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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, but the description adds substantial operational context beyond them: the 5000-count cap with total_is_lower_bound, page/offset/next_offset mechanics, ordering behavior with and without a query, facet counting across all matches, extraction accuracy caveats (location ~97%, salary/remote 90-95%, overtime/visa/english as hints), not_extracted semantics, unserved part-time-only postings, folded copies affecting totals, and explicit warnings never to invent pay or estimate hiring odds. This is rich disclosure an agent could not get from the annotations alone.

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?

The description is front-loaded with purpose and key return semantics, and most sentences carry real information. However, it is dense and run-on, packing many clauses into semicolon-chained sentences, and it duplicates some material already covered exhaustively by the schema. For a 23-parameter tool some length is warranted, but readability and structure suffer.

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?

There is no output schema, yet the description explains the return shape thoroughly: total with lower-bound caveat, page of postings without snippet, offset/next_offset pagination, collected date range, facets, not_stated counts, and the distinction between average_overtime_hours and overtime_hours. It also documents unserved and unprocessed postings. Given the tool's complexity, an agent has enough to call 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 description coverage is 100%, so the schema already documents all 23 parameters in depth, including enums and nested objects. The description mostly cross-references the schema ('as in search_jobs') and restates select behaviors like limit 0 returning only the total. It adds some cross-parameter meaning—notably that all conditions must hold and how not_stated interacts with include_unstated—but the schema does the heavy lifting, so the 3 baseline is appropriate.

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 opening sentence states a specific verb pair and resource: 'Count and list job postings by conditions'. It clarifies scope ('all optional, all of which must hold') and references search_jobs for keyword semantics, so an agent can distinguish it as the filtered count/list variant. It stops short of explicitly naming when to prefer search_jobs over this tool, which keeps it from 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?

Usage guidance is embedded throughout: 'Use it only when the user says they are a new graduate' for new_grad, the pay-floor basis min/max rule with 'ask first' when results are thin, 'confirm with get_job before telling the user', and 'Guide: job_search_guide'. These give clear when/when-not conditions for several high-stakes parameters. There is no single upfront statement of when to choose this tool over search_jobs, which prevents a 5.

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