Linear

linear_removeIssueLabel

Idempotent

Remove a label from a Linear issue by specifying the issue identifier and label ID. Update issue categorization by removing unwanted labels.

Instructions

Remove a label from an issue in Linear

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": {
      "issueId": "<issueId>",
      "labelId": "<labelId>"
    },
    "name": "linear_removeIssueLabel"
  }
}

Input Schema

Name	Required	Description	Default
`issueId`	Yes	ID or identifier of the issue to remove the label from (e.g., ABC-123)
`labelId`	Yes	ID of the label to remove from the issue

Output Schema

Name	Required	Description	Default
`issueId`	No
`labelId`	No
`success`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.4.1Jul 30, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "issueId": {
+      "type": "string"
+    },
+    "labelId": {
+      "type": "string"
+    },
+    "success": {
+      "type": "boolean"
+    }
+  },
+  "type": "object"
+}

First observedAug 18, 2025

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already provide idempotentHint=true, but the description adds no extra behavioral details such as what happens if the label isn't on the issue. With annotations present, the bar is lower; still, the description could mention idempotency or error conditions.

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?

Single sentence of 7 words, perfectly concise with no wasted text. Every word is necessary.

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 simple mutation tool with an output schema present, the description is adequate. It could mention return behavior or prerequisites, but overall completeness is high given the low complexity.

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 covers both parameters with descriptions (100% coverage). Description adds no additional meaning beyond the schema, so baseline 3 is appropriate.

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 'remove', the object 'label', and the context 'from an issue in Linear'. It distinguishes from sibling 'add' tool without ambiguity.

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

Usage Guidelines3/5

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

No guidance on when to use or when not to use this tool versus alternatives like adding labels or other issue modifications. The description is purely declarative without usage context.

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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