openai-skills--linear — community openai-skills--linear, Dhanvanthiri, community, ide skills

v1.0.0

关于此技能

非常适合需要结构化工作流和团队协作的 Linear 项目管理代理 Manage issues, projects & team workflows in Linear. Use when the user wants to read, create or updates tickets in Linear.

vigneshsinna vigneshsinna
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更新于: 3/8/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 6/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
6/11
Quality Score
42
Canonical Locale
en
Detected Body Locale
en

非常适合需要结构化工作流和团队协作的 Linear 项目管理代理 Manage issues, projects & team workflows in Linear. Use when the user wants to read, create or updates tickets in Linear.

核心价值

赋予代理管理 Linear 中的问题、项目和团队工作流的能力,确保通过 OAuth 与 Linear MCP 服务器进行一致的集成,并提供自然语言项目管理用于问题、项目、文档和团队协作

适用 Agent 类型

非常适合需要结构化工作流和团队协作的 Linear 项目管理代理

赋予的主要能力 · openai-skills--linear

在 Linear 中自动化项目管理工作流
生成问题报告和项目更新
与团队在文档和项目规划上进行协作

! 使用限制与门槛

  • 需要 Linear MCP 服务器连接和通过 OAuth 的访问
  • 需要访问相关的 Linear 工作空间、团队和项目

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

评审后的下一步

先决定动作,再继续看上游仓库材料

Killer-Skills 的主价值不应该停在“帮你打开仓库说明”,而是先帮你判断这项技能是否值得安装、是否应该回到可信集合复核,以及是否已经进入工作流落地阶段。

实验室 Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致,便于搜索引擎理解页面内容。

? FAQ

openai-skills--linear 是什么?

非常适合需要结构化工作流和团队协作的 Linear 项目管理代理 Manage issues, projects & team workflows in Linear. Use when the user wants to read, create or updates tickets in Linear.

如何安装 openai-skills--linear?

运行命令:npx killer-skills add vigneshsinna/Dhanvanthiri/openai-skills--linear。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

openai-skills--linear 适用于哪些场景?

典型场景包括:在 Linear 中自动化项目管理工作流、生成问题报告和项目更新、与团队在文档和项目规划上进行协作。

openai-skills--linear 支持哪些 IDE 或 Agent?

该技能兼容 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer。可使用 Killer-Skills CLI 一条命令通用安装。

openai-skills--linear 有哪些限制?

需要 Linear MCP 服务器连接和通过 OAuth 的访问;需要访问相关的 Linear 工作空间、团队和项目。

安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行:npx killer-skills add vigneshsinna/Dhanvanthiri/openai-skills--linear。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    openai-skills--linear 已启用,可立即在当前项目中调用。

! 参考页模式

此页面仍可作为安装与查阅参考,但 Killer-Skills 不再把它视为主要可索引落地页。请优先阅读上方评审结论,再决定是否继续查看上游仓库说明。

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

openai-skills--linear

安装 openai-skills--linear,这是一款面向AI agent workflows and automation的 AI Agent Skill。查看评审结论、使用场景与安装路径。

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

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:

json
1{"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.

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