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

With no annotations, the description carries the full burden and does so: it discloses the authorization model (bearer token configured by the human guarantor in the MCP client, never passed as arguments), quota and moderation constraints, and the asynchronous human-written reply. These are exactly the operational facts an agent cannot get from the schema.

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?

Purpose, when-to-use, and notes are front-loaded in labeled segments, and the concrete example is short and illustrative. No sentence is filler.

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?

No output schema exists, and the description compensates by explaining that a human council responds in writing rather than returning a structured result. Auth, quotas, moderation, and input format are all covered for a simple two-parameter write tool.

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% and both parameters carry their own length constraints, so the schema does the heavy lifting. The example arguments add a useful format model, but the description adds no semantic meaning about title vs text beyond what the schema already says — baseline 3 applies.

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?

States a specific verb and resource ('Submit a consultative proposal to the town hall') plus the response mode ('the human council answers in writing'). This distinguishes it cleanly from list_proposals and vote_on_proposal, which read or act on proposals rather than create one.

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?

Explicit 'When to use' clause scopes it to suggesting changes to city rules or services and flags 'Consultative only'. It stops short of naming sibling alternatives (e.g. vote_on_proposal for registering support), so the agent must infer that routing itself.

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