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

With no annotations, the description carries the burden well: it discloses the join path (person_positions with is_current=true), the `_unknown_company` bucketing for engagers lacking a current company, and that no LinkedIn pull or credits occur. It stops short of describing pagination or the exact row shape, but the key behavioral traits are covered.

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?

Four tight sentences, front-loaded with the core action and scope, then the join detail, the cost/safety note, and the edge-case bucketing. No filler and every sentence adds information.

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?

No output schema and no annotations, so the description must convey the return shape, which it does (companies ranked by engager count, with sample engagers implied by top_engagers_per_company). It is nearly complete, though it could say more about ordering ties or the response envelope.

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 coverage is 100%, so all five parameters are already documented, setting the baseline at 3. The description adds only marginal meaning beyond the schema — that industry_urn narrows to a single industry and that post_url/post_id are interchangeable inputs — without explaining limit or top_engagers_per_company behavior.

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?

States a specific verb and resource ('return the companies whose people engaged') plus the ranking rule, and the input ('LinkedIn post URL or id'). It is clearly distinguishable from siblings like get_post_set_engagers and get_alumni_engagers, which target different engager groupings.

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?

Gives context for when the tool applies (post URL or id, optional industry narrowing) and notes it is a pure DB read with no credits charged, which is a useful selection signal. However, it never names an alternative sibling or states when NOT to use it, so the agent must infer the choice between this and get_post_set_engagers/get_alumni_engagers.

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