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update_issue

Update an existing Linear issue by its identifier, altering only the fields you specify—status, assignee, priority, title, description, or labels. Labels passed replace the issue's current labels.

Instructions

Update fields on an existing Linear issue. Only the fields you pass are changed. identifier: human issue identifier, e.g. "GOV-123". state, assignee, labels: names, resolved against the issue's own team. priority: 0 none, 1 urgent, 2 high, 3 medium, 4 low. Passing labels replaces the issue's labels entirely.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateNo
titleNo
labelsNo
assigneeNo
priorityNo
identifierYes
descriptionNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries full behavioral weight and does so well: it discloses partial-update semantics, the destructive label-replacement behavior, name resolution against the issue's team, and the priority scale. This goes well beyond the schema and tells an agent exactly what side effects to expect.

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 compact, front-loaded with the core behavior, and uses a clear bullet-like structure for field semantics. Every sentence adds information; there is no repetition of schema 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 7-parameter mutation without annotations or an output schema, it covers the essential invocation semantics well: which fields are updateable, how values are resolved, and the destructive label behavior. It could additionally state the return value or null-clear semantics, but these are not blocking for correct use.

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

Parameters5/5

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

Schema description coverage is 0%, and the description compensates thoroughly: it explains the identifier format, the resolution rules for state/assignee/labels, the exact priority mapping, and the labels replacement behavior. Even without documentation on title/description, their meaning is self-evident from names and the update purpose.

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 opens with 'Update fields on an existing Linear issue', a specific verb+resource that distinguishes this from sibling create_issue (new issue) and read-only tools. The qualifier 'existing' plus the identifier field makes the tool's job unmistakable.

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?

It clearly frames the tool for modifying an existing issue rather than creating one, and clarifies that only passed fields change, which is the core usage rule. It does not explicitly name an alternative or state when not to use it, but the contrast with create_issue is implied by 'existing'.

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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