get_post_comments

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. It mentions that the tool 'Returns list of comments with author info,' which adds some context about the output format. However, it lacks critical details such as whether this is a read-only operation, potential rate limits, authentication requirements, or error conditions. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 concise, with a clear purpose statement followed by parameter explanations in a simple format. It avoids unnecessary details and is front-loaded with the main action. However, the 'Args:' and 'Returns' sections could be integrated more seamlessly, and it lacks a concluding sentence, slightly affecting flow.

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 low complexity (2 parameters, no nested objects) and the presence of an output schema, the description is adequate but incomplete. It covers the basic purpose and parameters but misses usage guidelines and behavioral details like error handling or permissions. The output schema likely documents return values, so the description doesn't need to elaborate there, but overall it leaves room for improvement in guiding the agent effectively.

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?

The description adds minimal semantic value beyond the input schema. It explains that 'post_urn' is a 'LinkedIn post URN' and 'limit' is the 'Maximum comments to return (default: 50),' which clarifies the purpose of each parameter. However, with 0% schema description coverage, the schema itself provides no descriptions, so the description compensates somewhat but doesn't fully address nuances like URN format or limit constraints. This meets the baseline for partial compensation.

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 comments on a specific post.' It specifies the verb ('Get') and resource ('comments on a specific post'), making the action unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_comments_official' or 'get_post_reactions', 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. It doesn't mention sibling tools like 'get_comments_official' or 'get_post_reactions', nor does it specify prerequisites or exclusions. The agent must infer usage from the tool name alone, which is insufficient for optimal selection.

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