linkedin_analyze_post

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

With no annotations, the description carries the full burden of behavioral disclosure. It lists analysis dimensions but omits input handling (e.g., whether postContent is required to supplement postId), potential network fetches, side effects, or return format. This leaves significant behavioral ambiguity.

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 with the action and scope front-loaded. The parenthetical dimension list adds value without bloat. It earns a slight deduction for listing only 7 of the 15 dimensions, which could be seen as a missed structured summary.

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?

The tool is moderately complex (2 parameters, no output schema, no annotations), yet the description does not explain output format, all 15 dimensions, or how the tool obtains data for a post. An agent would lack enough context to anticipate results or handle edge cases like missing post content.

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 baseline is 3. The description adds the context that the tool analyzes a single post and mentions dimensions, but it does not clarify the relationship between postId and postContent or how to choose between them. No additional parameter-level guidance is offered.

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 uses a specific verb ('Performs a deep 15-dimension analysis') with a clear resource ('a single LinkedIn post') and enumerates several dimensions. This differentiates it from sibling tools that target profiles, search results, or recent activity, so an agent can identify the correct tool.

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?

No explicit when-to-use or alternative guidance is provided. The description implies the tool is for analyzing a single LinkedIn post, but it does not explain when to choose it over similar tools like linkedin_analyze_recent_activity or linkedin_analyze_profile.

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