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 doesn't indicate whether the fetch is read-only (though 'Fetch' implies read), whether it returns error handling for missing IDs, rate limits, or format of the returned content. Minimal 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.

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

Single, efficient sentence that front-loads the action and resource. No unnecessary words, though could be slightly more explicit about the return value.

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, the description covers the essential purpose. However, with no annotations and no output schema, additional context such as response shape, error behavior, or authentication requirement would improve 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 100% and the single parameter's schema description already states it's the ID from search-community results. The description merely repeats 'by id' without adding format or other constraints. Baseline 3 per guidelines.

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?

States a specific verb (Fetch), resource (full content of a community contribution), and key modifier (by id). Distinguished from sibling search-community which is referenced as the source of the ID.

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?

Implied usage: after searching via search-community, use this tool to retrieve the full post. However, it doesn't explicitly state when NOT to use this tool or contrast with get-doc/get-menu/get-schema.

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 and no output schema, the description carries the full burden, and it does disclose the return shape (full page text plus all code examples). However, it says nothing about failure modes (unknown id/path), rate limits, or auth requirements, so key behavioral context is missing for a no-annotation 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?

Three compact sentences, each doing distinct work: what it returns, how to look it up, and when to call it. Front-loaded with the purpose and no 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?

Because there is no output schema, the description must describe returns – and it does (complete page text plus code examples). Sibling and sequencing relationships are covered. The only real gap is error/edge behavior when a lookup key does not resolve.

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 already documents id, path, and title, including the warning that titles are non-unique. The description's lookup guidance (id/path/title, prefer id or path) largely restates that, adding little beyond the schema – baseline 3.

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?

States a specific verb and resource ("Fetch a full official FeathersJS doc page") plus the scope of what it returns ("complete page text plus all code examples"). The role is clearly differentiated from siblings like search-doc and get-menu, which are named as upstream steps rather than substitutes.

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 enumerates the triggering conditions: after get-menu (paths/ids), after search-doc, or when the user supplied an exact id/path/title. It also gives a selection rule among the tool's own inputs ("Prefer id or path over title"), leaving little to inference.

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 behavioral burden; it discloses that the result is a hierarchical view of topics and relationships, implying a safe read. It says nothing about caching, freshness, size of the payload, or authentication needs, leaving meaningful gaps for a no-annotation 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?

Three short sentences, front-loaded with the core purpose before the return-shape and usage notes. Slightly verbose in restating the 'documentation topics/organization' idea twice, but nothing is wasted.

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 exists, so the description appropriately characterizes the return value as a hierarchical navigation structure. Combined with the stated session-start usage, this is sufficient for a zero-parameter read tool, though not exhaustively detailed.

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 takes zero parameters, so the baseline of 4 applies; there are no arguments whose semantics the description would need to explain. Schema coverage is reported at 100%, reinforcing that no parameter detail is missing.

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?

States a specific verb and resource ('Get the menu/navigation structure of the FeathersJS documentation') and clarifies the output is a hierarchical topic view. It is distinguishable from siblings like get-doc or search-doc by resource, though it does not explicitly contrast itself 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?

'Called at the start of each session to understand the organization of the content' gives explicit timing and intent for invoking the tool. There is no statement of when not to use it or which sibling to prefer for other needs, but the positive guidance is clear.

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 carries full burden. It implies a read-only operation (retrieving schema) but doesn't state permissions, rate limits, or output format. For a zero-parameter tool, the behavioral traits are minimal, so 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.

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

A single, front-loaded sentence that is efficient and waste-free. It directly states the tool's purpose without 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 (no parameters, no output schema), the description is sufficient to understand what it does. However, it could benefit from mentioning that it returns schema information for documentation tables, though that is implied.

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 to document. Schema coverage is 100% by default. The description adds no parameter details, but none are 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?

States a specific verb (get) and resource (database schema for FeathersJS documentation tables), which is clear. However, it doesn't distinguish itself from siblings like get-doc or get-menu, which also retrieve 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?

No guidance on when to use this tool versus alternatives such as search-doc or get-doc. The description implies it returns schema metadata, but no context or exclusions 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?

No annotations are provided, so the description carries the full disclosure burden. It states the return shape ('results with id for get-community-post') and an actionable post-call constraint ('Include at least one community insight in your answer'), but says nothing about result limits, pagination, or auth/scope requirements.

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?

Front-loaded with the core purpose, then organized under scannable headers (PRIMARY use cases / MUST use when / After calling / Returns). Every bullet carries routing or workflow information; nothing is padding.

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 single-parameter search tool with no output schema, the description covers purpose, triggers, and what the results contain, and even specifies the next tool to call. Nothing an agent needs to invoke or sequence it correctly is missing.

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 'query' parameter, so the schema already documents its type and purpose. The description adds example queries ('authentication', 'react-native'), but those duplicate the schema example, so this is the baseline 3.

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?

States a specific verb and resource: 'Search real-world FeathersJS solutions from the community.' It also implicitly scopes itself against siblings like search-doc and get-doc by targeting solutions 'not in docs,' so the agent can distinguish it without opening a schema.

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?

Explicit 'PRIMARY use cases' and a directive 'You MUST use this when' list three concrete triggering conditions, including negative-style guidance ('solution is not clearly in a single doc page') that routes the agent away from doc search. It also names get-community-post as the follow-up alternative.

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 the full burden. It usefully discloses that iterative multi-call refinement is expected, but says nothing about result format, ranking, pagination, or what limit does behaviorally beyond the schema default. Some behavioral context is added, but a no-annotation tool should say more.

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?

Three short sentences with the core purpose front-loaded and the operational tips following. Nothing is padded, though the prerequisite guidance could be tightened to make the tool's own scope clearer.

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?

There is no output schema and no annotations, so the description must cover behavior on its own. It covers prerequisites and iteration adequately but omits return shape and result-size behavior, leaving a real gap for an agent deciding how to consume or paginate results.

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 all four parameters (including the keyword/sql enum and category values) are already documented in the schema. The description adds no syntax, format, or example guidance beyond that, so the baseline 3 for schema-driven parameters 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?

States a specific verb (Search) and a specific resource (the FeathersJS documentation), so an agent immediately knows this is a retrieval tool over docs. It does not explicitly distinguish itself from close siblings like search-community or get-doc, relying on the resource noun alone to do that work.

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?

It gives a useful prerequisite chain (call get-schema and get-menu first) and notes that repeated calls are expected to refine results. However, it never states when to prefer this over the sibling get-doc (exact retrieval) or search-community, and gives no exclusions, so the routing 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.

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

With no annotations, the description carries the behavioral burden and does disclose the key trait: the tool only generates a link, it does not submit anything itself, and the URL must be surfaced in the next user-facing reply. It says nothing about auth, failures, or repeated-call behavior, which keeps it short of a 5 given 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.

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

Three sentences, front-loaded with the core action, then the trigger, then the critical output requirement. The emphasis is well placed, though the middle trigger sentence is somewhat long.

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?

There is no output schema, so the description must explain the return value -- and it does ('full magic link URL as a clickable Markdown link'). Combined with the contribution-collection workflow and the no-annotations behavior disclosure, an agent has enough to invoke it correctly, though nothing is said about error or edge cases.

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%, so the baseline is 3, but the description adds workflow meaning by naming the exact set of inputs to gather (title, author, content, tags) in the context of the contribution flow rather than just restating field names.

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 precise verb and artifact: 'Generate a pre-filled GitHub issue link so the user can submit a community contribution (project, tutorial, or pattern) to the repo.' It also enumerates the accepted contribution kinds, so an agent can distinguish this contribution-generating tool from the read-only siblings like get-doc and search-community.

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?

It gives explicit trigger conditions ('If the user has built or completed something useful with FeathersJS... proactively ask if they want to share; if they agree, collect title, author, content, tags and call this tool'). When-to-use and the prerequisite gathering step are both spelled out, leaving nothing to inference.

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