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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false; the description adds substantial behavioral context beyond that: account/payment requirements, parallel decomposition across 5,798 tools, the findings packet format with gaps[] and contradictions[], the guarantee that findings are never invented, semantic excerpting, and expected latency ranges. It discloses internal process details that an agent needs to trust and interpret results.

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 longer than the get_calls ideal, but the tool is genuinely complex, and the length is mostly justified by account caveats, output format, depth differences, and exclusion of open-web search. It is front-loaded with the most decision-critical facts: account required, alternative tool, and the structured-data scope. A few clauses are slightly redundant with the schema, but each sentence earns its place in practice.

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?

There is no output schema, so the description must explain return values; it does so thoroughly: 'findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding', plus gaps[], contradictions[], hop, and citation_uri for standard/thorough. It also covers latency, depth behavior, account tiers, and failures ('never invented'). No obvious missing context an agent would need to invoke or interpret this tool.

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 description coverage is 100%, and the input schema already explains the depth enum in detail (quick/standard/thorough, hop counts, contradictions, paid). The description restates some of this but does not add meaning beyond the schema. This is the baseline 3 case where the schema carries the parameter-semantics burden.

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', and clearly distinguishes itself from open-web search. It also names sibling alternatives, saying 'this is NOT open-web search' and 'For a single lookup use ask_pipeworx instead', so an agent can disambiguate it from related tools.

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 gives explicit when-to-use and when-not-to-use guidance: 'Best for broad/multi-part questions over structured data', 'For a single lookup use ask_pipeworx instead', and 'If you are not signed in, use ask_pipeworx instead — it works on every tier.' It also warns that depth:'thorough' needs a paid plan. This is exemplary routing to alternatives.

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