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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses decomposition into facets, parallel routing to 5,798 tools, the findings packet structure (gaps[], contradictions[], citation_uri), semantic excerpting rather than head-truncation, latency ranges (15-60s, up to ~90s), and the account/permission gate. These details go well beyond the annotations and let the agent predict both behavior and output characteristics.

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 information-dense but not tightly structured: 'For a single lookup use ask_pipeworx instead' appears twice, and the depth-explanation section partially duplicates the schema's own enum descriptions. Front-loading the account requirement is good, but the repeated sentence and redundancy with the schema make it slightly bloated.

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?

With no output schema, the description fully covers what an agent needs: what the tool does, the shape of the findings packet (verbatim evidence, confidence, source, fetched_at, citation_uri, gaps[], contradictions[]), behavioral facts like 'never invented' and semantic excerpting, operational constraints (latency, paid tier, sign-in), and alternative tools. Nothing essential is missing for correct selection and invocation.

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 schema already documents depth and question with clear descriptions, so the baseline is 3. The description adds concrete examples for question phrasing ('compare X and Y's regulatory + financial exposure'), ties 'thorough' depth to a paid plan and longer latency, and mentions the hop field and contradictions[] scan, which are not fully implied by the schema. It does not dramatically expand the parameter semantics but provides useful extra context.

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 action with a resource scope: 'Grounded multi-source research' across 1,517 structured data sources (SEC, FRED/BLS, FDA, USPTO, etc.), explicitly noting 'NOT open-web search'. It also differentiates from a key sibling by pointing out that single lookups should go to ask_pipeworx, so the tool's identity is unmistakable.

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 when-to-use and when-not-to-use guidance: 'If you are not signed in, use ask_pipeworx instead', 'For a single lookup use ask_pipeworx instead', and it says this tool is 'Best for broad/multi-part questions over structured data'. It also clarifies that depth:'thorough' requires a paid plan and that the default depth is 'standard', which helps the agent choose parameters.

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