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

The description goes well beyond the annotations by explaining decomposition, parallel routing, the findings packet shape, gap handling ('never invented'), contradictions[], semantic excerpting, fetchable citation URIs, and expected latency. It also discloses tier-dependent behavior and what makes 'thorough' different from 'standard.' No contradiction with the readOnly/openWorld/idempotent annotations.

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 and dense, but nearly every sentence adds operational value: auth requirements, alternatives, source scope, output structure, limitation handling, citation guarantees, and timing. It is front-loaded with the account requirement and the key 'NOT open-web search' distinction, though tighter paragraph structure or headings would improve scannability.

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 agent will receive: a findings packet with evidence, confidence, source, fetched_at, stable citations, explicit gaps[], contradictions[] for certain depths, and a hop field. It also covers large-record handling and latency, making the tool fully understandable without needing an output schema.

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 meaningful context: 'question' is clarified as naturally allowing broad/multi-part phrasing, and 'depth' is tied to hop count, gap recovery, contradiction scanning, paid plan requirements, and latency. This goes beyond the schema descriptions, though the schema already carried much of the depth-level detail.

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 names a specific resource and operation: grounded multi-source research over 1,517 structured data sources in one call, and explicitly differentiates itself by saying 'this is NOT open-web search.' It also contrasts with single-lookup tools by recommending ask_pipeworx, so an agent can easily distinguish it 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?

Usage conditions are explicit: an account is required, the free tier is limited, 'thorough' requires a paid plan, and if signed out the agent should use ask_pipeworx instead. It also states the best-use case ('broad/multi-part questions over structured data') and explicitly excludes single lookups, including the alternative to use.

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