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linear-agent-apiLinear Agent API 搜索

Agent Skill

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。

总安装

441

周安装

18

GitHub Stars

公开资料未说明

下载量

141
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

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"

简介

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。

SKILL.md

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

适合场景

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用户想查找某类 Agent Skill 时

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需要根据任务场景推荐可安装能力包时

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需要对比不同来源的安装命令和来源信息时

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需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

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能力 4

补充不同宿主或平台的使用分布数据

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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

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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

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来源信息

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