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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, and the description adds substantial context beyond them: account/pricing prerequisites, explicit 'never invented' claims about gaps[], the guarantee that citation URIs are only present when fetchable, semantic excerpting behavior, contradictions[] scanning, and latency expectations. Nothing contradicts the annotations.

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 long but every sentence carries distinct information — prerequisites, fallback, scope, methodology, output packet, gaps, alternatives, depth behavior, citation guarantees, latency. It is well front-loaded with the account warning and sibling fallback. It loses a point only for being a dense wall of text with some depth-related details repeated from the 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?

For a tool with two parameters, rich annotations, many siblings, and no output schema, the description covers everything an agent needs to invoke it correctly: auth/plan requirements, the findings-packet return shape, the gaps[] and contradictions[] fields, citation fetchability, and estimated latency. The absence of an output schema is compensated for by the explicit description of what gets returned.

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 baseline is 3; the description earns an extra point by adding operational meaning to the depth parameter (what gap-recovery and lead-chasing hops do in 'standard' vs 'thorough') and tying depth choices to time expectations (15-60s, up to ~90s). The question parameter additionally receives guidance that 'Broad/multi-part is fine.'

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 verb-resource pair — 'grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources ... in ONE call' — and explicitly differentiates it from open-web search and from ask_pipeworx. An agent can tell exactly what this tool does and what it is not without opening the 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?

The description states explicit when-to-use ('Best for broad/multi-part questions over structured data'), gives a concrete example, and names exclusions: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead — it works on every tier.' The routing guidance is direct and actionable.

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