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

Annotations already mark it read-only/idempotent, and the description adds significant behavioral context beyond that: account/payment gates, latency ranges, depth semantics, output shape (findings packet with evidence/confidence/source/fetched_at/citation), explicit gaps[], contradictions[], and non-invention guarantees. There is no contradiction with the 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 and packs a lot of detail, but it is front-loaded with the critical account gate and alternative first, then purpose, then usage and depth behavior. A few details (e.g., 5,718 tool count, 1,496 sources) are illustrative rather than essential, so it is not maximally 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?

For a complex tool with no output schema, the description is remarkably complete: it documents return fields, citation/fetchability semantics, gaps[], contradictions[], latency, auth requirements, and depth options. An agent has enough to select, invoke, and interpret the result without inferring critical behavior.

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% and the schema already documents both parameters well; the description adds practical value with latency estimates for depth options, payment implications for 'thorough', and examples of the broad multi-part questions 'question' should receive. This goes beyond the baseline but not by a huge margin.

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?

States a specific action ('Grounded multi-source research'), a specific resource scope ('Pipeworx's 1496 STRUCTURED data sources ... SEC filings, FRED/BLS, FDA, USPTO ...'), and a concrete mechanism (decomposes into facets, routes to 5,718 tools in parallel, returns a findings packet). It also distinguishes itself from open-web search and from ask_pipeworx.

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?

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 states the account and paid-plan preconditions for depth:"thorough".

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