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

Annotations already declare read-only, open-world, idempotent, non-destructive behavior. The description adds useful behavioral context beyond those flags: it describes routing across 5,738 tools, automatic argument filling, structured output, and stable pipeworx:// citation URIs. It does not contradict 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 opening is front-loaded and effective, but the description degenerates into a long repeated tail of the same 'START HERE... Examples...' block. The repetition adds no information and substantially bloats the text, violating the every-sentence-earns-its-place standard.

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 single-string-parameter, read-only router tool, the description is contextually complete: it specifies domains, trigger language, routing behavior, output shape, and citation format. With no output schema, the explicit mention of 'structured answer with stable pipeworx:// citation URIs' is sufficient.

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?

The schema covers all six aliases and already explains that the value is a natural-language question, so the baseline is 3. The description adds value with trigger phrases and concrete example questions that help an agent recognize what to pass, even though it does not add new parameter format details.

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 clear, specific purpose: route a natural-language question to the right underlying tool and return a structured, cited answer. It strongly signals coverage across many data domains, but it does not differentiate ask_pipeworx from siblings like ask_pipeworx_beta, ask_pipeworx_grounded, or deep_research.

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 usage guidance: prefer it over web search, use it for factual/lookup questions, and includes concrete trigger phrases and examples. However, it gives no when-not-to-use conditions or named alternatives among the sibling tools, so agents must infer boundaries versus deep_research and related tools.

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