add_comment

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it describes what the tool does (adding comments with different types), it lacks critical behavioral details: whether this operation is destructive (e.g., overwrites existing comments), requires specific permissions, has side effects, or how errors are handled. For a mutation tool with zero annotation coverage, 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 well-structured and efficient: it starts with the core purpose in one sentence, then lists comment types with brief explanations. Each sentence adds value without redundancy. It could be slightly more front-loaded by mentioning the comment_type parameter upfront, but overall it's concise and clear.

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 moderate complexity (adding comments with types), no annotations, and no output schema, the description is partially complete. It covers the basic purpose and parameter semantics but lacks behavioral transparency (e.g., mutation effects, error handling) and usage guidelines. For a tool that modifies data without safety annotations, more context on risks or outcomes would improve completeness.

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 all three parameters (address, comment, comment_type) with descriptions and defaults. The description adds some value by listing and briefly explaining the comment_type options (e.g., 'regular', 'repeatable'), which clarifies their semantics beyond the schema's enum-like list. However, it doesn't provide additional syntax or format details for parameters, so it meets the baseline for high schema coverage.

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: 'Add a comment at the specified address.' It specifies the verb ('Add') and resource ('comment'), and the list of comment types provides additional specificity. However, it doesn't explicitly distinguish this tool from sibling tools like 'set_comment' or 'delete_comment' in terms of when to use each, which prevents a perfect score.

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 no guidance on when to use this tool versus alternatives like 'set_comment' or 'delete_comment' from the sibling list. It lists comment types but doesn't explain when to choose one type over another or any prerequisites (e.g., whether the address must be valid or within a specific context). This lack of contextual guidance limits its utility for an AI agent.

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