linear

Manage Linear issues, projects, and team workflows with structured MCP integration. Provides 20+ tools across issue management, project planning, documentation search, and team collaboration Supports eight practical workflows including sprint planning, bug triage, workload balancing, release planning, and retrospectives Requires Linear MCP server setup with OAuth authentication; includes Windows/WSL configuration guidance Executes operations in logical batches: read first for context, then...

npx skills add https://github.com/openai/skills --skill linear

Linear

Overview

This skill provides a structured workflow for managing issues, projects & team workflows in Linear. It ensures consistent integration with the Linear MCP server, which offers natural-language project management for issues, projects, documentation, and team collaboration.

Prerequisites

  • Linear MCP server must be connected and accessible via OAuth
  • Confirm access to the relevant Linear workspace, teams, and projects

Required Workflow

Follow these steps in order. Do not skip steps.

Step 0: Set up Linear MCP (if not already configured)

If any MCP call fails because Linear MCP is not connected, pause and set it up:

  1. Add the Linear MCP:
    • codex mcp add linear --url https://mcp.linear.app/mcp
  2. Enable remote MCP client:
    • Set [features] rmcp_client = true in config.toml or run codex --enable rmcp_client
  3. Log in with OAuth:
    • codex mcp login linear

After successful login, the user will have to restart codex. You should finish your answer and tell them so when they try again they can continue with Step 1.

Windows/WSL note: If you see connection errors on Windows, try configuring the Linear MCP to run via WSL:

{"mcpServers": {"linear": {"command": "wsl", "args": ["npx", "-y", "mcp-remote", "https://mcp.linear.app/sse", "--transport", "sse-only"]}}}

Step 1

Clarify the user's goal and scope (e.g., issue triage, sprint planning, documentation audit, workload balance). Confirm team/project, priority, labels, cycle, and due dates as needed.

Step 2

Select the appropriate workflow (see Practical Workflows below) and identify the Linear MCP tools you will need. Confirm required identifiers (issue ID, project ID, team key) before calling tools.

Step 3

Execute Linear MCP tool calls in logical batches:

  • Read first (list/get/search) to build context.
  • Create or update next (issues, projects, labels, comments) with all required fields.
  • For bulk operations, explain the grouping logic before applying changes.

Step 4

Summarize results, call out remaining gaps or blockers, and propose next actions (additional issues, label changes, assignments, or follow-up comments).

Available Tools

Issue Management: list_issues, get_issue, create_issue, update_issue, list_my_issues, list_issue_statuses, list_issue_labels, create_issue_label

Project & Team: list_projects, get_project, create_project, update_project, list_teams, get_team, list_users

Documentation & Collaboration: list_documents, get_document, search_documentation, list_comments, create_comment, list_cycles

Practical Workflows

  • Sprint Planning: Review open issues for a target team, pick top items by priority, and create a new cycle (e.g., "Q1 Performance Sprint") with assignments.
  • Bug Triage: List critical/high-priority bugs, rank by user impact, and move the top items to "In Progress."
  • Documentation Audit: Search documentation (e.g., API auth), then open labeled "documentation" issues for gaps or outdated sections with detailed fixes.
  • Team Workload Balance: Group active issues by assignee, flag anyone with high load, and suggest or apply redistributions.
  • Release Planning: Create a project (e.g., "v2.0 Release") with milestones (feature freeze, beta, docs, launch) and generate issues with estimates.
  • Cross-Project Dependencies: Find all "blocked" issues, identify blockers, and create linked issues if missing.
  • Automated Status Updates: Find your issues with stale updates and add status comments based on current state/blockers.
  • Smart Labeling: Analyze unlabeled issues, suggest/apply labels, and create missing label categories.
  • Sprint Retrospectives: Generate a report for the last completed cycle, note completed vs. pushed work, and open discussion issues for patterns.

Tips for Maximum Productivity

  • Batch operations for related changes; consider smart templates for recurring issue structures.
  • Use natural queries when possible ("Show me what John is working on this week").
  • Leverage context: reference prior issues in new requests.
  • Break large updates into smaller batches to avoid rate limits; cache or reuse filters when listing frequently.

Troubleshooting

  • Authentication: Clear browser cookies, re-run OAuth, verify workspace permissions, ensure API access is enabled.
  • Tool Calling Errors: Confirm the model supports multiple tool calls, provide all required fields, and split complex requests.
  • Missing Data: Refresh token, verify workspace access, check for archived projects, and confirm correct team selection.
  • Performance: Remember Linear API rate limits; batch bulk operations, use specific filters, or cache frequent queries.

More skills from openai

user-context
openai
Load or manage the Data Analytics plugin's durable source-routing preferences, onboarding logic, setup progress, and semantic-layer registry.
official
notion-research-documentation
openai
Research Notion content and synthesize into structured briefs, reports, or comparisons with citations. Search and fetch Notion pages using targeted queries, then organize findings by theme with inline source citations and a references section Choose from four output formats (quick brief, research summary, comparison, comprehensive report) based on scope and user goal Create and update Notion pages using built-in templates; link sources directly and track changes as new information arrives...
official
rcsb-pdb-skill
openai
Submit compact RCSB PDB requests for core metadata, Search API queries, and FASTA downloads. Use when a user wants concise RCSB summaries; save raw JSON or…
official
pdf
openai
PDF reading, creation, and validation with visual rendering and programmatic generation. Render PDF pages to PNG for visual inspection of layout, spacing, and typography before delivery using Poppler ( pdftoppm ) Generate PDFs programmatically with reportlab for reliable formatting; extract text and metadata with pdfplumber or pypdf Enforce quality standards: no clipped text, overlapping elements, broken tables, or rendering artifacts; ASCII hyphens only, human-readable citations Use...
official
test-coverage-improver
openai
Improve test coverage in the OpenAI Agents JS monorepo: run `pnpm test:coverage`, inspect coverage artifacts, identify low-coverage files and branches, propose…
official
playwright
openai
Terminal-driven browser automation with element snapshots and interactive UI workflows. Operates via playwright-cli wrapper script (requires npx ); supports headless and headed modes for visual debugging Core workflow: open page, snapshot for stable element references, interact using refs, re-snapshot after navigation or DOM changes Includes form filling, clicking, typing, multi-tab management, screenshot/PDF capture, and trace recording for flow debugging Element refs (e.g., e3 , e15 )...
official
ukb-topmed-phewas-skill
openai
Fetch compact UKB-TOPMed PheWAS summaries for single variants by accepting rsID, GRCh37, or GRCh38 input and resolving to the required GRCh38 query. Use when a…
official
code-review-context
openai
Model visible context
official