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

Discloses substantial behavior beyond the annotations: requires an account, 'never invented' findings with gaps[], returns contradictions[] on standard/thorough, citation_uri presence conditional on resolvability, semantic excerpting of large records, and latency expectations (15-60s, up to ~90s). These details match the readOnly/idempotent annotations and add operational context annotations cannot express.

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 front-loaded with the most critical constraint (account required) and alternative tool, then purpose, then behavioral details. Each sentence carries information, though some depth details repeat the schema's enum descriptions. The '(More detail below.)' transition is slightly awkward but not substantially wasteful.

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 explains the return shape: findings packet with evidence, confidence, source, fetched_at, pipeworx:// citation, gaps[], contradictions[], hop field, and citation_uri semantics. It covers prerequisites, alternatives, depth options, timeouts, and grounding behavior, so an agent has everything needed to invoke and interpret results correctly.

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% with rich descriptions for both question and depth, so the baseline is 3. The description adds meaningful extras: latency ranges, account/plan constraints for depth, and how multi-step questions resolve in one call, which go beyond the schema's facet counts and recovery hops. It does not add new syntax, but these operational details help the agent choose depth correctly.

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 clear verb-resource pair: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources ... in ONE call', and distinguishes itself from sibling tools by noting 'this is NOT open-web search' and pointing to 'ask_pipeworx' for single lookups. It also describes the core mechanism (decompose into facets, route in parallel) so an agent knows exactly what the tool does.

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-to-use guidance: 'Best for broad/multi-part questions over structured data' with concrete examples, and explicit when-not-to-use: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead.' Account and plan conditions are stated up front, leaving no ambiguity about prerequisites or alternatives.

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