Token导航 LogoToken导航

Agent Skill · 研究检索

linear-agent-api(Linear Agent API 搜索)

用于处理 Linear 项目、Issue、团队、周期和产品开发任务流。它适合让 Agent 辅助查询任务状态、整理需求队列、创建缺陷或汇总迭代进展。使用时需要确认 workspace、team、label、assignee 和状态流转规则;涉及批量创建或修改任务时,应先核对字段和目标团队,避免把草稿需求直接写入正式项目。

linear-agent-api 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 57,063。

总安装 441周安装 18GitHub Stars 公开资料未说明下载 141核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:linear-agent-api(Linear Agent API 搜索)
来源仓库:https://github.com/5dlabs/cto
仓库路径:skills/linear-agent-api
安装命令:
npx skills add 5dlabs/cto --skill "linear-agent-api"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add 5dlabs/cto --skill "linear-agent-api"

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

Linear Agent API 技能支持通过自然语言创建、更新和查询 Linear 项目任务。适用于自动化工作流集成,如将用户反馈自动转为开发工单。通过 npx skills add 5dlabs/cto --skill "linear-agent-api" 安装。

使用前应熟悉 Linear 状态机规则,避免非法状态转换报错。建议设置重试机制与异常捕获,提升鲁棒性。

来源仓库内路径:skills/linear-agent-api

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add 5dlabs/cto --skill "linear-agent-api";命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

linear-agent-api 怎么安装?

在终端执行 npx skills add 5dlabs/cto --skill "linear-agent-api"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

linear-agent-api 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

linear-agent-api 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

linear-agent-api 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

linear-agent-api 用的人多吗?

公开数据是累计安装 441 次,近一周安装 18 次,下载 141 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

linear-agent-api 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
linear-agent-api

Linear Agent API 搜索 · 本页

441—需要联网MIT未收录

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Linear Agent API Skill

Comprehensive reference for Linear's Agent API, following the Agent Interaction Guidelines (AIG).

When to Use

  • Verifying agent sessions are created correctly
  • Checking activity streaming (thought, action, response)
  • Implementing two-way communication (user input, stop signals)
  • Debugging Linear integration issues

Agent Session Lifecycle

Sessions track the lifecycle of an agent run:

StateMeaning
pendingSession created, waiting for agent
activeAgent is working
awaitingInputAgent needs user input
errorSomething went wrong
completeWork finished

Sessions are created automatically when an agent is @mentioned or assigned as delegate.


Agent Activity Types

TypePurposeWho Creates
thoughtAgent reasoning, progress updatesAgent
actionTool invocations (with optional result)Agent
elicitationRequest user input or clarificationAgent
responseFinal completion messageAgent
errorReport failureAgent
promptUser follow-up messageHuman

Activity Payloads

// thought - Agent thinking
{
  "content": {
    "type": "thought",
    "body": "Analyzing the codebase structure..."
  }
}

// action - Tool call
{
  "content": {
    "type": "action",
    "action": "edit_file",
    "parameter": "src/main.rs"
  }
}

// action with result
{
  "content": {
    "type": "action",
    "action": "run_tests",
    "result": "All 42 tests passed"
  }
}

// elicitation - Request input
{
  "content": {
    "type": "elicitation",
    "body": "Which database should I use?"
  }
}

// response - Completion
{
  "content": {
    "type": "response",
    "body": "Implementation complete. PR #123 created."
  }
}

// error - Failure
{
  "content": {
    "type": "error",
    "body": "Build failed: missing dependency"
  }
}

Ephemeral Activities

Activities can be marked ephemeral: true for temporary status messages that get replaced by the next activity. Only thought and action types support this.


Signals (Two-Way Communication)

Human-to-Agent Signals

stop Signal

When user clicks "Send stop request" in Linear, agent receives a prompt activity with signal: "stop".

Agent MUST:

  1. Halt immediately - No further code changes or API calls
  2. Emit final activity - response or error confirming stop
  3. Report current state - What was completed, what remains

CTO Implementation: The status-sync.rs sidecar detects signal: "stop" in polled activities and triggers graceful shutdown via /stop endpoint.

Agent-to-Human Signals

auth Signal

Used with elicitation to request account linking:

{
  "content": { "type": "elicitation", "body": "Please authenticate" },
  "signal": "auth",
  "signalMetadata": {
    "url": "https://auth.example.com/oauth",
    "providerName": "GitHub"
  }
}
select Signal

Used with elicitation to present multiple choice options:

{
  "content": { "type": "elicitation", "body": "Which repository?" },
  "signal": "select",
  "signalMetadata": {
    "options": [
      { "value": "5dlabs/cto" },
      { "value": "5dlabs/alertub" }
    ]
  }
}

Agent Plans (Checklists)

Agents can provide session-level task checklists:

{
  "plan": [
    { "content": "Parse PRD document", "status": "completed" },
    { "content": "Generate task breakdown", "status": "inProgress" },
    { "content": "Create Linear issues", "status": "pending" }
  ]
}

Status values: pending, inProgress, completed, canceled

Note: Plan updates replace the entire array, not individual items.


Best Practices

1. First Response Within 10 Seconds

Upon receiving created webhook, agent MUST emit a thought activity within 10 seconds or be shown as unresponsive.

2. Follow-up Activities Within 30 Minutes

After first response, activities can be sent for up to 30 minutes before session is stale.

3. Delegate vs Assignee

  • Delegate = The agent working on the issue
  • Assignee = The human responsible (ownership)

Agents should set themselves as delegate, not assignee.

4. Status Updates

When starting work, move issue to first "started" status if not already there.

5. Completion

When work complete, emit response activity. If user action needed, emit elicitation or error.


GraphQL Queries

Get Session Activities

query AgentSession($agentSessionId: String!) {
  agentSession(id: $agentSessionId) {
    id
    state
    createdAt
    activities {
      edges {
        node {
          updatedAt
          content {
            ... on AgentActivityThoughtContent { body }
            ... on AgentActivityActionContent { action parameter result }
            ... on AgentActivityElicitationContent { body }
            ... on AgentActivityResponseContent { body }
            ... on AgentActivityErrorContent { body }
            ... on AgentActivityPromptContent { body }
          }
        }
      }
    }
  }
}

Get Team Started Statuses

query TeamStartedStatuses($teamId: String!) {
  team(id: $teamId) {
    states(filter: { type: { eq: "started" } }) {
      nodes {
        id
        name
        position
      }
    }
  }
}

CTO Status-Sync Implementation

The status-sync.rs sidecar implements:

FunctionPurpose
emit_thought()Progress updates
emit_ephemeral_thought()Transient status
emit_action()Tool invocations
emit_action_complete()Tool results
emit_error()Error reporting
emit_response()Final completion
update_plan()Checklist updates
get_session_activities()Poll for user input

Input Polling: The input_poll_task periodically calls get_session_activities() to detect:

  • New prompt activities from users
  • signal: "stop" requests

Webhook Events

EventActionDescription
AgentSessionEventcreatedAgent mentioned/delegated
AgentSessionEventpromptedUser sent follow-up message
AppUserNotificationissueAssignedToYouIssue delegated to agent
AppUserNotificationissueUnassignedFromYouAgent removed from issue

Reference Documentation

平台分布

Claude Code

29.55%
按下载量换算42

OpenCode

24.62%
按下载量换算35

windsurf

15.87%
按下载量换算22

trae

12.73%
按下载量换算18

Codex

6.77%
按下载量换算10

Antigravity

3.68%
按下载量换算5

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills