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meskhetian

linkedin-applicants-mcp

by meskhetian

Cancel pending tasks

queue_cancel
Destructive

Cancel pending LinkedIn applicant tasks by type, job ID, or application ID. Without filters, cancels all queued tasks while running and completed tasks remain unaffected.

Instructions

Cancel PENDING tasks matching the filters (type / jobId / applicationId). Without filters cancels every pending task. Running tasks finish; done work is untouched.

Input Schema

NameRequiredDescriptionDefault
typeNo
jobIdNo
applicationIdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior5/5

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

The description goes beyond the destructiveHint annotation by specifying exactly what is affected: only PENDING tasks, with running tasks allowed to finish and completed work untouched. It also discloses the default behavior when no filters are provided (cancels all pending). This is rich behavioral context that an agent needs to anticipate side effects.

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 concise and well-structured, with two sentences. The main action is front-loaded, followed by essential clarifications about scope and side effects. Every sentence adds value, and there is no redundancy or filler.

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 cancellation tool with no required parameters and no output schema, the description covers the critical aspects: what it does, the filters, the default behavior, and what it does not affect. It could optionally mention error handling or return values, but these are not essential for correct invocation given the annotations and the clear scope. Minor gaps remain, but overall it is sufficiently complete.

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?

The schema has 0% description coverage, so the description must compensate. It lists the three filter fields (type, jobId, applicationId) but does not explain their semantics, combination logic, or constraints (e.g., how multiple filters interact, whether they are OR/AND). The description essentially repeats the parameter names without adding meaning beyond what the schema already shows.

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 clearly states the action (cancel), the target (pending tasks), and the filtering mechanism (type/jobId/applicationId). It also distinguishes the scope: without filters it cancels every pending task, and explicitly notes that running tasks finish and done work is untouched. This differentiates it from sibling tools like queue_pause or queue_retry_failed.

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?

The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention queue_pause, queue_retry_failed, or any other sibling, nor does it state conditions for choosing this over them. The intended use is implied by the name and description, but there is no direct comparison or exclusion criteria.

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