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

Annotations already mark it read-only, idempotent, non-destructive, and open-world; the description adds substantial behavior beyond that: auth/paid-tier requirements, 15-60s (up to ~90s) latency, parallel decomposition, explicit gaps[] with 'never invented', contradictions[] for standard/thorough, semantic excerpting rather than head-truncation, and the guarantee that citation_uri is fetchable whenever present. No statement contradicts the 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?

Long (~340 words) but densely informative and front-loaded: the account-required gate and the fallback to ask_pipeworx appear in the first two sentences. Almost every sentence earns its place; the clearest waste is 'use ask_pipeworx instead — it works on every tier' appearing twice nearly verbatim, and depth behavior is paraphrased in both prose and schema.

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, the description fully specifies the return contract: findings packet with verbatim evidence, confidence, source, fetched_at, stable pipeworx:// citation, gaps[], contradictions[], and hop field. Combined with annotations covering the safety profile and a schema covering both parameters, nothing an agent needs to call it correctly or interpret results is missing.

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. The description adds real value above the schema: it ties depth to cost and latency (thorough needs a paid plan, up to ~90s with the follow-up + contradiction pass) and to behavioral outcomes (gap recovery, lead-chasing) that the enum alone doesn't convey. The increment is modest because the schema's own depth description is already rich.

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 and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources ... in ONE call.' It distinguishes itself from related tools by insisting 'this is NOT open-web search' and by contrasting with ask_pipeworx for single lookups. An agent can tell what this tool does and roughly what it is not without opening any sibling schema.

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?

Gives explicit when-to-use guidance ('Best for broad/multi-part questions over structured data') with concrete example questions, plus two explicit when-not-to-use routes: not signed in → ask_pipeworx, and single lookup → ask_pipeworx. This is textbook routing guidance — an agent can select the tool by matching question complexity and auth state.

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