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discover_jobs

Search LinkedIn for recent job postings, newest first, and get the exact search URL used. Focuses on Easy Apply roles so you can proceed directly to application.

Instructions

Search LinkedIn for postings, newest first.

Use this when the user wants jobs found rather than handed a link. Defaults to Easy Apply only, because that is the route this server can actually finish; "Apply on company site" hands off to an ATS whose form we have never seen.

Returns the postings plus the exact search_url used, so a surprising result can be traced back to the query that produced it.

This applies to nothing. It only lists. Take a job_id or url from the result and run the normal preflight -> apply flow on it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
keywordsYes
locationNo
recent_daysNo
easy_apply_onlyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so well. It discloses the Easy Apply-only limitation and the reason ('Apply on company site' hands off to an ATS whose form we have never seen), explicitly says the tool applies to nothing, and explains that the exact `search_url` is returned for traceability.

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

Conciseness5/5

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

The description is compact and front-loaded, starting with the core action and following with usage, behavioral limitations, and downstream flow. Every sentence adds either purpose, a constraint, or routing guidance; there is minimal fluff.

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?

The description covers purpose, behavior, limitations, return traceability, and the correct downstream flow, and an output schema exists for result details. It is only slightly incomplete in not defining the less obvious parameters such as `recent_days` and `location`, though their defaults and names mitigate the gap.

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

Parameters2/5

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

Schema description coverage is 0%, so the description needed to compensate by explaining the parameters. It only adds meaningful context to `easy_apply_only` via the default rationale; `keywords`, `location`, `limit`, and especially `recent_days` are left to be inferred from their names and types alone.

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?

The description opens with a specific verb-resource pair: 'Search LinkedIn for postings, newest first.' It then distinguishes itself from sibling tools by explicitly saying it only lists results and does not apply, which makes its role clear without needing to inspect other schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

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

It gives an explicit trigger: 'Use this when the user wants jobs *found* rather than handed a link.' It also states a clear exclusion ('This applies to nothing. It only lists.') and directs the agent to run the `preflight` -> apply flow on a returned job_id or url, so the downstream action is unambiguous.

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