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

Annotations already mark this as readOnly, openWorld, and idempotent, and the description adds rich context beyond that: account/paywall requirements, parallel decomposition across 5,798 tools, gaps[] that are never invented, contradictions[] for standard/thorough depths, citation_uri presence conditions, semantic excerpting of large records, and latency expectations of 15-90s. 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 well-structured, front-loading the critical account requirement and alternative tool before explaining mechanism, output, and depth behavior. Every sentence adds relevant information, though there is some redundancy with the schema's depth descriptions and an awkward 'Second-hop iteration:' phrase that prevent a perfect structure score.

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?

With no output schema, the description fully explains the findings packet (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), gaps[], contradictions[], hop field, and citation_uri resolvability conditions. It also covers prerequisites, the alternative tool, and expected latency, giving an agent everything needed to invoke and interpret the tool correctly.

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 input schema covers both parameters thoroughly, including the depth enum values and their behavioral implications, so the description carries little additional parameter meaning. The description mostly repeats depth semantics (paid thorough, contradiction scans) already present in the schema, adding only minor context like latency expectations tied to depth. Baseline 3 is appropriate.

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 verb and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources' in one call, clearly distinguishing it from open-web search and naming the ask_pipeworx sibling. It explains the decomposition and parallel routing mechanism, making the tool's function unmistakable.

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?

The description explicitly says 'Best for broad/multi-part questions over structured data' and 'For a single lookup use ask_pipeworx instead.' It also provides an exclusion condition by stating 'If you are not signed in, use ask_pipeworx instead — it works on every tier,' which gives clear when-to-use and when-not-to-use guidance with a named alternative.

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