report_issue_or_feedback

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

The description adds behavioral context beyond the readOnlyHint annotation, such as the timing and scope of use (proactive, mid-task). It does not contradict the annotation. While it doesn't detail all side effects, it provides sufficient guidance for using the tool appropriately.

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 concise (approx. 130 words) and well-structured. It front-loads the primary purpose, follows with usage guidance, and uses bullet points for clarity. Every sentence contributes meaningful information without redundancy.

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?

Given the tool's simplicity (3 parameters, 2 required, no output schema), the description is thorough. It covers when, why, and how to use the tool, including examples. The optional context field is explained, though a bit more detail on its structure could enhance completeness, but it is still adequate.

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 schema covers all parameters (100% coverage), but the description adds significant value by clarifying the intent of the 'message' parameter with good and bad examples ('GOOD: ... / BAD: ...'). This helps the agent understand the semantic boundary of acceptable input, which is not evident from the schema alone.

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: reporting bugs or feedback about Prisme.ai MCP tools. It uses the specific verb 'report' and identifies the resource ('issue_or_feedback'). It distinguishes itself from sibling tools by being the only tool for this function.

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 explicitly instructs proactive use ('Use PROACTIVELY when you encounter issues - even mid-task. Don't wait for task completion.') and lists specific triggers (tool errors, misleading documentation, missing constraint information). It also clearly delineates what to report (guidance improvements) vs. what not to (API behavior changes) with concrete examples.

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