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Get Saved Jobs

get_saved_jobs
Read-only

List your saved, in-progress, applied, or archived LinkedIn jobs from the job tracker and return job IDs to fetch full details.

Instructions

List the authenticated user's jobs at one stage of LinkedIn's job tracker.

Returns job_ids that can be passed to get_job_details for full info.

Input Schema

NameRequiredDescriptionDefault
stageNoTracker tab: saved (default), in_progress, applied or archived. applied lists Easy Apply submissions and external applications the user confirmed to LinkedIn.saved
max_pagesNoMaximum number of tracker pages to load (1-10, default 3)

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.29.0

TDQS

A4/5.0
Behavior3/5

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

The readOnlyHint and openWorldHint annotations already establish that this is a safe read against external LinkedIn data. The description adds useful relational behavior (the returned job_ids are meant to feed get_job_details), but says nothing about ordering, page budget effects, or what an empty result means for a user with no jobs in that stage.

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?

Two short sentences, front-loaded with what it returns and followed by the actionable next step. Nothing is redundant or padded.

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?

For a two-parameter read-only lister with a full schema and an output schema, this covers purpose, scope and follow-up. The only gap is not hinting at pagination/truncation behavior implied by max_pages, which matters if the agent must page through a large tracker.

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

Parameters3/5

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

Schema description coverage is 100%, and the stage enum is documented in detail there, including the meaning of 'applied'. The description only echoes the stage concept ('at one stage') and adds no format, default, or interaction detail beyond the schema, so it sits at the baseline.

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 pairs a specific verb (List) with a specific resource (the authenticated user's jobs in LinkedIn's job tracker) and adds a scope qualifier (one stage). This clearly separates it from search_jobs (which searches the wider job corpus) and from get_job_details (which expands a single job).

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?

It states the intended workflow: list to obtain job_ids, then pass those ids to get_job_details for full info. That is genuine when-to-use guidance for the follow-up call, but there is no explicit exclusion such as 'use search_jobs instead when you don't know the employer/user's saved state'.

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