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linear_create_issue

Creates a new issue in Linear by specifying title, description, and team ID, with optional fields for priority, estimate, assignee, project, and display settings.

Instructions

Create a new issue in Linear

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesIssue title
teamIdYesTeam ID
estimateNoIssue estimate points (typically 1, 2, 3, 5, 8, etc.)
priorityNoIssue priority (0-4)
projectIdNoProject ID
assigneeIdNoAssignee user ID
descriptionYesIssue description
createAsUserNoName to display for the created issue
displayIconUrlNoURL of the avatar to display
Behavior1/5

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

With no annotations provided, the description must disclose behavioral traits, but it only states the action. It fails to mention authentication requirements, potential side effects, return values, or any constraints. This is a significant gap for a write operation.

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 a single sentence with no redundancy or filler. It is front-loaded and adequately concise for a simple CRUD tool, though this brevity comes at the cost of completeness.

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

Completeness2/5

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

Given the tool has 9 parameters, no annotations, and no output schema, the description is too sparse. It does not explain what the tool returns, how it behaves beyond the obvious, or any important context like required teamId. The schema covers parameters, but the overall context is incomplete.

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?

The input schema covers 100% of parameters with descriptions, so the description does not need to add meaning. The baseline of 3 applies because the schema handles the heavy lifting, and the description contributes nothing extra.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action ('Create a new issue') and resource ('Linear'), making it distinct from other tools like comments. However, it does not differentiate from the plural 'linear_create_issues' nor mention any scope, so it stops short of a perfect score.

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 guidance on when to use this tool versus alternatives such as linear_create_issues (bulk creation) or linear_create_project_with_issues. There is no mention of prerequisites or context, leaving the agent without direction.

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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