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

Annotations already declare read-only, open-world, and idempotent hints, and the description adds substantial behavioral context beyond them: authentication and tier requirements, expected latency (15-60s or up to ~90s), the gaps[]/contradictions[] return fields, always-fetchable citation_uri behavior, passage-level excerpting, and the explicit 'never invented' guarantee. No contradictions with the annotations exist.

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?

Every sentence carries essential information and the account-required gating is front-loaded, which is ideal for agent parsing. The content is dense but delivered as one long run-on paragraph with many parenthetical asides, making it slightly less scannable than a structured layout would be. This is a minor cost given the high information density.

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 covers the return contract: findings packet with verbatim evidence, confidence, source, fetched_at, citation, gaps[], contradictions[], and hop field. It also covers auth, cost, latency, parallel execution, and failure modes. For a 2-parameter tool this is complete enough for an agent 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%, providing a baseline of 3, and the description adds meaningful depth beyond the schema: it clarifies that 'question' can be broad/multi-part and details the behavioral differences between depth values (standard adds a gap-recovery hop, thorough chases leads, standard/thorough return contradictions[]). This adds real value rather than merely restating the 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?

The description states a specific verb and resource: 'Grounded multi-source research across Pipeworx's 1506 STRUCTURED data sources... in ONE call' and explicitly distances itself from open-web search. It also names what it returns (findings packet with gaps[]) and gives concrete example questions, so an agent can clearly identify the tool's purpose and differentiate it from siblings like ask_pipeworx.

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 offers explicit routing guidance: 'If you are not signed in, use ask_pipeworx instead', 'Best for broad/multi-part questions over structured data', 'For a single lookup use ask_pipeworx', and for breaking news 'prefer ask_pipeworx'. It also discloses the account requirement and that depth:'thorough' needs a paid plan, leaving no ambiguity about when this tool should be selected.

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