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

Annotations already mark this as read-only, open-world, idempotent, and non-destructive. The description adds meaningful behavioral context: it routes to one of thousands of tools, fills arguments, returns a structured answer with stable citation URIs, and is described as a fast default entry point that works on every tier. That goes well beyond 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 is long but tightly packed with actionable information: the main directive is front-loaded, followed by supported domains, examples, alternatives, and stepping-up criteria. There is no filler or redundant repetition relative to the structured schema and annotations.

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 read-only query tool with no output schema, the description covers purpose, trigger phrases, example queries, return characteristics, supported data domains, tier behavior, and how it relates to sibling tools. Nothing essential is missing for an agent deciding whether to call it and what to pass.

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%, so the schema fully documents the single meaningful parameter and its aliases. The description clarifies that the question is natural language and gives examples, but it does not add meaning beyond the schema's own parameter description. Baseline 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 identifies a specific verb and resource: it routes questions to a large verified corpus and returns structured answers with stable pipeworx:// citation URIs. It distinguishes itself from web search and from siblings like ask_pipeworx_grounded and deep_research, so an agent can select it without opening schemas.

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 explicitly says to prefer this over web search for a broad list of factual question types and gives concrete example queries. It also names the exact conditions for stepping up to ask_pipeworx_grounded or deep_research, providing clear when-to-use and when-not-to-use guidance.

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