get_post_comments

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

No annotations are provided, so the description carries full burden. It mentions 'Returns cleaned data in TOON format' which adds some behavioral context about output formatting, but lacks critical details like whether this is a read-only operation, rate limits, authentication needs, pagination behavior beyond parameters, or what 'cleaned' entails. For a tool with 6 parameters and no annotations, this is insufficient.

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 a single, efficient sentence that front-loads the core purpose. It avoids unnecessary words, though it could be slightly more structured by separating purpose from output details. Every part earns its place, but it's brief given the tool's complexity.

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 6 parameters, no annotations, and no output schema, the description is incomplete. It mentions the output format ('TOON format') but doesn't explain what that means or provide behavioral context for a data-fetching tool. For a tool with moderate complexity and rich input schema, more guidance on usage and behavior is needed.

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%, providing clear documentation for all 6 parameters. The description adds no parameter-specific information beyond what's in the schema, so it meets the baseline of 3. However, it doesn't compensate with additional context like explaining relationships between parameters (e.g., 'paginationToken' vs 'page').

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 ('Get') and resource ('comments on a LinkedIn post'), and specifies the output format ('cleaned data in TOON format'). However, it doesn't explicitly differentiate from sibling tools like 'get_profile_comments' or 'get_post_reactions', which target different resources or aspects of LinkedIn 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 no guidance on when to use this tool versus alternatives. With multiple sibling tools for LinkedIn data (e.g., 'get_post_reactions', 'get_profile_comments'), there's no indication of context, prerequisites, or exclusions to help an agent choose appropriately.

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