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

Annotations cover readOnly/openWorld/idempotent, and the description adds far richer behavior beyond them: the account/paid-plan gate, 15-60s/up-to-90s latency, parallel decomposition across 5,743 tools, the full findings-packet shape (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), the never-invented gaps[] guarantee, contradictions[] scanning, the hop field, the citation_uri fetchability guarantee, and semantic excerpting. 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?

Information-dense and well front-loaded, with the critical auth gate first and the core purpose immediately after. Slightly redundant — the ask_pipeworx alternative and the paid-plan constraint each recur — but for a complex tool with no output schema, nearly every sentence earns its place.

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 carries the full burden of explaining return values, and it does so exhaustively: findings packet fields, gaps[], contradictions[], hop, citation_uri, plus auth prerequisites, latency windows, sibling routing, and edge behaviors like semantic excerpting. An agent has everything required to invoke it correctly and interpret results.

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% and the depth enum is already richly described in the schema (hop counts, gap recovery, contradictions scan). The description adds value above that baseline: per-depth latency expectations, the paid-plan restriction on thorough, and worked example questions illustrating what 'question' should contain. Genuinely additive, though not a dramatic delta over the already-strong schema.

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+resource: 'Grounded multi-source research across Pipeworx's 1500 STRUCTURED data sources... in ONE call.' Actively differentiates from siblings by declaring 'this is NOT open-web search' and explicitly naming ask_pipeworx as the sibling for different jobs, so an agent can disambiguate without opening other schemas.

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?

Gives explicit when-to-use, when-not-to-use, and named alternatives: 'If you are not signed in, use ask_pipeworx instead,' 'For a single lookup use ask_pipeworx instead,' and for breaking news 'prefer ask_pipeworx... deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog.' Also provides positive worked examples ('compare X and Y's regulatory + financial exposure'). Nothing is left to inference.

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