n8n-linear-issue

name	n8n:linear-issue
description	Fetch and analyze Linear issue with all related context. Use when starting work on a Linear ticket, analyzing issues, or gathering context about a Linear issue.
argument-hint	[issue-id]
compatibility	{"requires":[{"mcp":"linear","description":"Core dependency — used to fetch issue details, relations, and comments"},{"cli":"gh","description":"GitHub CLI — used to fetch linked PRs and issues. Must be authenticated (gh auth login)"}],"optional":[{"mcp":"notion","description":"Used to fetch linked Notion documents. Skip Notion steps if unavailable."},{"skill":"loom-transcript","description":"Used to fetch Loom video transcripts. Skip Loom steps if unavailable."},{"cli":"curl","description":"Used to download images/attachments. Typically pre-installed."}]}

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. Run gh auth status to 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 public n8n-io/n8n repo. Mixed remotes are not allowed — you must work in a separate local clone of n8n-io/n8n-private with 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 ![](url)
   • 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 Read tool 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 gh CLI to fetch PR/issue details:
  • gh pr view <number> for pull requests
  • gh 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.

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 gh CLI
• 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 just 1975 (will search)
• If no issue ID is provided, ask the user for one