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

Annotations provide no safety hints, so the description carries full burden. It discloses rate limiting ('Rate-limited to 5 per identifier per day'), quota behavior ('doesn't count against your tool-call quota'), the claim_token workflow for follow-up, and the fact that the team reads digests daily—all valuable behavioral context beyond 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?

Although lengthy, every sentence earns its place—from purpose to exclusions to workflow details. The description is front-loaded with the core purpose and flows logically through triggers, scope, formatting, claim_token, and constraints. No fluff.

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 4-parameter tool with no output schema, the description covers all critical aspects: what the tool does, when to use it, how to use parameters effectively, the claim_token follow-up mechanism, and operational constraints. The absence of an output schema is compensated by explaining what filing returns (claim_token).

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%, but the description adds meaning: it explains the claim_token usage pattern ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"})') and gives message guidance ('don't paste the end-user's prompt'). It also contextualizes the type enum by mapping it to concrete scenarios.

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: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It explicitly defines the feedback types (bug, feature, data_gap, praise) and distinguishes the tool from sibling tools by scoping it to Pipeworx connection tools only, with a unique claim_token mechanism.

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?

Provides explicit when-to-use triggers: '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 includes a clear when-not: tools from other MCP servers should be filed there instead, with guidance on identifying Pipeworx tools.

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