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

Annotations only declare readOnlyHint=true, so the description carries most of the load and does it well: it explains the ranking rule (median over up to 5 fitted people plus the page), the selection order (founders/CEO/C-suite in last 90 days, then most active), the 18-post floor, the '1 account' flag, and that results are held back while history pulls are pending. It omits pagination/return-shape detail, keeping it from a 5.

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?

Front-loaded with what the tool returns, and every clause about ranking, the floor, and the single-account case earns its place. The second sentence is a long run-on that is harder to parse than necessary, so it is not a clean 5.

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 complex analytical tool with no output schema and no required params, the description explains the computation, edge cases (single account, pending pulls), and which output fields identify counted members. That is nearly complete; only pagination/return format is left implicit.

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 five inputs. The description references people.counted/countedPersonIds, but those are output fields, not the input params, so it adds no new meaning about dateTo, company, dateFrom, companyId, or workspaceId.

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 resource (a company's page fit plus its people's geometric-mean distribution, median and baseline band) and even the computation behind it. It does not explicitly name or contrast itself with siblings like category_breakdown or industry_landscape, so it stops short of a 5.

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 closing line 'Use for "how is X doing on LinkedIn"' gives one concrete usage scenario, but there are no exclusions or alternatives named (e.g. when to prefer category_breakdown or list_companies). Usage is implied rather than spelled out.

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