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

Annotations already indicate this is not read-only, not idempotent, and not destructive, but openWorldHint is true, meaning external side effects. The description adds the authentication detail, which is useful but minimal. It does not disclose rate limits, error behavior, or response format. No contradiction with annotations.

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

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

The description is a single, concise sentence that front-loads the core purpose. It is efficient and avoids fluff, but could have been enriched with a bit more context without losing conciseness.

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 generic API request tool with 5 parameters, the description is quite sparse. It does not explain the return value structure, authentication failure behavior, or how the 'data' parameter should be formatted for different methods. Given the tool's complexity and lack of output schema, more detail is needed to guide 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 100%, so every parameter already has a clear description. The tool description itself adds no additional meaning beyond what the schema provides, such as how parameters interact or typical usage patterns. 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 tool's purpose: making an authenticated request to a specific API (DataForSEO). The verb 'make' and the resource 'authenticated request' are specific and unambiguous. Sibling tools are all documentation-related, so this tool is clearly distinguished as the API request 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 on when to use this tool versus alternatives. While siblings are documentation tools, the description does not explicitly state that this is the only tool for API requests or mention any conditions or exclusions. The agent must infer usage from context.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered structurally. The description adds the llms.txt format detail and the optional filtering behavior, which is helpful context. It does not disclose return format or pagination, but for a simple read-only fetch the annotations carry most of the burden.

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?

A single 13-word sentence that front-loads the core action and then states the optional modifier. Zero filler, 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?

For a simple one-parameter fetch tool with a strong annotation safety profile, the description is mostly adequate. The gap is that it does not clarify the relationship with siblings (docs_search, docs_list_sections), and with no output schema the agent only learns the response is an 'index' or llms.txt text rather than its structure. Routing guidance would complete it.

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 the single 'section' parameter is already documented with an example ('SERP API'). The description's mention of 'optionally filtered by section' reinforces the parameter's purpose but adds no syntax or format details beyond what the schema 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.

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

The description uses a specific verb ('Fetch') and a precise resource ('DataForSEO API documentation index (llms.txt)'), and notes the optional section filter. It is clear what the tool does, though it does not explicitly contrast itself with siblings like docs_search or docs_list_sections, leaving some differentiation to inference.

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?

There is no guidance on when to use this tool versus the sibling tools. The description mentions optional section filtering but never routes the agent to docs_search for queries or docs_list_sections for browsing sections. A clear when-to-use/when-not-to-use statement is absent.

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 the tool read-only, idempotent, and non-destructive, so the description does not need to cover those aspects. It adds a small amount of behavioral context by stating that it returns available section names, but it does not disclose output format, ordering, or other runtime 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 a single, concise sentence that front-loads the action and the resource. There is 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?

For a zero-parameter, read-only listing tool with strong annotations, the description is adequately complete. It clearly states what the tool returns, which is sufficient given the low complexity and lack of 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?

This tool has zero parameters and the schema description coverage is 100%, so the description has no parameter meaning to add. A score of 4 is appropriate for a no-parameter tool where the schema is already complete.

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') and identifies the resource ('available DataForSEO API documentation section names'), making the tool's function clear. It does not explicitly contrast with sibling tools like docs_index or docs_search, so it misses the full differentiation that would earn a 5.

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?

There is no guidance about when to use this tool versus the sibling tools docs_index, docs_search, or api_request. The intended use is implied by the description, but no alternatives, exclusions, or selection criteria are provided.

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, openWorldHint, idempotentHint, and destructiveHint false. The description does not contradict these and adds that the tool fetches documentation content from a URL, but it offers no further behavioral detail such as return format, error behavior, or URL handling. The annotation coverage makes this adequate.

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 efficient sentence with a front-loaded verb and no unnecessary words. It communicates the core purpose immediately and avoids restating the title.

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 fetch tool with two fully described parameters and rich annotations, the description is nearly sufficient. It lacks explicit return-value expectations and sibling routing, but the schema and annotations compensate for most of the missing context.

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%, so the schema fully documents the url and needCodeExample parameters. The tool description itself adds no extra semantic meaning 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.

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

Description clearly states the verb 'Fetch' and the resource 'DataForSEO API documentation', and specifies it operates 'from a documentation URL'. It is distinguishable from api_request, which executes API calls, but it does not explicitly differentiate from sibling doc tools like docs_index or docs_list_sections.

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 phrase 'from a documentation URL' implies this tool should be used when a specific documentation URL or path is already known. However, it does not explicitly state when to use this tool instead of docs_index, docs_list_sections, or api_request, leaving the choice to inference.

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