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Read Linear Issue

linear_get_issue
Read-only

Read one Linear issue by its identifier (e.g. 'ENG-123') or UUID. Returns title, description, state, assignee, priority, labels and URL. Use this whenever the task mentions a Linear issue — do not rely on details pasted into the prompt, which may be stale. Read-only.

Input Schema

NameRequiredDescriptionDefault
issueYesLinear issue identifier such as 'ENG-123', or the issue UUID.
contextNoExplain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so 'Read-only' is redundant, but the description earns its keep by enumerating the returned fields and warning that prompt-pasted issue data may be stale — behavior an agent cannot get from the schema. It does not mention error behavior for unknown identifiers, which keeps it out of 5 territory.

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?

Three short sentences, front-loaded with the identifier and return shape, then the usage rule. Nothing is padding; only 'Read-only' duplicates structured data.

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?

For a two-parameter read tool with full schema coverage and annotations carrying the safety profile, the description covers what it fetches, how to identify the issue, and when to prefer it over stale prompt context. No output schema exists, and the field list compensates adequately.

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% and both parameters are thoroughly documented in the schema, including the 'ENG-123' example and the elaborate analytics constraint on `context`. The description repeats the identifier example but adds no new semantics, so baseline 3 applies.

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 ('Read one Linear issue') plus the two accepted identifier forms, and lists exactly what comes back. It is clearly distinguishable from linear_search_issues and linear_get_comments, which do different things.

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?

Gives an explicit trigger ('whenever the task mentions a Linear issue') and a prohibition against trusting pasted-in details that may be stale, which is a real routing signal. It stops short of naming a sibling for multi-issue/matching workflows, so the when-not side is inferred rather than stated.

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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