linear-issue

仓库: n8n-io/n8n
安装量: 107
排名: #7904

安装

npx skills add https://github.com/n8n-io/n8n --skill linear-issue
Linear Issue Analysis
Start work on Linear issue
$ARGUMENTS
Prerequisites
This skill depends on external tools. Before proceeding, verify availability:
Required:
Linear MCP
(
mcp__linear
): 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
(
mcp__notion
): 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
(
/loom-transcript
): 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 to fetch the issue details and comments together:
Use
mcp__linear__get_issue
with the issue ID to get full details including attachments
Include relations to see blocking/related/duplicate issues
Immediately after
, use
mcp__linear__list_comments
with the issue ID to fetch all comments
Both calls should be made together in the same step to gather the complete context upfront.
2. 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):
Scan the issue description AND all comments for ALL image URLs:
tags
Markdown images
Raw URLs (github.com/user-attachments, imgur.com, etc.)
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
Do NOT skip images - they often contain critical context like error messages, UI states, or configuration
Loom Videos (ALWAYS fetch transcript):
Scan the issue description AND all comments for Loom URLs (loom.com/share/...)
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
Loom videos often contain crucial reproduction steps and context that text alone cannot convey
3. Fetch Related Context
Related Linear Issues:
Use
mcp__linear__get_issue
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
for pull requests
gh issue view
for issues
Download images attached to issues:
curl -H "Authorization: token $(gh auth token)" -L -o image.png
Notion Documents:
If Notion links are present, use
mcp__notion__notion-fetch
with the Notion URL or page ID to retrieve document content
Summarize relevant documentation
4. 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 2)
Clarifications or updates to the original issue description
5. 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:
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.
(e.g. "HTTP Request" →
n8n-nodes-base.httpRequest
)
Trigger variants:
n8n-nodes-base.Trigger
(e.g. "Gmail Trigger" →
n8n-nodes-base.gmailTrigger
)
Tool variants:
n8n-nodes-base.Tool
(e.g. "Google Sheets Tool" →
n8n-nodes-base.googleSheetsTool
)
LangChain/AI nodes:
@n8n/n8n-nodes-langchain.
(e.g. "OpenAI Chat Model" →
@n8n/n8n-nodes-langchain.lmChatOpenAi
)
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.
If the node is
not found
in the popularity file, note that it may be a community node or a very new/niche node.
6. Assess Effort/Complexity
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.
7. 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:
Issue Overview
Title, status, priority, assignee, labels
Description
Full issue description with any clarifications from comments
Visual Context
Summary of screenshots/videos (what you observed in each)
Affected Node
(if applicable): Node name, node type ID (
n8n-nodes-base.xxx
), popularity score with level (e.g.
0.64 — medium popularity
)
Related Issues
How this connects to other work
Technical Context
Any PRs, code references, or documentation
Effort Estimate
T-shirt size (XS/S/M/L/XL) with justification
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
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