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

With no annotations present, the description carries the full burden and does so extremely well. It discloses that the returned result is incomplete ('passages, not a finished answer'), requires agent judgment, and honorsting versioning plus conflict-handling rules. It also mandates citing Source URLs, adding behavioral expectations beyond the input schema.

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?

Everything is compact and front-loaded: purpose, then payoff behavior, then nuance. The description is dense but every sentence carries information — no fluff, no repetition of the input schema.

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?

Since there is no output schema, the description compensates by fully specifying the return shape ('passages'), semantics ('version -pinned', conflicts, citation). All important behaviors an agent needs to call it correctly and interpret results are stated.

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 only parameter, 'question', is already fully documented in the schema as 'Your question'. The description doesn't add extra parameter-level detail, but with 100% schema coverage, that's acceptable — this hits 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?

The description names a specific action ('Ask a natural language question') and a clear resource scope ('all connected sources'), distinguishing it from narrower or more targeted sibling tools like search_docs or query_source. It also clarifies the output type ('passages') rather than a finished answer, which prevents the agent from confusing it with a summarizer or direct-answer 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?

The usage context is clear: it is a cross-source natural-language QA tool, and it gives explicit downstream instructions: read the passages, respect version labels, prefer the current-docs one on conflict, and cite the Source URL. It could name sibling tools or state exclusions explicitly, but it offers enough context for an agent to decide when to call it.

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