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

Goes well beyond the readOnly/openWorld annotations: it discloses that only PDL's directory is consulted, that a supplied LinkedIn URL remains usable even when the directory cannot match it, and it names the response fields (source, providerStatus) that disambiguate those outcomes, plus the OAuth requirement. That is exactly the kind of non-obvious outcome-vs-error behavior an agent needs to avoid retrying or aborting wrongly.

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?

Five tightly packed sentences, front-loaded with purpose, then input rules, then scope exclusions, then result interpretation, then next steps. No sentence is filler; each carries a distinct constraint or routing instruction.

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 4-param read-only lookup with no output schema, the description covers purpose, required auth, scope limits, how to read ambiguous results, and what to do with the output. Nothing needed to call it correctly is missing.

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 the baseline is 3; the description still earns credit by attaching a provenance constraint to name/website/linkedinUrl ('supplied by the user or verified on the web; never invent URLs'), which is a real behavioral rule about those fields rather than a restatement. workspaceId is never discussed, but its schema description is complete.

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 ('Identify a named employer') plus the exact downstream purpose ('before using it as a sourcing filter'). It also scopes the tool negatively — directory lookup only, no people search, no candidate counts — which separates it cleanly from build_sourcing_query, source_candidates and the list_* siblings.

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?

Explicit triggering condition (resolve the name first, then use it as a filter), explicit input guidance ('pass the company name and any LinkedIn company URL or website the user supplied or that you verified'), an explicit prohibition ('never invent URLs'), and explicit routing to both follow-up tools (build_sourcing_query or edit_sourcing_query). This is the when/when-not/alternatives bar fully met.

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