get_post

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

No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Get' implies a read operation, the description doesn't address important behavioral aspects like authentication requirements, rate limits, error conditions, or what 'cleaned data' specifically means. The mention of 'TOON format' is unexplained and adds confusion rather than clarity.

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 appropriately brief with two clear sentences. The first sentence states the core purpose, and the second provides output information. However, the unexplained 'TOON format' reference creates ambiguity that slightly reduces effectiveness.

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?

For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'cleaned data' includes, what 'TOON format' means, or provide any behavioral context about the operation. Given the complexity of LinkedIn data retrieval and the lack of structured metadata, more complete guidance 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?

With 100% schema description coverage, the schema already documents both parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain URL format requirements, what 'save_dir' actually does with the data, or provide examples. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 'LinkedIn post details', making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'get_post_comments' or 'get_post_reactions', which also retrieve post-related data but focus on specific aspects rather than general details.

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 like 'get_post_comments', 'get_post_reactions', and 'search_posts', there's no indication of when this general post details tool is preferred over more specific ones or search functionality.

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