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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint, so the safety profile is mostly covered. The description adds valuable behavioral context: it routes to internal tools, fills arguments, returns structured answers with stable pipeworx:// citation URIs, and can handle live news despite the open-world nature. It misses minor details like rate limits or failure modes, but those are not core to calling the tool correctly.

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 packs a lot of useful guidance, but it is overly long and has a somewhat rambling, uneven ending ('default entry point, works on every tier... a single fast call...') that feels like spliced internal notes. It front-loads the core usage advice, but the later routing rules are hard to parse and would benefit from tighter structure.

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 a single free-text parameter, no output schema, and rich annotations, the description covers the essential context: what domains it spans, when to prefer it, exact example questions, and when to pick a sibling. It lacks explicit guidance on expected output shape, but for an open-ended question-routing tool this is a minor gap.

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%, and the description reinforces that the question parameter is natural language, even providing representative examples. However, the description adds little beyond the schema's aliases, and it does not specify formatting expectations (e.g., language, length, whether to include context). Baseline 3 is appropriate because the schema already fully documents the parameters.

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 names a specific verb and resource ('routes the question to the right one of 5,798 tools across 1517 verified sources') and enumerates concrete domains and query phrasings, making it readily distinguishable from vague search-like siblings. It explicitly positions itself as the first-choice tool for authoritative structured data questions.

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 strong when-to-use guidance ('PREFER OVER WEB SEARCH', 'START HERE for most questions', specific trigger phrases like 'what is', 'look up', 'find') and mentions alternatives with explicit conditions: use ask_pipeworx_grounded when hallucination resistance is needed and deep_research for broad multi-part questions. This is model clarity.

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