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

Annotations already declare the tool read-only, open-world, and idempotent, and the description adds meaningful behavioral detail: it routes across a large toolset, auto-fills arguments, returns structured answers with stable pipeworx:// citation URIs, works on every tier, and is a single fast call. No contradiction exists between the description and 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 but front-loaded with the most important guidance ('PREFER OVER WEB SEARCH') and packs in usage rules, examples, and escalation paths. Some redundancy exists in the extensive domain enumeration, but most sentences carry useful routing information.

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?

Given the simple schema of a single question string and no output schema, the description fully covers what the tool does, when to use it, when to step up to alternatives, what outputs to expect, and example query formats. An agent has enough context to call it correctly in the default case.

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 all six parameters are aliases of the single `question` string, so the schema fully documents the parameters. The description offers natural-language guidance and examples but does not add new parameter-level semantics beyond what the schema provides.

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 the tool routes a natural-language question to one of 5,743 tools across 1,500 verified sources, fills arguments, and returns a structured answer with citation URIs. It distinguishes itself from ask_pipeworx_grounded and deep_research by naming them explicitly.

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 when-to-use guidance: prefer over web search for factual questions about real-world entities, events, or numbers. It also names alternatives for edge cases — ask_pipeworx_grounded for hallucination-resistant answers and deep_research for broad multi-part questions — and provides concrete example queries.

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