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

Beyond the annotations (which only say readOnlyHint=false, etc.), the description discloses critical behavioral traits: filing returns a claim_token for later retrieval, rate-limited to 5 per identifier per day, free with no quota impact, and the team reads digests daily. These details are not inferable from the schema or annotations and greatly help the agent set expectations.

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 carries necessary decision-supporting information. It is front-loaded with purpose and use cases, then exclusions, then token/rate-limit details. The structure is logical and no sentence is wasted; it earns its length.

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 covers what the agent needs: return behavior (claim_token), how to follow up, constraints (rate limit, free), and what not to do. It also ties into the broader catalog by using sibling tool names and pack/tool context, making it complete for a feedback tool.

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. The description adds meaningful guidance beyond the schema: it explains that claim_token must be used with no other arguments, and instructs users to 'Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt,' which clarifies the message parameter's intended content. This extra context justifies a score above baseline.

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 specific verb-resource pair ('Tell the Pipeworx team') and states the exact purpose: 'something is broken, missing, or needs to exist.' It distinguishes this from sibling tools like ask_pipeworx and discover_tools by framing it as feedback reporting rather than querying or discovery, making its role unambiguous.

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 provides explicit when-to-use guidance: bug, feature/data_gap, praise. It also gives a clear when-not-to-use: 'if the tool came from a different MCP server... file it with that server instead.' It even clarifies how to disambiguate ('Not sure? Pipeworx tool names are the ones this connection lists'), which is strong alternative guidance.

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