draft_community_message

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

No annotations are provided, so the description must carry the full burden. It mentions AI tone matching but does not detail behavioral traits like whether the tool is read-only, destructive, or what permissions are required. This is insufficient for an AI agent to understand side effects.

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 two sentences and front-loaded with the core purpose. Every sentence adds value: first states action and target, second explains capability. No wasted words.

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?

With no output schema, the description should explain what the tool returns (e.g., a drafted message string or JSON). It fails to do so. The tool has low complexity, but the missing return value description leaves gaps for agent understanding.

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%, so baseline is 3. The description does not add any extra meaning beyond what the schema already provides for parameters like community_type and message_purpose. No parameter-specific details are offered.

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 'draft' and the resource 'message for a Discord community', and adds value by noting 'Uses AI to match community tone'. This distinguishes it from sibling tools like analyze_server_engagement or find_relevant_channels, which have different purposes.

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 implies use when drafting a community message, but does not explicitly state when to use versus alternatives or provide exclusions. Siblings have distinct functions (analyzing, searching, etc.), so context is somewhat clear but guidance is lacking.

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