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IzikStar

linkedin-agent-mcp

by IzikStar

Save a job on LinkedIn

linkedin_save_job

Save a LinkedIn job using a user-confirmed actionId from the prepare step. Without confirmation, the action fails, preventing unapproved changes.

Instructions

[EXECUTE - external action; REQUIRES the user to have confirmed this exact action] Saves a job on LinkedIn (changes LinkedIn state; reversible with linkedin_unsave_job). Requires an actionId from linkedin_prepare_save_job that the USER has confirmed in their own terminal. Fails with CONFIRMATION_REQUIRED otherwise; do not retry in a loop, ask the user. Never save jobs just because they look good.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionIdYesThe actionId returned by the matching prepare tool, after the user confirmed it.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
actionYes
summaryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only tell the agent this is a non-read-only, non-idempotent, non-destructive write. The description adds the crucial operational context they lack: user confirmation is mandatory, the specific CONFIRMATION_REQUIRED error, and that retrying is harmful because the call is not idempotent. That is genuine value beyond the structured fields.

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 EXECUTE warning and a dense but single-paragraph body where each clause earns its place (precondition, failure, no-retry, reversal). The closing 'Never save jobs just because they look good' is slightly editorial but still functional guidance.

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

Completeness5/5

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

Given an output schema exists, the description needn't document returns, and it covers everything else an agent needs: prerequisite actionId, required user confirmation, error behavior, and reversibility. No meaningful gap remains for invoking this tool correctly.

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 coverage is 100% for the single actionId parameter, and the description largely restates the schema's own wording ('after the user confirmed it'). Baseline 3 applies since the schema already carries the semantics; the description adds only the terminal-confirmation nuance.

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 ('Saves a job on LinkedIn') with an execution tag up front. It clearly distinguishes itself from the sibling prepare/unsave tools by naming both, so an agent can route without opening any schema.

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?

Explicitly states the precondition (an actionId from linkedin_prepare_save_job that the USER confirmed in their own terminal), the failure path (CONFIRMATION_REQUIRED), and the anti-pattern (do not retry in a loop, ask the user). It names the reversal tool linkedin_unsave_job and even gives a policy guardrail against gratuitous saves.

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