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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantial context: account/auth requirements, never-invents-answers behavior via explicit gaps[], latency expectations (15-60s, ~90s for thorough), the resolvable citation_uri guarantee, contradictions[] scan on standard/thorough, and semantic excerpting of large records. No contradiction with 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?

Dense with valuable content but structured as one rambling wall of text with mixed emphasis and parentheticals. The depth-mechanics prose partially duplicates the schema enum descriptions, and there are formatting glitches like 'depth:"thorough"' and a repeated 'prefer ask_pipeworx' that read as typos. It is front-loaded well (account requirement first) but would benefit from segmentation.

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 complex tool with no output schema, the description compensates fully: it describes the findings packet contents (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), gaps[], contradictions[], the hop field, timing, and auth requirements. An agent has everything needed to decide when to call and what to expect from the response.

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 coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema: it maps depth levels to facet counts and hops, discloses that thorough requires a paid plan, and explains the question parameter is meant for broad/multi-part natural language where 'decomposition is the point.'

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?

States a specific verb and resource: 'Grounded multi-source research across Pipeworx's 1506 STRUCTURED data sources' delivered in one call. It distinguishes itself from alternatives by explicitly declaring 'this is NOT open-web search' and contrasting with ask_pipeworx for single lookups, so an agent can tell it apart from siblings.

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?

Provides explicit when/when-not guidance with named alternatives: use ask_pipeworx if not signed in, for single lookups, and for breaking/current news because deep_research returns empty gaps for topics outside the structured catalog. It also states the tool is best for broad/multi-part questions over structured data and supplies example queries ('compare X and Y's regulatory + financial exposure').

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