suggest_comment_reply

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 mentions 'AI-powered' and tone maintenance ('friendly, professional'), but fails to detail critical aspects: whether it's read-only or has side effects, rate limits, authentication needs, output format, or error handling. For a tool with potential AI integration and no annotations, this is a significant gap.

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 and front-loaded, with two sentences that directly state the tool's function and key behavioral trait (tone). There's no wasted text, but it could be slightly more structured (e.g., separating purpose from guidelines). Overall, it's efficient and easy to parse.

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 complexity (AI-powered, customer interaction) and lack of annotations and output schema, the description is insufficient. It doesn't explain return values, error cases, or operational constraints, leaving the agent with incomplete context for reliable invocation. More detail is needed to compensate for the missing structured data.

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 the schema already documents both parameters ('commentText' and 'tone') with descriptions and defaults. The description adds minimal value beyond the schema, only implying tone usage without elaborating on parameter interactions or constraints. Baseline 3 is appropriate as the schema handles most of the parameter documentation.

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: 'Get AI-powered reply suggestions for customer comments.' It specifies the verb ('Get'), resource ('reply suggestions'), and target ('customer comments'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'auto_respond_common_questions' or 'get_new_comments', which might handle similar content.

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 provides minimal guidance: it implies usage for replying to customer comments and mentions tone preferences. However, it lacks explicit when-to-use rules, prerequisites (e.g., comment context), or alternatives among siblings. No exclusions or comparisons are stated, leaving the agent to infer usage scenarios.

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