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Get one LinkedIn job posting in full

get_linkedin_job

Fetch one LinkedIn job posting by its id or URL: title, company, location, employment_type, seniority_level, salary where the posting shows one, and the full description — the fields linkedin/jobs leaves null, and workplace_type, listed_at and easy_apply where the posting shows them. Use it on the job_id of a search result. Give exactly one of id or url. Costs 3 credits, cached or not; a failed call is refunded.

Input Schema

NameRequiredDescriptionDefault
idNoLinkedIn's numeric id for the posting: `job_id` in a search result, and the number at the end of `/jobs/view/…`.
urlNoThe posting's URL, e.g. `https://www.linkedin.com/jobs/view/4468618386/`.
freshNoSkip the cache and fetch now. Charged normally. Not available on trial credits — buy any pack to unlock it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and delivers real operational facts the schema cannot: cost is 3 credits "cached or not", a failed call is refunded, and the cache can be bypassed via `fresh` though not on trial credits. It omits auth requirements and rate limiting, which is the remaining gap for a metered external API call.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose and return payload, then input rules, then cost — a sensible priority order with no filler. It is a single dense paragraph rather than separated clauses, so the cost/cache details are slightly buried, but every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description must enumerate return fields, and it does so in detail while noting which fields are only present "where the posting shows" them — honest about optionality. Cost, cache, and input exclusivity are all covered; only auth/rate-limit behavior is absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds a constraint the schema does not express: `required` is empty, yet the tool demands "exactly one of `id` or `url`". That mutual-exclusivity rule is essential to invoking the tool correctly and is only in the prose. It adds nothing further about `fresh` beyond the schema text.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Fetch one LinkedIn job posting by its id or URL") and then enumerates exactly what comes back (title, company, location, employment_type, seniority_level, salary, full description). It also distinguishes itself from the list/search sibling by noting it returns "the fields linkedin/jobs leaves null" and pulls one posting, so an agent can separate it from the plural search tool 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.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear triggering context ("Use it on the job_id of a search result") and an explicit input rule ("Give exactly one of `id` or `url`"). It does not name the sibling search tool by its exact name (`search_linkedin_jobs`) and gives no when-not-to-use case, so it stops short of full routing guidance.

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

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