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

Annotations already cover read-only/idempotent/open-world, but the description adds real operational context beyond them: one LinkedIn call per page of up to 25, each counted against the daily job_searches quota (default 50 pages), with advice to keep to a few pages, plus the shape of a returned posting. Quota and cost-per-call behavior is exactly the kind of disclosure annotations cannot carry.

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?

Purpose is front-loaded and the density is high, but the Reach-jobs exclusion is stated twice ('not Reach jobs (create_job / list_jobs)' and again 'Not for Reach batch jobs (list_jobs)'), which is redundant in an already long single block. Removing the duplicate would tighten it without losing 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?

With an output schema present and rich annotations, the description need not explain return values, yet it still summarizes them briefly. It covers cost model, pagination, filtering dimensions, keyword syntax, and sibling routing — everything needed to invoke 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 coverage is 100%, so the baseline is 3; the description earns above baseline by documenting LinkedIn keyword syntax ('exact phrase', OR, AND, NOT) that the schema's keywords description only implies, and by restating the start pagination series in context. It adds real semantic value but does not extend every parameter.

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 (search) and resource (LinkedIn job postings) and pins the scope with an analogy ('like the Jobs tab of LinkedIn: which companies are hiring for a role right now'). It also explicitly separates itself from the Reach job tools (create_job / list_jobs), so an agent can distinguish it from siblings without opening a schema.

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 an explicit when-to-use rationale (hiring as a buying signal), names the downstream alternatives (salesnav_build_search_url with current_company, scrape_search filtered on company), and states when-not-to-use it (Reach batch jobs, list_jobs). This is close to a complete routing decision.

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