indicate readOnlyHint=true, so safety is clear. The description adds behavioral detail by enumerating return fields (title, description, heading outline, full Markdown body) and confirming it's a fetch operation. No destructive or unexpected side effects are implied.

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 efficiently conveys purpose, parameters, and return value. It is front-loaded with the core action and format, and every clause 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?

For a simple read tool with full schema coverage, annotations, and no output schema, the description provides all necessary context: what it does, what it returns, and how to derive inputs. There is no missing or ambiguous information.

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% with descriptive parameter names. The description supplements by explaining the source of each parameter (e.g., 'from list_products results') and providing URL extraction guidance. This adds meaningful context beyond the schema's own descriptions.

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), resource (single documentation page), and output format (Markdown). It distinguishes from siblings by specifying that it retrieves a full page given a product and slug, unlike listing or searching. Examples of return fields (title, description, heading outline, body) add specificity.

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 the agent that parameters come from list_products or search_docs results, or from a doc URL. This gives clear context for when to use the tool (after identifying a specific page). However, it does not explicitly state when not to use it or compare to siblings beyond mentioning source 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?

Annotations already declare readOnlyHint=true, so no contradiction. The description adds key behavioral context: the file is large and returned as a resource link/canonical URL rather than inlined. This aids agent understanding of response 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?

Two highly concise sentences. The first sentence front-loads the purpose, and the second adds usage guidance and behavioral context. 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?

Given the tool's simplicity (one required parameter, no output schema, read-only annotation), the description is fully complete. It covers what the tool does, when to use it, and a key behavioral trait about the response format.

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 100% for the single parameter 'product'. The description does not add further semantics beyond what the schema provides (product id from list_products). Baseline score of 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 'Return', the resource 'link to the complete, source-linked agent reference', and the scope 'for a product'. It explicitly distinguishes from sibling tools 'search_docs/get_doc' by noting this tool is for 'the whole corpus'.

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 tells when to use this tool ('when you want the whole corpus') and provides a clear alternative for targeted lookups ('use search_docs/get_doc'). This helps an agent decide correctly.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false. The description adds valuable context about the output contents (blurb, version, URLs) and the live documentation constraint. Slightly more detail on potential staleness or caching could elevate it, but currently adds good behavioral insight beyond annotations.

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

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

Two sentences: the first lists the action and output fields, the second gives usage order. Every sentence is essential and informative 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 parameter-less listing tool with an output schema, the description fully covers what the tool does, what it returns, and its role in the tool ecosystem. No gaps identified.

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, so the schema fully covers them (100% coverage baseline). The description does not need to elaborate on parameters, and its content about output is sufficient for an agent to understand invocation without further detail.

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 lists Free Battery Factory products with live documentation, including specific fields (one-line blurb, docs version, canonical URLs). It distinguishes from siblings by positioning itself as the initial discovery tool for product IDs used by other 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?

Explicitly instructs the agent to call this first to discover valid product IDs for other tools, providing clear when-to-use guidance and implying it should precede sibling tools like get_doc or search_docs.

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?

Annotations already declare readOnlyHint=true and openWorldHint=false, so the description does not need to repeat safety. It adds value by specifying the output structure (title, description, URL, headings, snippet) and the scope behavior, which are behavioral traits beyond what annotations provide.

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

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

The description is two sentences, immediately stating the function and output, then providing usage guidance. Every sentence is necessary and well-placed, with no filler or repetition of schema 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?

The description covers the core functionality, output fields, and parameter usage. It lacks explicit comparison to siblings, but the presence of an output schema and the clear scope handling make it mostly complete. The mention of 'best-matching' implies relevance ranking, which is sufficient.

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%, but the description adds meaningful context: for product, it references list_products; for query, it provides example terms. This goes beyond the schema's basic descriptions, helping an agent understand how to use these parameters effectively.

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 performs full-text search across product documentation and lists the returned fields (title, description, canonical URL, matched section headings, snippet). It does not explicitly distinguish from sibling tools like get_doc or get_llms_full, but the verb and resource are specific, and the scope (single product or all) is clarified.

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 provides explicit guidance on using the product parameter: omit for all-product search or pass an id from list_products to scope. It does not explicitly state when not to use this tool (e.g., vs. get_doc for retrieving a single document), but the context is clear enough for an agent to infer appropriate usage.

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