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

Annotations declare readOnly/openWorld/idempotent/non-destructive, and the description adds substantial behavioral context beyond those: auth requirements, paid tier for thorough, parallel decomposition, explicit gaps[] with no invention, contradictions[] for standard/thorough, stable pipeworx:// citations, semantic excerpting, and expected latency. No contradiction with annotations exists.

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 information-dense, front-loading the critical account requirement before use guidance. Some phrasing is convoluted with nested parentheticals and wordplay-like repetition ('stable citation... a citation you get back is always fetchable'), which slightly hurts scannability, but nearly every sentence carries unique operational value.

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?

For a tool with no output schema and only two parameters, the description fully compensates: it explains the return packet shape (evidence, confidence, source, fetched_at, citation_uri, gaps, contradictions, hop), timeout expectations, and how large records are handled. An agent has everything needed to decide whether to invoke it and what to expect back.

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 goes further: it explains what depth levels do in behavioral terms (quick=3 facets, standard adds gap recovery, thorough is paid and adds lead-chasing) and clarifies that the question parameter accepts broad/multi-part natural language because decomposition is the point. This adds real value beyond 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 clear specific function: grounded multi-source research across 1,517 structured data sources in one call, decomposing the question and routing facets to 5,798 tools in parallel. It explicitly distinguishes itself from open-web search and from ask_pipeworx for single lookups, so an agent can reliably tell it apart from siblings.

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?

It gives explicit when-to-use guidance: best for broad/multi-part questions over structured data, and explicitly says to use ask_pipeworx instead when the user is not signed in or for a single lookup. It also explains depth-tier differences so the agent can choose the right depth level. This is excellent routing guidance.

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