linkedin_job_detail

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

There are no annotations provided (readOnlyHint, destructiveHint are absent), so the description carries the full burden of disclosing behavioral traits. It does this well: it states that this tool does not apply to the job, does not save it, and has no way to change anything about the posting; it also clarifies it does not collect other people on the page. It describes null vs. FAIL behavior for missing fields and unrenderable pages. The only small gap is that it doesn't explicitly mention auth requirements or rate limits, but for a read-only tool with one page load, the disclosure is thorough and covers the key side effects and failure modes.

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 well-structured and front-loaded: the first sentence states the core purpose, then it builds context about what cards lack, confirms the one-page behavior, clarifies non-effects, and explains null/fail semantics. It is a bit longer than strictly necessary (around 150 words) but every paragraph earns its place by addressing a distinct aspect: what this gives, what it does not give, and the specific edge case. The structure is clear and uses paragraphs to separate logical blocks. Slightly verbose in places (repeats 'this does not apply...' phrasing), but overall effective.

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?

Given the complexity is simple (one parameter, no nested objects) and there is an output schema (has_output_schema=true) that presumably describes the returned fields, the description covers the critical runtime behaviors an agent needs: what data is available, the distinction from sibling list tools, the null vs. FAIL semantics, and the explicit side-effect-free nature. The description fully equips an agent to decide when to call this tool and what to expect. The only potential missing detail is the exact output fields, but that is covered by the output schema, so the description is complete.

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?

The schema has a single parameter, job_id, with 100% description coverage (the schema already describes it as the numeric job id or a job URL from two sibling tools). The description reinforces this by mentioning that both linkedin_search_jobs and linkedin_saved_jobs return it, but does not add new meaning beyond what the schema gives. Since coverage is 100% and the description adds a small hint about which tools return the id, a score of 4 is appropriate—slightly above baseline because the description confirms the source of the parameter value, which is useful for an agent.

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 opens with a direct, specific statement of what the tool does: 'Read one job posting in full, including the description and the pay.' It clearly identifies the resource (one job posting) and the verb (read). It goes further to distinguish itself from sibling list tools, explaining that this tool retrieves the full posting behind a card, and explicitly lists the facts available only here (pay range, applicant count, etc.). This fully separates it from the list/collection siblings (linkedin_search_jobs, linkedin_saved_jobs) and from action tools (linkedin_save_job, linkedin_unsave_job).

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 description is explicit about when to use this tool vs. the sibling list tools: it explains that list tools return only cards with title, company, location, link, while this tool is where the decision-settling facts live. It states there is one page load, no pagination, and explicitly mentions it does not read the 'people also viewed' rail or hiring team. It also provides clear behavioral conditions: the call FAILS if the page did not render the posting, and it treats a title-only page as an error. This gives an agent unambiguous selection criteria.

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