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

Annotations already cover readOnly, openWorld, idempotent, and non-destructive hints. The description adds context beyond these: it notes that the tool fills arguments, routes to many tools, works on every tier, and returns citations with pipeworx:// URIs. It does not detail rate limits or error behavior, but given the annotation coverage, this is a strong disclosure of behavior.

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 lengthy but deliberately structured: it opens with a strong directive ('PREFER OVER WEB SEARCH'), then provides rationale, examples, and explicit routing to alternatives. Every sentence adds value, no fluff or redundancy. While not as concise as a two-sentence description, the structure is clear and front-loaded, making it easy for an agent to parse the critical usage guidance quickly.

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 tool that aggregates thousands of sources, the description covers all necessary context: what it does, when to use it, how it differs from siblings, example queries, and the nature of the returned data (structured answer with citations). It even addresses edge cases like breaking news and free-account tiers. Without an output schema, this description provides sufficient completeness for an agent to call it correctly.

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 description coverage is 100%, with all six parameters being aliases for the single required 'question' field, each documented directly. The description provides a natural-language explanation and examples, but these largely mirror the schema's own description ('Your question or request in natural language'). No additional semantic depth is added beyond what the schema already conveys, so the baseline of 3 is appropriate.

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 clearly states what the tool does: routes a natural-language question to one of 5,718 tools across 1,496 sources and returns a structured answer with stable citation URIs. It explicitly contrasts with sibling tools (ask_pipeworx_grounded, deep_research) by naming them and their specific use cases, leaving no ambiguity about the tool's role.

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?

Provides explicit guidance on when to prefer this tool over web search, lists example query types and specific phrasings ('what is', 'look up', 'find'), and names alternatives with conditions for escalation (e.g., 'Step up only when needed: for a hallucination-resistant single answer... use ask_pipeworx_grounded'). Also distinguishes it from deep_research for broad/multi-part questions, so the agent has clear decision criteria.

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