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

Annotations already mark the tool read-only, idempotent, open-world, and non-destructive, and the description adds substantial behavioral context: account/tier requirements, no-invention gap reporting, resolvable citation_uri only when the source emits one, contradictions[] on deeper depths, semantic excerpting rather than head-truncation, and expected latency. No statement conflicts with 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?

The description is long but information-dense, with the critical account prerequisite front-loaded before the core capability and every clause covering a real operational or behavioral fact. Some depth-mode details repeat the schema near the end, which prevents a perfect score, but there is no filler or vague marketing language.

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?

Given there is no output schema, the description compensates well by enumerating the return packet (verbatim evidence, confidence, source, fetched_at, stable pipeworx:// citation), gap and contradiction behavior, fetchable citation_uri semantics, excerpting behavior, and latency. An agent has enough information to decide whether to call this tool 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?

The schema already covers both parameters at 100%, including detailed depth-mode semantics (quick/standard/thorough hop behavior, contradictions, paid plan) and question natural-language semantics. The description mostly restates these schema details; it adds usage framing but little parameter-level meaning beyond what the schema already provides.

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 operation: grounded multi-source research across Pipeworx's 1517 structured data sources in one call, with decomposition and parallel routing. It also distinguishes itself from open-web search and from single-lookup siblings, so an agent can classify this tool cleanly.

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 selection criteria: best for broad/multi-part structured-data questions, and 'For a single lookup use ask_pipeworx instead.' It also handles the auth edge case directly: 'If you are not signed in, use ask_pipeworx instead — it works on every tier.' This names the alternative and the conditions that disambiguate it.

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