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

Beyond annotations, the description discloses rate limiting ('Rate-limited to 5 per identifier per day'), the return token behavior ('Filing without an account returns a `claim_token`'), and the internal processing cadence ('The team reads digests daily'). It also clarifies that it is free and doesn't count against tool-call quota, providing a thorough behavioral profile not captured in 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 longer than typical but every sentence adds necessary context, covering purpose, usage, exclusions, token flow, rate limits, and roadmap impact. It is logically structured, front-loading the core purpose before caveats. It earns its length, though it could theoretically be trimmed without losing critical info.

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?

Despite having no output schema, the description fully explains the return value (claim_token), how to use it later, and what to expect ('read whether it was fixed and what changed'). It also covers prerequisites (account optional), limitations (rate limit), and scope boundaries (only Pipeworx tools). This makes the tool self-contained and complete for an agent to invoke correctly.

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 already has 100% coverage with detailed parameter descriptions. The description adds practical usage semantics beyond schema, such as the claim_token round-trip pattern ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"})') and the instruction to describe issues in terms of Pipeworx tools rather than pasting end-user prompts. This enriches the semantic understanding beyond the schema 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 a clear action and target: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It further specifies the resource (tools served by this Pipeworx connection) and distinguishes it from other MCP servers' tools, making it unmistakably distinct from sibling research tools.

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 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 gives a clear exclusion: 'if the tool came from a different MCP server... file it with that server instead.' This fully covers when and when not to use.

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