ask_wiki

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

With no annotations, the description carries the full burden and does so thoroughly: it explains the retrieval pipeline (search → top hits + 1-hop wikilinks), the use of a configured LLM, and the citation-marker rendering convention. This is more than most tool definitions disclose.

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 three sentences with no wasted lines. The first states the core action, the second explains the retrieval behavior, and the third gives the critical citation-rendering instruction. Details are front-loaded and relevant.

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 explain the return shape, and it does: the cited answer and the citations array, including how to link each [N] marker to mindbase_uri. The description is sufficiently complete for an agent to select and correctly use the tool.

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 are already well documented in the input schema (100% coverage), so the description doesn't need to add much. The description provides broader retrieval context but doesn't add parameter-specific semantics beyond the schema, which aligns with the baseline of 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?

The description states a specific action ('Ask a natural-language question against the user's wiki') and a concrete resource, plus the distinguishing output (a cited answer). It differentiates from siblings by emphasizing graph-aware retrieval and 'what do I know about X?' questions.

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 positions this as the 'Best tool for "what do I know about X?" questions', which gives clear direction on when to use it. It does not mention alternatives or exclusions, but the use-case framing effectively routes agents toward it.

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