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Iridium: LinkedIn MCP Server

cancel_job

Cancel Job

Stop a background search that has not finished. What it already found stays readable with get_job. Nothing is sent or changed on LinkedIn; it only stops looking.

Responses:

200: Successful Response (Success Response) Content-Type: application/json

Input Schema

NameRequiredDescriptionDefault
job_idYes

Schema Changelog

Changes observed during successful MCP inspections.

No schema history has been recorded yet.

TDQS

A4/5.0
Behavior4/5

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

With zero annotations, the description carries the burden well: it declares this is not a LinkedIn-visible action ('Nothing is sent or changed on LinkedIn; it only stops looking') and that partial results survive cancellation. It omits whether cancelling is reversible, what happens if the job already finished, and whether a cancelled job can be restarted.

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?

The behavioral content is front-loaded in two tight sentences with no wasted wording. The trailing 'Responses: 200 Successful Response' block is boilerplate generated text that adds nothing and slightly dilutes the signal.

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 single-parameter cancellation tool with no output schema, the description covers the important agent-facing facts: it's a local stop, not an outward action, and prior findings remain accessible. Missing only job_id sourcing and post-cancellation job state.

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?

There is one required parameter (job_id, UUID) with 0% schema description coverage, and the description never mentions it — no guidance on where the job_id comes from (presumably get_job or a listing call) or what happens on an invalid/unknown ID. The prose compensates for nothing on the parameter side.

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 ('Cancel Job') and narrows the scope precisely: 'Stop a background search that has not finished.' That framing distinguishes it from get_job (which reads results) and from the many draft/scheduled-send siblings, none of which are background searches.

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?

Says when to call it (an unfinished background search) and what to use instead to retrieve partial output ('stays readable with get_job'). The condition 'has not finished' implicitly excludes completed jobs, but there is no explicit when-not-to-use or guidance on the already-finished/completed case.

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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