
linear-type-labeler
✓ Official★ 2by sentry · part of getsentry/sdk-skills
Classifies Linear issues and applies a Type label from the Sentry workspace's label taxonomy based on the content of each issue's title and description.
This is the playbook your agent receives when the skill activates — you don't need to read it to use the skill, but it's here to audit before installing.
name: linear-type-labeler description: > Classify and apply Type labels to Linear issues based on their title and description. allowed-tools: mcp__linear-server__query_data mcp__linear-server__get_issue mcp__linear-server__save_issue AskUserQuestion compatibility: Requires the Linear MCP server to be configured.
Linear Type Labeler
Classifies Linear issues and applies a Type label from the Sentry workspace's label taxonomy based on the content of each issue's title and description.
Type Label Reference
Type labels in the Sentry workspace (workspace-level, not per-team):
| Label | When to use |
|---|---|
| Bug | Something is broken, regression, error, crash, incorrect behavior |
| Feature | New capability, integration, API, SDK support — something that doesn't exist yet |
| Improvement | Making existing functionality better — performance, DX, UX, reliability |
| Task | Chore, investigation, spike, migration, cleanup, operational work |
| Tracking Issue | Parent/umbrella tracking a larger body of work; has sub-issues or a checklist |
| Docs | Documentation, RFC, write-up, changelog, guide |
| Tests | Writing or fixing tests, coverage, test infrastructure |
Workflow
Step 1 — Identify issues to process
Two modes:
A — List of Linear IDs provided (e.g. SDK-123, SDK-456):
- Fetch each issue by ID using
get_issue. Skip the team-fetch step entirely.
B — No IDs provided:
- Infer the team: (1) current GitHub repository name — for the
getsentryorg, the repo name matches the Linear team name, (2) explicitly stated by the user, (3) if still ambiguous, ask.
Step 2 — Fetch label IDs
Use query_data to fetch workspace-level labels and build a UUID map:
query_data: fetch all labels for the workspace (not the team)
→ filter to those whose parent label name is "Type"
→ build a map: { "Bug": "<uuid>", "Feature": "<uuid>", ... }If the workspace has no "Type" label group, surface that to the user before proceeding.
Step 3 — Fetch and filter issues
If in mode A (list of IDs): use the already-fetched issues from Step 1. Filter client-side: keep only those where none of the issue's label IDs appear in the Step 2 UUID map values.
If in mode B (team): use query_data to list issues for the team, including each issue's
label IDs. Paginate (limit 50, use cursor) until done. Filter client-side: keep only issues
where none of the issue's label IDs appear in the Step 2 UUID map values (i.e., no Type label
assigned yet).
Announce the total candidate count before continuing. If there are more than 25 candidates, process in chunks of 25, confirming each chunk before the next.
Step 4 — Classify each issue
For each candidate issue, read its title and description. Apply heuristics in priority order — stop at the first match:
- Title or description is clearly about testing work: mentions "test", "tests", "coverage", "test infra", "test suite", "unit test", "integration test" → Tests
- Title or description is clearly about documentation: mentions "docs", "README", "changelog", "RFC", "spec", "guide", "write-up", "develop.sentry.dev" → Docs
- Title contains
[META],[EPIC], "Track", "Tracking"; or description has a checklist of Linear/GitHub issue links → Tracking Issue - Title starts with "Fix", "Fixes", "Broken", "Error", "Crash", "Regression" → Bug
- Title starts with "Improve", "Optimize", "Enhance"; or is a refactor with user-visible impact (changes behavior, performance, or API ergonomics) → Improvement
- Title starts with "Investigate", "Spike", "Migrate", "Update", "Clean up", "Chore"; or is a refactor with no user-visible change → Task
- Title starts with "Add", "Support", "Implement", "New", "Introduce"; or adds something that doesn't exist yet → Feature
When ambiguous between Feature and Improvement: does it add something that doesn't exist at all, or make something existing better? Former → Feature, latter → Improvement.
When ambiguous between Task and Improvement: is there a user-visible benefit (better performance, reliability, DX, API ergonomics)? If yes → Improvement. If it's purely internal with no user-visible impact → Task.
Assign exactly one Type label. Mark confidence:
- High — clear signal in title or description
- Low — genuinely ambiguous; flag for human review, don't guess
Step 5 — Present the plan
Show a summary table before writing anything:
| Issue | Title | Proposed Type | Confidence |
|---------|------------------------|---------------|---------------------|
| SDK-123 | Fix crash on startup | Bug | High |
| SDK-456 | Add OAuth support | Feature | High |
| SDK-789 | Some vague title | Task | Low — please review |Ask: "Should I apply these labels? Reply with any corrections (e.g. 'SDK-789 → Bug') and I'll update the plan before applying."
If the user provides corrections, update the table and show the revised plan before proceeding.
Step 6 — Apply labels
For each approved classification:
- Call
get_issueto fetch the issue's current label IDs immediately before writing - Append the Type label UUID from the Step 2 map
- Call
save_issuewith the full combined label set
Always re-fetch and always pass the full combined set. Linear replaces labels on update — labels added between Step 3 and now would be silently stripped if you use the cached label list.
Report as you go: "SDK-123 → Bug", "SDK-456 → Feature".
Edge Cases
- Issue already has a Type label: Skip it; don't overwrite human classifications.
- Very short title, no description: Flag as low-confidence; surface for human review.
- Issue belongs to multiple types: Pick the primary type (bug fix with a docs update → Bug).
npx skills add https://github.com/getsentry/sdk-skills --skill linear-type-labelerRun this in your project — your agent picks the skill up automatically.
Requirements
This skill requires the Linear MCP server to be configured.
No common issues documented yet. If you hit a problem, the repository's GitHub Issues page is the best place to look.