LinkedIn MCP Zero

by SanthaKumar-K-2004

Overview Schema Source Related Servers Discussions Admin

confirm_export

Idempotent

Export selected LinkedIn jobs to CSV, JSON, or XLSX after an interactive confirmation prompt, ensuring user approval before files are generated.

Instructions

Export jobs with interactive user confirmation dialog.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "ids": "<ids>",
      "fmt": "<fmt>"
    },
    "name": "confirm_export"
  }
}

Input Schema

Name	Required	Description	Default
`fmt`	Yes	Export format ('csv', 'json', or 'xlsx')
`ids`	Yes	List of LinkedIn job IDs to export

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.4.8Nov 4, 2026

TDQS

B3.1/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=false, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds one genuinely non-obvious trait — that a user-facing confirmation dialog is involved — but omits whether the call blocks on user input, what happens if the user declines, and whether a file is written or a job queued.

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?

A single short sentence with no filler, and the interactive-confirmation trait is front-loaded. It is efficient, though slightly too terse for the ambiguity it leaves with export_jobs.

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?

Missing justifications for contextual_completeness score?

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%, so both parameters (ids and fmt with its csv/json/xlsx options) are fully documented in the schema. The description adds no extra meaning about id format, batch size limits, or format defaults, so baseline 3 applies.

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

Purpose3/5

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

The description names a verb ('Export') and resource ('jobs') plus a distinguishing trait ('interactive user confirmation dialog'), but a sibling tool literally named export_jobs exists and the description never says how confirm_export differs from it, or whether this tool performs the export or merely confirms one. An agent cannot reliably choose between the two from this text alone.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no mention of the export_jobs sibling as the alternative, and no precondition stated for when the confirmation dialog path is appropriate. Usage is only implied by the word 'confirmation'.

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