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

Annotations only provide hints (readOnly=false, destructiveHint=false) which don't conflict. The description adds rich behavioral context: filing without an account returns a claim_token for later lookup, the team reads digests daily, rate-limited to 5 per identifier per day, and does not count against quota. This goes well beyond the structured hints.

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?

Although longer than minimal, every sentence earns its place: purpose, usage, exclusions, follow-up mechanism, and operational notes. It is front-loaded with the core 'tell us' action and maintains clear structure, making the length appropriate for the complexity.

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?

The description covers all essential aspects for correct invocation: when to use, what to write, how to handle follow-up via claim_token, and constraints (rate limit, quota). Given the 4-parameter schema with an optional nested object and no output schema, the description is fully sufficient for an agent to use the tool 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 descriptions already cover 100% of parameters, so the baseline is 3. The description adds value by explaining the claim_token workflow (pass it back later to check status) and content guidance ("don't paste the end-user's prompt"), which complements the schema without repeating it.

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 verb+resource: "Tell the Pipeworx team something is broken, missing, or needs to exist" and enumerates feedback types (bug, feature/data_gap, praise). It distinguishes itself from sibling research/Polymarket tools by focusing on feedback about Pipeworx itself, not market data.

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?

Explicitly states when to use: "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)." Also gives an exclusion: "if the tool came from a different MCP server... file it with that server instead," and even provides a decision aid ("Not sure? Pipeworx tool names are the ones this connection lists.").

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