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

Beyond the annotations, the description discloses real behavioral traits: the tool is free, the budgetUsd amount is held while it runs and released, the result is a verified token safe to paste, and it requires a write OAuth scope. The 'Needs the write scope' note sits in mild tension with readOnlyHint=true, but it describes an auth requirement rather than a state mutation, so it is not a direct contradiction.

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?

Three compact sentences with no filler; the output artifact is front-loaded and the cost/auth caveats follow. The first sentence is dense with an inline URN example but remains readable.

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 two-parameter lookup with an output schema and read-only annotations, the definition covers purpose, cost behavior, auth scope, and usage constraint. Return-format detail is not required since an output schema exists, so the description is nearly complete; the only soft spot is the unexplained 'write scope' requirement.

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 baseline is 3. The description adds meaning beyond the schema by explaining that budgetUsd is held while the call runs and then released, and by characterizing what the query accepts (a large company name or topic keywords), which goes past the schema's example strings.

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 resource and output: the verified LinkedIn mention token (e.g. @[Microsoft](urn:li:organization:1035)) for a company, or companies for a topic. It is clearly distinguishable from siblings like posts_publish or find_photo. It leads with the noun/return artifact rather than a verb ('Look up X'), which slightly weakens the action framing.

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?

'Ready to paste into a LinkedIn post' implies the context of use, and 'Tag only a company it returns' constrains how results may be used. However, there is no explicit when-to-use vs when-not guidance and no alternative tool is named among the many siblings, so the agent must infer the scenario.

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