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

The description goes well beyond the annotations, explaining how the tool decomposes questions, routes to 5,718 tools in parallel, returns verbatim evidence with confidence and citations, never invents gaps, includes contradictions[] for certain depths, semantically excerpts records, and has expected latency. It also notes account/tier implications. No contradiction with 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 each sentence adds operational information an agent needs: account requirements, alternatives, output format, depth semantics, timing, and citation behavior. It is front-loaded with the most critical gate (account required) and the alternative tool. Minor redundancy exists around the gap-recovery behavior described in both the second paragraph and the depth parameter semantics, but overall it earns its length.

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 no output schema, the description fully explains return contents: findings packet with verbatim evidence, confidence, source, fetched_at, pipeworx:// citation, gaps[], contradictions[], and hop field. It covers parameters, output, error/edge behavior, account requirements, latency, and alternative tools. Nothing an agent needs to invoke or interpret this tool correctly 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%, but the description adds meaningful detail beyond the enum values: quick/standard/thorough are tied to hop counts, gap recovery, contradiction scans, and paid tiers. It also clarifies that the question parameter should be natural language and that broad/multi-part questions are fine. This materially enriches what the schema alone conveys.

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 1496 STRUCTURED data sources...in ONE call." It explicitly distinguishes itself from open-web search and from ask_pipeworx, and gives concrete example questions. This makes the tool's purpose unmistakable relative to its 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: "ACCOUNT REQUIRED," "If you are not signed in, use ask_pipeworx instead," and "For a single lookup use ask_pipeworx instead." It also states when the tool is best: "broad/multi-part questions over structured data." This gives an agent clear decision criteria for choosing this tool over alternatives.

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