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ARCLinearGitHub-MCP

ARCLinearGitHub-MCP

by arclabs-studio
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Remote

linear_get_issue

Retrieve details of a specific Linear issue by providing its identifier (e.g., PROJ-123).

Instructions

Get details of a specific Linear issue.

Args: issue_id: Issue identifier (e.g., 'PROJ-123')

Returns: Dictionary with issue details or error

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": {
      "issue_id": "<issue_id>"
    },
    "name": "linear_get_issue"
  }
}

Input Schema

NameRequiredDescriptionDefault
issue_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries full burden. It indicates a read operation returning details or error, but does not disclose potential behaviors such as required authentication, issue existence, or rate limits.

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 with no wasted words, front-loading the purpose and using a structured Args/Returns format that is clear and easy to parse.

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

Completeness3/5

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

With no output schema and low complexity, the description minimally explains returns ('Dictionary with issue details or error') but lacks specifics on the fields included, leaving some ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, so the description adds value by specifying the format ('PROJ-123') for the issue_id parameter, which is not present in the schema.

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 verb 'Get' and the resource 'specific Linear issue', distinguishing it from sibling tools like linear_list_issues (list) and linear_update_issue (write).

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?

While the description implies usage for retrieving a single issue, it does not explicitly state when to use this tool over alternatives like linear_list_issues or provide any exclusions or prerequisites.

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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