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

Beyond the annotations (readOnly, idempotent, openWorld, non-destructive), the description discloses important behaviors: auth/paid-tier requirements, parallel tool routing, gap reporting, never-inventing findings, hop fields, contradictions[], semantic excerpting rather than head-truncation, and expected latency. It also explains that citations are only returned when fetchable, which manages the agent's expectations about output reliability.

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 densely packed, and every sentence earns its place: auth, alternative routing, scope, mechanism, return format, best-use cases, depth semantics, citation guarantees, contradiction behavior, and latency. Critical information is front-loaded with the account requirement and fallback tool before the longer functional explanation.

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?

There is no output schema, but the description fully compensates by describing the return packet structure: verbatim evidence, confidence, source, fetched_at, pipeworx:// citation, gaps[], hop, citation_uri, and contradictions[]. It also covers error-ish cases like out-of-catalog topics and large-record handling, so an agent has enough context to invoke the tool 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%, so the baseline is 3, but the description adds meaning beyond the schema: it explains that depth:'thorough' requires a paid plan, that 'standard' adds gap recovery and contradiction scanning, and that broad/multi-part questions are appropriate because decomposition is the point. This supplements the schema's enum descriptions without being redundant.

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 clearly identifies the tool as grounded multi-source research over Pipeworx's structured data sources, with a specific verb ('research'), resource ('1499 STRUCTURED data sources'), and explicit non-scope ('this is NOT open-web search'). It also differentiates itself from ask_pipeworx and sibling lookup/search tools by emphasizing parallel decomposition and one-call delivery of a findings packet.

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 provides explicit when-to-use and when-not-to-use guidance: use it for broad/multi-part structured-data questions, and instead use ask_pipeworx for single lookups or when the topic is not in the structured catalog. It even gives an auth-based alternative ('If you are not signed in, use ask_pipeworx instead'), which is unusually actionable.

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