
Linear Issue
- 314 installs
- 199k repo stars
- Updated August 5, 2026
- n8n-io/n8n
linear-issue is an n8n agent skill that fetches and analyzes Linear issues with linked GitHub PRs, comments, and optional Notion or Loom context for developers starting work on a ticket.
About
linear-issue is an agent skill from n8n-io/n8n that fetches and analyzes a Linear issue with full related context before development begins. The skill requires the Linear MCP for issue details, relations, and comments, plus the GitHub CLI (gh) authenticated via gh auth login to pull linked PRs and issues. Optional integrations include the Notion MCP for linked documents and the loom-transcript skill for video transcripts—steps skip gracefully when unavailable. Developers invoke it with an issue ID when starting ticket work, analyzing bugs, or gathering sprint context. Argument hint accepts [issue-id]. The workflow produces a consolidated issue brief covering description, relations, comments, linked PRs, and external doc excerpts so agents file updates and keep boards current without tab-hopping across Linear, GitHub, and Notion.
- Linear issue creation
- label and cycle assignment
- PR linkage context
- triage templates
- backlog sync
Linear Issue by the numbers
- 314 all-time installs (skills.sh)
- Ranked #870 of 3,282 Productivity & Planning skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/n8n-io/n8n --skill linear-issueAdd your badge
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| Installs | 314 |
|---|---|
| repo stars | ★ 199k |
| Last updated | August 5, 2026 |
| Repository | n8n-io/n8n ↗ |
How do you gather full Linear issue context?
Create, update, and triage Linear issues from n8n development workflows so agents file bugs, link PRs, and keep sprint boards current.
Who is it for?
Developers starting Linear ticket work who need GitHub PR links, comments, and optional Notion or Loom context in one agent session.
Skip if: Teams without Linear MCP or an authenticated gh CLI who cannot fetch linked GitHub pull request data.
When should I use this skill?
A developer provides a Linear issue ID and asks to analyze, triage, or gather context before implementing the ticket.
What you get
Consolidated Linear issue brief with relations, comments, linked GitHub PRs, and optional Notion or Loom excerpts
- issue context brief
- linked PR summary
- comment thread digest
By the numbers
- Requires 2 core dependencies: Linear MCP and authenticated GitHub CLI
- Supports 2 optional integrations: Notion MCP and loom-transcript skill
Files
Linear Issue Analysis
Start work on Linear issue $ARGUMENTS
Prerequisites
This skill depends on external tools. Before proceeding, verify availability:
Required:
- Linear MCP: Must be connected. Without it the skill cannot function at all.
- GitHub CLI (
gh): Must be installed and authenticated. Rungh auth statusto verify. Used to fetch linked PRs and issues.
Optional (graceful degradation):
- Notion MCP: Needed only if the issue links to Notion docs. If unavailable, note the Notion links in the summary and tell the user to check them manually.
- Loom transcript skill: Needed only if the issue contains Loom videos. If unavailable, note the Loom links in the summary for the user to watch.
- curl: Used to download images. Almost always available; if missing, skip image downloads and note it.
If a required tool is missing, stop and tell the user what needs to be set up before continuing.
Instructions
Follow these steps to gather comprehensive context about the issue:
1. Fetch the Issue and Comments from Linear
Use the Linear MCP tools available in the active harness to fetch the issue details and comments together:
- Fetch the issue by ID to get full details including attachments
- Include relations to see blocking/related/duplicate issues
- Immediately after, fetch all comments for the issue ID
Both calls should be made together in the same step to gather the complete context upfront.
2. Check for Private/Security Issues (MANDATORY — do this before anything else)
After fetching the issue, immediately check its labels:
1. Look at the labels returned with the issue. 2. If any label is `n8n-private`: a. Run git remote -v (via Bash) to list all configured remotes. b. If any remote URL contains n8n-io/n8n without the -private suffix (i.e. matches the public repo), stop immediately and tell the user:
This issue is marked `n8n-private` and must be developed in a clean clone of the private repository.
>
One or more of your remotes point to the publicn8n-io/n8nrepo. Mixed remotes are not allowed — you must work in a separate local clone ofn8n-io/n8n-privatewith no references to the public repo.
For the full process, see: https://www.notion.so/n8n/Processing-critical-high-security-bugs-vulnerabilities-in-private-2f45b6e0c94f803da806f472111fb1a5
Do not continue with any further steps — return after showing this message.
3. If the label is not present, or all remotes point exclusively to n8n-io/n8n-private, continue normally.
3. Analyze Attachments and Media (MANDATORY)
IMPORTANT: This step is NOT optional. You MUST scan and fetch all visual content from BOTH the issue description AND all comments.
Screenshots/Images (ALWAYS fetch):
1. Scan the issue description AND all comments for ALL image URLs:
<img>tags- Markdown images
 - Raw URLs (github.com/user-attachments, imgur.com, etc.)
2. For EACH image found (in description or comments):
- Download using
curl -sL "url" -o /path/to/image.png(GitHub URLs require following redirects) OR the linear mcp - Use the
Readtool on the downloaded file to view it - Describe what you see in detail
3. Do NOT skip images - they often contain critical context like error messages, UI states, or configuration
Loom Videos (ALWAYS fetch transcript):
1. Scan the issue description AND all comments for Loom URLs (loom.com/share/...) 2. For EACH Loom video found (in description or comments):
- Use the Loom transcript skill to fetch the FULL transcript
- Summarize key points, timestamps, and any demonstrated issues
3. Loom videos often contain crucial reproduction steps and context that text alone cannot convey
4. Fetch Related Context
Related Linear Issues:
- Use the Linear MCP issue-fetching tool for any issues mentioned in relations (blocking, blocked by, related, duplicates)
- Summarize how they relate to the main issue
GitHub PRs and Issues:
- If GitHub links are mentioned, use
ghCLI to fetch PR/issue details: gh pr view <number>for pull requestsgh issue view <number>for issues- Download images attached to issues:
curl -H "Authorization: token $(gh auth token)" -L <image-url> -o image.png
Notion Documents:
- If Notion links are present, use the Notion MCP fetch tool with the Notion URL or page ID to retrieve document content
- Summarize relevant documentation
5. Review Comments
Comments were already fetched in Step 1. Review them for:
- Additional context and discussion history
- Any attachments or media linked in comments (process in Step 3)
- Clarifications or updates to the original issue description
6. Identify Affected Node (if applicable)
Determine whether this issue is specific to a particular n8n node (e.g. a trigger, action, or tool node). Look for clues in:
- The issue title (e.g. "Linear trigger", "Slack node", "HTTP Request")
- The issue description and comments mentioning node names
- Labels or tags on the issue (e.g.
node:linear,node:slack) - Screenshots showing a specific node's configuration or error
If the issue is node-specific:
1. Find the node type ID. Use Grep to search for the node's display name (or keywords from it) in packages/frontend/editor-ui/data/node-popularity.json to find the exact node type ID. For reference, common ID patterns are:
- Core nodes:
n8n-nodes-base.<camelCaseName>(e.g. "HTTP Request" →n8n-nodes-base.httpRequest) - Trigger variants:
n8n-nodes-base.<name>Trigger(e.g. "Gmail Trigger" →n8n-nodes-base.gmailTrigger) - Tool variants:
n8n-nodes-base.<name>Tool(e.g. "Google Sheets Tool" →n8n-nodes-base.googleSheetsTool) - LangChain/AI nodes:
@n8n/n8n-nodes-langchain.<camelCaseName>(e.g. "OpenAI Chat Model" →@n8n/n8n-nodes-langchain.lmChatOpenAi)
2. Look up the node's popularity score — first check for a Flaky assessment (see below), otherwise use the popularity file:
Primary: Check for Flaky's assessment in Linear comments. Flaky is an auto-triage agent that posts issue analysis as a comment. Search the comments already fetched in Step 1 for a comment from a user named "Flaky" (or containing "Flaky" in the author name) — do not re-fetch comments. If found, extract the popularity score and level directly from Flaky's analysis and use those values.
Fallback (if no Flaky comment exists): Look up the node's popularity score from packages/frontend/editor-ui/data/node-popularity.json. Use Grep to search for the node ID in that file. The popularity score is a log-scale value between 0 and 1. Use these thresholds to classify:
| Score | Level | Description | Examples |
|---|---|---|---|
| ≥ 0.8 | High | Core/widely-used nodes, top ~5% | HTTP Request (0.98), Google Sheets (0.95), Postgres (0.83), Gmail Trigger (0.80) |
| 0.4–0.8 | Medium | Regularly used integrations | Slack (0.78), GitHub (0.64), Jira (0.65), MongoDB (0.63) |
| < 0.4 | Low | Niche or rarely used nodes | Amqp (0.34), Wise (0.36), CraftMyPdf (0.33) |
Include the raw score and the level (high/medium/low) in the summary, and note whether it came from Flaky or the popularity file.
3. If the node is not found in the popularity file (and no Flaky comment exists), note that it may be a community node or a very new/niche node.
7. Assess Effort/Complexity
Primary: Check for Flaky's effort estimate in Linear comments. Search the comments already fetched in Step 1 for a Flaky comment — do not re-fetch. If found, extract the effort/complexity estimate directly from it and use that as your assessment.
Fallback (if no Flaky comment exists): After gathering all context, assess the effort required to fix/implement the issue. Use the following T-shirt sizes:
| Size | Approximate effort |
|---|---|
| XS | ≤ 1 hour |
| S | ≤ 1 day |
| M | 2-3 days |
| L | 3-5 days |
| XL | ≥ 6 days |
To make this assessment, consider:
- Scope of changes: How many files/packages need to be modified? Is it a single node fix or a cross-cutting change?
- Complexity: Is it a straightforward parameter change, a new API integration, a new credential type, or an architectural change?
- Testing: How much test coverage is needed? Are E2E tests required?
- Risk: Could this break existing functionality? Does it need backward compatibility?
- Dependencies: Are there external API changes, new packages, or cross-team coordination needed?
- Documentation: Does this require docs updates, migration guides, or changelog entries?
Provide the T-shirt size along with a brief justification explaining the key factors that drove the estimate. Note whether it came from Flaky or your own assessment.
8. Present Summary
Before presenting, verify you have completed:
- [ ] Downloaded and viewed ALL images in the description AND comments
- [ ] Fetched transcripts for ALL Loom videos in the description AND comments
- [ ] Fetched ALL linked GitHub issues/PRs via
ghCLI - [ ] Listed all comments on the issue
- [ ] Checked whether the issue is node-specific and looked up popularity if so
- [ ] Assessed effort/complexity with T-shirt size
After gathering all context, present a comprehensive summary including:
1. Issue Overview: Title, status, priority, assignee, labels 2. Description: Full issue description with any clarifications from comments 3. Visual Context: Summary of screenshots/videos (what you observed in each) 4. Affected Node (if applicable): Node name, node type ID (n8n-nodes-base.xxx), popularity score with level (e.g. 0.64 — medium popularity) 5. Related Issues: How this connects to other work 6. Technical Context: Any PRs, code references, or documentation 7. Effort Estimate: T-shirt size (XS/S/M/L/XL) with justification 8. Next Steps: Suggested approach based on all gathered context
Notes
- The issue ID can be provided in formats like:
AI-1975,node-1975, or just1975(will search) - If no issue ID is provided, ask the user for one
Related skills
How it compares
Use linear-issue for read-heavy ticket context at work start; pair with Linear MCP write tools when creating or updating issues.
FAQ
What dependencies does linear-issue require?
linear-issue requires the Linear MCP for issue data and the GitHub CLI with gh auth login for linked PRs. Notion MCP and loom-transcript are optional; the skill skips those steps when unavailable.
When should agents invoke linear-issue?
linear-issue runs when a developer starts work on a Linear ticket, analyzes bugs, or needs full issue context. Pass an issue ID to fetch description, relations, comments, and linked GitHub artifacts in one brief.
Does linear-issue create or only fetch issues?
linear-issue primarily fetches and analyzes Linear issues with related context from GitHub and optional Notion or Loom sources. Use it to triage and gather context; separate flows handle creating or updating tickets.