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

Annotations only declare read-only, open-world, idempotent, and non-destructive hints; the description adds far more: account requirements, paid tier for thorough, parallel decomposition across 5,798 tools, explicit gaps[] with a 'never invented' guarantee, resolvable citation_uri behavior, contradictions[] for standard/thorough, semantic excerpting, and latency expectations. This far exceeds annotation coverage.

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 front-loaded with the auth gate and alternative tool before anything else, and nearly every sentence adds useful information. However, it is long and repeats some schema content and the 'one call' point multiple times, so it is not perfectly concise.

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 carries the full burden of explaining return values, and it does: findings packet with verbatim evidence, confidence, source, fetched_at, citation_uri, hop, gaps[], contradictions[], and semantic excerpts. It also covers auth, pricing, depth modes, data-source scope, and timing. Nothing essential 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, but the description adds operational meaning to the depth parameter: thorough requires a paid plan, standard/thorough return contradictions[], and latency varies by depth (15-60s, thorough up to ~90s). It also gives a concrete example of the kind of question the question parameter should receive.

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 names a specific verb and resource: 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources in ONE call.' It also explicitly distinguishes itself from open-web search and from the ask_pipeworx sibling: 'For a single lookup use ask_pipeworx instead.' The purpose is 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 gives explicit when-to-use guidance: 'Best for broad/multi-part questions over structured data.' It also gives explicit when-not-to-use guidance: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead.' This is strong routing behavior with named alternatives.

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