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

Annotations already declare read-only, open-world, idempotent behavior. The description adds meaningful behavioral context: it is a routing layer that fills arguments automatically, spans 5,743 tools and 1500 verified sources, and returns citations via stable pipeworx:// URIs. This goes beyond what annotations alone convey, with no contradiction.

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 longer than average but logically organized: scope, behavior, trigger phrases, examples, and a final routing instruction. It is not wasteful overall, though the emphatic capitalization and the slightly awkward final caveat keep it from being a 5.

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?

Even without an output schema, the description fully covers what the tool accepts, what it returns, when to use it, and how it behaves internally. An agent has enough information to select this tool and invoke it with a suitable natural-language question.

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 coverage is 100%, so the baseline is 3, but the description adds useful parameter-level guidance: the input is a plain natural-language question, the tool fills arguments itself, and the many domain examples clarify what kinds of questions are 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 function: routing natural-language questions to the right tool and returning structured answers with stable pipeworx:// citation URIs. It gives concrete domains and examples, but it does not explicitly distinguish ask_pipeworx from the sibling variants ask_pipeworx_beta and ask_pipeworx_grounded.

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 explicitly says to prefer this tool over web search, lists triggering phrasings such as 'what is', 'look up', 'find', and 'get the latest', and even says to use it even when web search could also answer. It also provides a clear exclusion: unless the agent is porting analysis from another framework and already knows a specific tool.

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