docs

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

The description goes far beyond the readOnlyHint annotation by disclosing a critical behavioral caveat: the `current` field is an SSR-time fallback, not the live browser state, and the mechanism to find the live state varies per dimension. This transparency prevents an agent from misinterpreting returned data, which is exactly what behavioral transparency should do.

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 longer than the minimal case, but every sentence earns its place: it leads with purpose, then the read-only confirmation, and then the essential caveat about SSR fallback and per-dimension live-state discovery. The structure is logical and front-loaded; while not terse, it is not bloated.

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 no parameters, the description fully explains the output semantics (what is returned), the limitations (SSR fallback), and how to correctly interpret the data (read each dimension's description). With an output schema presumably defining structure, nothing is missing for an agent to call and use this 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?

The tool has zero parameters, so there is nothing for the description to add beyond the schema (which is empty). The baseline of 4 for 0-param tools is appropriate because the schema covers everything (100% coverage trivially) and no parameter guidance is needed.

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 a specific verb ('describe'), a resource ('adaptive dimensions of this site's pages'), and details the content (each layout regime, states, signal, thresholds). It clearly distinguishes itself from siblings, which are all about docs/products (get_doc, list_products, etc.), so an agent would never confuse this tool with them.

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 clear context for what the tool is for, but does not explicitly state when to use it vs alternatives. However, since no sibling tools perform a similar function, omitting explicit alternatives is acceptable. The read-only statement helps signal it's for inspection, not modification.

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, but the description adds valuable return details: title, description, heading outline, and full Markdown body, as well as output format. It also confirms 'single page' scope, which is not in the annotations.

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

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

One dense sentence conveys the action, inputs, output, and parameter provenance without filler. It is front-loaded with the core purpose and every clause 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?

For a simple read-only tool with two well-documented parameters and no output schema, the description covers inputs, output, and format. There are no significant gaps in the context needed to invoke it 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 100% and both parameter descriptions already include examples and source references. The description adds no new semantic detail beyond what the schema provides, so it stays at baseline.

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 uses specific verb 'Fetch' and identifies the resource as 'a single documentation page as Markdown', with clear inputs (product id and slug). It distinguishes itself from siblings: list_products lists products, search_docs searches, while get_doc pulls a specific page.

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 says parameters 'come from list_products / search_docs results, or a doc URL', providing clear context on how to obtain inputs. However, it does not explicitly state when to prefer get_doc over search_docs or list_products, nor does it describe 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?

Annotations already provide readOnlyHint=true. The description adds meaningful behavioral context: the file is large, so it is returned as a resource link and canonical URL rather than inlined. This goes beyond the annotation without contradicting it.

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: first states purpose, second adds behavioral detail and usage guidance. Every sentence earns its place, with no redundancy or filler.

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 one-parameter read-only tool with rich annotations, the description fully covers return behavior (link/URL rather than inline), usage context, and alternatives. No output schema is present, but the description explains the return form sufficiently.

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 a single parameter described as 'Product id from list_products.' The description adds no additional parameter semantics, but the schema already fully covers the only parameter, so 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 uses a specific verb ('Return a link') and names a clear resource ('llms-full.txt' complete agent reference). It distinguishes itself from siblings by contrasting with targeted lookups via search_docs/get_doc.

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 states when to use this tool versus alternatives: 'use search_docs/get_doc for targeted lookups and this when you want the whole corpus.' This is direct, unambiguous guidance naming both alternatives and exclusion conditions.

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 include readOnlyHint=true and openWorldHint=false, which already indicate a safe, closed-world operation. The description adds context about lifecycle status per blurb and that presence does not imply active development, which adds value beyond annotations without contradicting them.

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

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

The description is a single, well-structured paragraph that front-loads the purpose, lists specific output contents, and ends with a critical usage instruction. Every sentence adds unique information, with 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 zero parameters, an output schema exists, and annotations cover safety and scope, the description is comprehensive. It tells the agent exactly what to expect in the output and why to call the tool, making it complete for its simple function.

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 tool has zero parameters, and the schema coverage is 100%, so there is nothing to explain. The description focuses on output semantics (list of products with blurbs, versions, URLs) which adds value beyond an empty schema, aligning with the baseline of 4 for zero parameters.

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 lists Free Battery Factory products with a one-line blurb, current docs version, and canonical URLs, and explicitly distinguishes from siblings by noting that presence means docs are published, not active development. It sets expectations and provides a unique purpose.

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 instructs to 'Call this first to discover the valid product ids used by the other tools,' which provides clear when-to-use guidance and implies it is a prerequisite for other tools. It also explains the meaning of presence, indicating when not to over-interpret results.

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 discloses the full-text search behavior, the nature of results ('best-matching pages'), and exactly which fields are returned. It also explains the effect of omitting the product parameter. Annotations already declare readOnlyHint=true, and the description adds scoping and output context without any contradiction.

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 concise sentences. It leads with the core purpose, then adds the key usage nuance about the product parameter. No redundant or filler content.

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 moderate complexity (3 parameters, output schema, clear annotations), the description covers purpose, return contents, and usage nuance sufficiently. The output schema handles return structure details, and the read-only annotation covers safety, making the description complete on its own.

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% and each parameter already has a clear description. The tool description adds a brief explanation of the product parameter's scoping behavior, but this largely duplicates the schema's own description. No significant additional meaning is provided beyond the structured definitions.

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 performs 'Full-text search across the product documentation' with a specific verb and resource. It also lists the return fields (title, description, canonical URL, headings, snippet), distinguishing it from sibling tools like get_doc and list_products.

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 explains how to scope the search by omitting or providing the product parameter and references list_products as the source of valid IDs. However, it does not explicitly mention when to prefer search_docs over get_doc, so it stops short of full when/when-not guidance.

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