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

Annotations already declare readOnly/idempotent/openWorld/non-destructive, and the description adds substantial context beyond them: auth tiers (thorough is paid), findings-packet shape (verbatim evidence, confidence, source, fetched_at, pipeworx:// citation), a never-invented gaps[] guarantee, contradictions[] scanning, semantic excerpting of long records rather than head-truncation, and 15-90s latency. Nothing contradicts 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 front-loads critical facts (account required, sign-in URL, fallback tool) and is information-dense, but it contains a clearly duplicated block: the 'Grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources... For a single lookup use ask_pipeworx instead' passage repeats, with the fallback sentence appearing three times. The same information could be conveyed in roughly half the length, forcing an agent to parse redundant claims.

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, this is essentially complete: return format, field semantics (hop, citation_uri, gaps[], contradictions[]), citation fetchability, excerpting behavior, latency, and auth prerequisites are all disclosed. An agent has everything needed to invoke the tool and interpret the result without guessing.

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 baseline is 3; the description earns a 4 by adding concrete example questions, per-depth latency expectations, and the paid requirement for thorough. Much of the depth-tier detail reinforces the schema's already-rich enum descriptions rather than replacing them, so the added value is real but supplementary.

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 verb and resource ('grounded multi-source research across Pipeworx's 1517 STRUCTURED data sources') plus a distinctive mechanism (decomposes into facets, routes in parallel to 5,798 tools). Explicitly disambiguates from open-web search and from the ask_pipeworx sibling, so an agent can tell them apart without reading the schema.

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 guidance with two concrete example questions ('compare X and Y's regulatory + financial exposure'), and names the alternative twice: 'For a single lookup use ask_pipeworx instead' and 'If you are not signed in, use ask_pipeworx instead — it works on every tier.' The depth enum also tells the agent which variant matches cheap vs. thorough needs.

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