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

Annotations provide only generic hints (readOnlyHint: false, etc.), but the description adds substantial behavioral context: rate-limiting ('Rate-limited to 5 per identifier per day'), cost ('Free; doesn't count against your tool-call quota'), the claim_token mechanism for later follow-up, and the team's daily digest process. It also clarifies that reporting cross-server issues is futile, which helps set expectations. No contradiction with 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 information-dense yet well-structured: it opens with purpose, moves to use cases, exclusions, formatting advice, token mechanics, and side effects. Every sentence adds value, with no fluff or repetition. The length is justified by the breadth of operational guidance provided.

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 low-complexity feedback tool with no output schema, the description covers all necessary context: when to use, what to include, rate limits, quota, token follow-up, and the fact that feedback influences roadmap. There is no missing critical information for the agent to decide, invoke, and interpret results 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 description coverage is 100%, and the schema already explains each parameter thoroughly (e.g., claim_token: 'Read the reply to a report you filed earlier...'). The description reaffirms the claim_token usage but does not significantly augment the parameter meanings beyond what the schema provides. Since the schema carries the full burden, a baseline 3 is appropriate.

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 function: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It uses a specific verb+resource and is distinguishable from sibling tools like ask_pipeworx (which answers questions) and discover_tools (which lists tools), making its purpose 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?

Provides explicit when-to-use criteria ('Use when a tool returns wrong/stale data...'), when-not-to-use exclusions ('ONLY for tools served by this Pipeworx connection... file it with that server instead'), and even guidance on what to include ('Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt'). 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.