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

Annotations already establish read-only, idempotent, open-world behavior. The description adds useful behavioral context beyond that: it routes internally, fills arguments, returns a structured answer with stable citation URIs, and works on every tier as a single fast call. It does not discuss failure modes or rate limits, but those are not critical given the annotation set.

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 dense but well-structured: it front-loads the preference instruction, gives concrete categories and examples, then clearly separates 'START HERE' from 'Step up only when needed'. Each sentence adds practical value for tool selection and invocation.

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 broad default entry-point tool, the description is remarkably complete: it covers when to use it, what it returns, how it differs from alternatives, examples of queries, and even news routing behavior. No output schema exists, but the description sufficiently describes the expected structured citation return.

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 schema documents every alias for the question parameter. The description itself does not add parameter-level guidance, but with full schema coverage the baseline of 3 applies. The schema examples further clarify expected input formats.

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?

Description states exactly what ask_pipeworx does: it takes natural-language factual questions, routes them to one of 5,743 source tools, and returns structured answers with pipeworx:// citation URIs. It also clearly positions itself as the default entry point versus siblings like ask_pipeworx_grounded and deep_research, so an agent can distinguish them.

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?

Gives explicit when-to-use guidance: prefer over web search for a wide range of factual/current-data questions, and use specific trigger phrases like 'what is', 'look up', 'find', 'current'. It also provides clear alternatives: use ask_pipeworx_grounded for a grounded single answer and deep_research for broad/multi-part questions.

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