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

Annotations already cover read-only and idempotent behavior. The description adds valuable contextual behavior beyond that: LinkedIn does not expose follower history for personal profiles, so only a live total is returned and no follower series or gained-count is available. This prevents an agent from expecting data that will never be present.

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 two focused sentences with no filler. The main purpose and returned metrics are front-loaded, and the important LinkedIn limitation is stated in a separate, clearly structured sentence.

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?

Even without an output schema, the description names the key returned categories (impressions, unique reach, video, cadence, follower count) and explicitly documents the missing follower-history behavior. For a read-only tool with simple parameters and strong annotations, this is sufficient for an agent to use it correctly.

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, including defaults for start_date and end_date. The description does not add detail about parameter usage or format, so the baseline of 3 is appropriate.

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 states a specific verb ('Fetch') and a clear resource: personal LinkedIn post performance for a connected person or team influencer. It also lists concrete metrics and the follower count, making it easy to distinguish from sibling tools like get_company_performance or get_post_engagement.

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 clearly establishes the intended context: retrieving metrics for personal profiles or team influencers, not company pages or individual posts. It does not explicitly name alternatives or give when-not-to-use conditions, but the 'personal' scope and follower-history caveat provide clear usage context.

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