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

Beyond the read-only and idempotent annotations, the description discloses meaningful behavior: it autonomously routes to many tools, fills arguments, returns structured answers, provides stable citation URIs, and is one fast call. This gives the agent a solid model of what happens when the tool is invoked.

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 its most important instruction ('PREFER OVER WEB SEARCH') and then progresses through purpose, use cases, examples, and escalation paths. Some repetition exists between 'prefer over web search' and 'even if web search could also answer it', but each section earns its place for a broad routing tool.

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 meta-routing tool with no output schema and a single required natural-language parameter, the description is complete: it covers domains, trigger phrasings, examples, output characteristics, speed, citation behavior, and when to step up to sibling tools. An agent has enough information to invoke it appropriately in most situations.

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 already provides 100% coverage for all parameters, including aliases for question. The description goes further by clarifying that a full natural-language question is the expected input, via trigger phrases and concrete examples, which helps the agent formulate better values for the question parameter.

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's purpose: it takes natural-language factual questions, routes them across 5,798 tools, fills arguments, and returns structured answers with pipeworx:// citations. It distinguishes itself from web search and from sibling tools like ask_pipeworx_grounded and 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 when-to-use guidance: prefer over web search for factual data questions, use for phrasings like 'what is', 'look up', 'find', 'get the latest'. It also names concrete alternatives and conditions, such as ask_pipeworx_grounded for verification and deep_research for broad/multi-part questions, so routing decisions are clear.

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