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

Annotations provide no safety hints (all false), so the description carries the full burden. It discloses key behavioral traits: 'Filing without an account returns a claim_token', the ability to poll status with that token, rate limiting ('Rate-limited to 5 per identifier per day'), and cost ('Free; doesn't count against your tool-call quota'). It even explains the team's reading cadence and roadmap impact.

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 dense paragraph, but every sentence earns its place: purpose, use cases, exclusions, token mechanics, rate limits, and cost. It is front-loaded with the core action and branches into important caveats. While longer than average, the complexity of the tool justifies the 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?

For a tool with no output schema and four parameters, the description fully covers the context needed to invoke it correctly: when to use it, what to include in the message, how to use claim_token for follow-up, rate limits, and quota behavior. It even notes the team reads digests daily and that feedback influences roadmap, which helps the agent understand the tool's impact.

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?

The input schema already covers all parameters comprehensively (100% coverage), so the baseline is 3. The description adds beyond the schema by explaining the claim_token round-trip ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"})') and instructing users to describe issues in terms of Pipeworx tools rather than pasting end-user prompts. This enriches parameter understanding without duplicating schema content.

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 states the tool's purpose: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It identifies the resource (Pipeworx team) and the action (sending feedback), and distinguishes it from sibling tools like ask_pipeworx by focusing on reporting issues rather than asking questions.

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: '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: 'ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server... file it with that server instead.' This is exemplary usage guidance.

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