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

The description goes far beyond annotations, disclosing rate limits ('Rate-limited to 5 per identifier per day'), cost ('Free; doesn't count against your tool-call quota'), and the claim_token flow ('Filing without an account returns a claim_token; pass it back later... to read whether it was fixed'). It also explains the team's review process ('reads digests daily and signal directly affects roadmap'). No contradiction with 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 a single well-organized paragraph that front-loads the core purpose, then flows through usage conditions, exclusions, message guidance, token mechanics, and rate limits. Every sentence adds necessary information with no filler or repetition, making it dense but efficient.

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?

Given the tool has 4 parameters, zero required, no output schema, and non-trivial behaviors, the description covers all critical aspects: return values (claim_token and status), rate limiting, scope restrictions, and message formatting. It leaves no major functional gap for an agent to make a correct call.

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?

While the schema covers all parameters, the description enriches them with usage context: it advises 'Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt,' and gives a concrete syntax example for claim_token usage. It also clarifies how the 'type' field maps to real scenarios, which is more than the schema's enum definitions alone.

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 opens with 'Tell the Pipeworx team something is broken, missing, or needs to exist,' which immediately identifies the verb and resource. It clearly differentiates from siblings like ask_pipeworx or discover_tools by focusing on feedback submission, not information retrieval or tool discovery.

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?

Explicit when-to-use guidance is given: 'Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise).' It also provides clear exclusions: 'ONLY for tools served by this Pipeworx connection... if the tool came from a different MCP server... file it with that server instead,' and suggests an alternative action for uncertain cases.

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