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

Annotations already declare readOnly, openWorld, and idempotent hints, and the description adds substantial behavioral context beyond them: auth requirements, paid-plan gate for 'thorough', NOT open-web search, explicit gaps[] when facts are missing, contradictions[] scanning, semantic excerpting, latency expectations, and fetchable citation URIs. No contradiction with annotations; the description enriches the safety and operational profile.

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 informative, with each major behavioral fact (auth, alternatives, output shape, gaps, latency) earning its place. Some clauses are redundant (stable pipeworpx:// citation vs citation_uri) and the paragraph format could be more scannable, but it remains well-organized and front-loaded with the most critical operational constraints.

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?

Despite having no output schema, the description thoroughly explains what the tool returns: a findings packet with verbatim evidence, confidence, source, fetched_at, citations, gaps[], contradictions[], and hop fields. It also covers latency, auth prerequisites, depth behavior, and when it will return empty gaps, making the description sufficient for an agent to select, invoke, 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 both parameters are well described in the schema, so the baseline is 3. The description adds extra meaning for 'question' by noting broad/multi-part questions are acceptable and giving concrete examples, and it clarifies how depth tiers affect behavior and cost. It mostly reinforces the schema's depth enum, but the additional usage context justifies a 4.

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, and mechanism: 'Grounded multi-source research across Pipeworx's 1506 STRUCTURED data sources' in one call, with decomposition and parallel routing. It explicitly distinguishes itself from open-web search and names the sibling alternative, ask_pipeworx, so an agent can differentiate without inspecting other tools.

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 structured-data questions, and explicitly says to use ask_pipeworx instead for single lookups, breaking/current-news topics, or when not signed in. Also explains depth-level behavior and second-hop iteration, so the selection criteria between this tool and alternatives are fully spelled out.

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