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

With no annotations provided, the description carries the full burden of behavioral disclosure. It openly states the tool does not execute, describes the approval queue flow, and specifies the return value structure ({id, action_type, status}) or an error. This is transparent about the async and non-authoritative nature, though it could add more context about error conditions or queue status.

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, with three sentences that front-load the key point (no execution) and provide necessary context. It avoids repetition and wastes no words. Slightly verbose in the parameter explanation, but overall well structured.

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 that the tool has an output schema and a clear description of workflow, the description is complete enough for an agent to call it correctly. It covers the non-execution aspect, the approval queue, the return format, and the action_type registration. It does not mention prerequisites or permissions, but these are not critical for basic invocation.

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 0%, so the description must compensate. It thoroughly explains action_type with concrete examples (jira.create_issue, etc.), but does not elaborate on the meaning of title, evidence, or description parameters. While title and description are likely self-explanatory, evidence remains ambiguous without guidance. Partial compensation only.

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 verb ('Propose') and resource ('a new action'), and explicitly notes it 'does NOT execute it'. It also differentiates from related tools by explaining that approve/execute are intentionally not exposed over MCP, making the tool's purpose unambiguous even among siblings.

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 clearly explains that the action lands in an approval queue for human review, and that execution is not possible through MCP. This gives strong contextual signals on when to use the tool. However, it does not explicitly name an alternative tool for direct execution, though it implies such tools exist outside MCP.

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