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

Annotations already mark the tool as read-only, open-world, idempotent, and non-destructive. The description adds substantial behavior beyond that: parallel facet decomposition, routing to 5,798 tools, explicit gaps[] with never-invented findings, contradictions[] for standard/thorough, fetchable pipeworx:// citation URIs, semantic excerpting instead of head-truncation, latency expectations, and auth/tier restrictions. This all aligns with the annotations; no contradiction.

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 dense and front-loaded with the most decision-critical fact: account required, and use ask_pipeworx if not signed in. Every major behavior is stated, but it is a long wall-of-text paragraph with some redundancy against the scheam's depth description (e.g., contradictions[] and gap-recovery). A structured list would improve scannability while preserving the content.

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?

For a complex research tool with no output scheam, the description fully covers input syntax, output shape, failure representation (gaps[]), contradiction detection, citation fetchability, latency, auth/tier restrictions, and usage boundaries. An agent has enough information to decide whether to call it, how to call it, 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?

Scheam coverage is 100%, so the baseline is 3. The description adds value beyond the scheam by giving example multi-part questions, tying the 'thorough' depth to a paid plan, explaining why depth levels matter ('multi-step questions resolve in one call'), and providing latency expectations per depth. It doesn't redefine the parameters, but it enriches the practical meaning of question and depth.

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 action — multi-source grounded research across Pipeworx's structured data sources — and specifies the output format (findings packet with citations, gaps, contradictions). It explicitly contrasts with open-web search and with ask_pipeworx, so an agent can distinguish it from siblings without opening schemas.

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 usage boundaries: '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'. It also states the account/tier prerequisite, making the selection criteria actionable.

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