fetch_rag

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions returning relevant content but does not disclose how the tool handles redirects, authentication, errors, or the chunking behavior hinted at by the max_chunks parameter. This is a significant gap for a web-fetching tool, leaving the agent with limited insight into side effects or limitations.

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, front-loaded sentence that directly states the tool's purpose and the optional refinement. It contains no filler or redundant wording, making it highly concise and easy to parse.

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 schema covers all parameters and defaults, but the description does not specify the return format or any behavioral constraints such as timeouts or size limits. Since there is no output schema, a bit more detail about what 'relevant content' means (e.g., chunks, snippets) would improve completeness. However, for an agent invoking the tool, the schema and current description provide enough to proceed.

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?

All three parameters have schema descriptions with 100% coverage, clearly explaining 'URL to fetch', 'Query to find relevant content', and 'Maximum number of chunks to return'. The description itself adds little beyond the schema, merely restating the existence of an optional query. Since the schema carries the semantic weight, a 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 tool's action ('Fetch URL') and expected output ('return relevant content'), with an optional query to refine results. This is a specific verb+resource pair, and the description is unambiguous about what the tool does, even without sibling tools for differentiation.

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 use cases by stating it fetches URLs and optionally filters by query, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. Since no sibling tools are listed, some implicit usage guidance is acceptable, but it remains at the implied level.

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