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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, and the description adds substantial behavior beyond that: account/payment requirements, parallel tool routing, findings packet structure with citation_uri, gaps[] for unanswered facets, contradictions[] for standard/thorough, semantic excerpting, and latency expectations. No contradiction with 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 dense and long, but nearly every sentence adds operational value given the tool's complexity and lack of an output schema. It is front-loaded with the account requirement and alternative, though some depth detail repeats the input schema and could be tightened or bulleted.

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 schema, the description is exceptionally complete: it covers authentication, pricing, data-source scope, how the tool works, what the response contains, how gaps and contradictions are handled, latency, and how citations are made resolvable. An agent has enough context to invoke it correctly and set expectations.

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 meaningful selection context: the thorough depth requires a paid plan, quick is single-hop with 3 facets, standard adds gap recovery and contradictions, and thorough adds a full iterative hop. It also gives example question phrasings that clarify what 'question' should look like.

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, with parallel decomposition and a findings packet. It explicitly distinguishes itself from open-web search and from sibling tools like ask_pipeworx, making tool selection unambiguous.

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?

It gives explicit when-to-use guidance: best for broad/multi-part questions over structured data, and for a single lookup it directs the agent to ask_pipeworx instead. It also handles the authentication edge case by saying unsigned-in users should use ask_pipeworx, which works on every tier.

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