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Agent Skill · 开发

task-engine(任务引擎)

task-engine 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

task-engine 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在开发类的 21,746 个 Skill 里排第 3,209。

总安装 12,290周安装 507GitHub Stars 公开资料未说明下载 4,015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-0
版本
1.0.0

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:task-engine(任务引擎)
来源仓库:https://github.com/zeron-g/task-engine
安装命令:
openclaw skills install task-engine
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install task-engine

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

多代理协作的状态机任务编排引擎。task-engine 属于开发类 Skill,可作为该场景下的辅助能力补充。支持复杂项目自动监控与跨代理任务流转。适用于多阶段、高可靠性工作流场景。安装前需确认权限范围、维护状态及是否启用后台守护进程。建议结合原始 README 核验状态同步与故障恢复机制。

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 OpenClaw;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 openclaw skills install task-engine;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

    它需要接触敏感数据,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

task-engine 怎么安装?

在终端执行 openclaw skills install task-engine。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

task-engine 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

task-engine 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

task-engine 是免费的吗?

来源标注的许可证是 MIT-0。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。

task-engine 用的人多吗?

公开数据是累计安装 12,290 次,近一周安装 507 次,下载 4,015 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。

task-engine 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
task-engine

任务引擎 · 本页

12,290—接触敏感数据MIT-0有提醒

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

name
task-engine
description
Multi-agent task orchestration engine with state machine tracking. Use when complex multi-step projects need automated monitoring, multi-agent collaboration, and Discord-based progress tracking.

Task Engine

Orchestrates multi-step projects across multiple agents (Claude Code, Eva, others) using a state machine with JSON-based persistence. Each task has subtasks dispatched to agents, tracked via heartbeat, and reported through Discord.

CLI Commands

All commands run from the skill root:

cd /home/zeron/.openclaw/workspace/skills/task-engine

All commands support --json for machine-readable output:

{"ok": true, "task_id": "TASK-001", "status": "PLANNING", "message": "Created TASK-001"}

Create a task

python3 scripts/task_engine.py create "Implement feature X" --priority P0 --plan "3 phases: models, API, tests"
python3 scripts/task_engine.py create "Feature Y" --priority P1 --json

View status

python3 scripts/task_engine.py status                    # All active tasks (table)
python3 scripts/task_engine.py status TASK-001           # Detailed single task
python3 scripts/task_engine.py status TASK-001 --json    # Machine-readable
python3 scripts/task_engine.py status --all              # Include terminal tasks

Transition task state

python3 scripts/task_engine.py transition TASK-001 approve --note "Plan approved" --json
python3 scripts/task_engine.py transition TASK-001 block --note "Waiting on API key"
python3 scripts/task_engine.py transition TASK-001 complete --note "All verified" --json

Dispatch subtask to an agent

python3 scripts/task_engine.py dispatch TASK-001 "Implement auth models" \
    --agent claude-code --type dev --json
python3 scripts/task_engine.py dispatch TASK-001 "Run integration tests" \
    --agent eva --type test --deps subtask_01,subtask_02

Dispatching the first subtask auto-transitions APPROVED -> IN_PROGRESS.

Update subtask progress

python3 scripts/task_engine.py subtask TASK-001 subtask_01 start --progress 30 --json
python3 scripts/task_engine.py subtask TASK-001 subtask_01 done --note "Models complete" --json
python3 scripts/task_engine.py subtask TASK-001 subtask_02 fail --note "Schema mismatch" --json

Check tasks (heartbeat integration)

python3 scripts/task_engine.py check              # Check all active tasks (verbose)
python3 scripts/task_engine.py check TASK-001      # Check one task
python3 scripts/task_engine.py check --quiet       # Minimal output for cron
python3 scripts/task_engine.py check --json        # Machine-readable JSON
python3 scripts/task_engine.py check --discord     # Discord-formatted digest

Archive completed task

python3 scripts/task_engine.py archive TASK-001 --json    # Only works on terminal tasks

Auto-dispatch

Auto-dispatch scans subtasks and dispatches ready ones to appropriate agents:

python3 scripts/task_engine.py auto-dispatch TASK-001             # Dispatch ready subtasks
python3 scripts/task_engine.py auto-dispatch TASK-001 --dry-run   # Preview without acting
python3 scripts/task_engine.py auto-dispatch --all                # All active tasks
python3 scripts/task_engine.py auto-dispatch TASK-001 --subtask subtask_02  # Specific subtask
python3 scripts/task_engine.py auto-dispatch TASK-001 --subtask subtask_01 --show-context  # View dispatch context

Output is always JSON with dispatches and skipped arrays.

Notify (Discord formatting)

Generate Discord-formatted notification messages:

python3 scripts/task_engine.py notify digest               # Full heartbeat digest
python3 scripts/task_engine.py notify TASK-001 created     # Task creation message
python3 scripts/task_engine.py notify TASK-001 status      # Status update with progress
python3 scripts/task_engine.py notify TASK-001 transition   # Last transition
python3 scripts/task_engine.py notify TASK-001 completed    # Completion summary
python3 scripts/task_engine.py notify TASK-001 alert --type stuck --subtask-id subtask_01

Rebuild index (recovery)

Reconstruct index.json from task directories if it gets corrupted:

python3 scripts/task_engine.py rebuild-index         # Scan and rebuild
python3 scripts/task_engine.py rebuild-index --json  # Machine-readable output

Heartbeat Integration

Add step 4.3 to the heartbeat's cmd_beat() function, after the ongoing.json check:

# 4.3 Task Engine check
logger.info("[4.3/8] Task Engine check")
try:
    import sys
    sys.path.insert(0, str(Path("/home/zeron/.openclaw/workspace/skills/task-engine/scripts")))
    from engine.checker import check_all_tasks
    te_result = check_all_tasks()
    if te_result.get("alerts"):
        alerts.extend(te_result["alerts"])
        all_ok = False
    if te_result.get("summary"):
        logger.info("  Tasks: %s", te_result["summary"])
except ImportError:
    logger.debug("  Task engine not installed, skipping")
except Exception as e:
    logger.warning("  Task engine check failed: %s", e)

The check is cheap (~300-500 tokens per heartbeat for 1-3 active tasks). It reads index.json first, then only loads task/subtask files for active tasks.

State Machine

PLANNING ──approve──> APPROVED ──start──> IN_PROGRESS ──test──> TESTING ──review──> REVIEW ──complete──> COMPLETED
    │                                         │  │                 │  │                │
    │reject                              block│  │fail        reopen│  │fail       reopen│ fail
    v                                         v  v                 v  v                v   v
 REJECTED                                BLOCKED FAILED      IN_PROGRESS FAILED   IN_PROGRESS FAILED
                                           │
                                      unblock│
                                           v
                                      IN_PROGRESS

Terminal states: COMPLETED, FAILED, REJECTED.

See references/state-transitions.md for the full transition table.

Subtask states

PENDING -> ASSIGNED -> IN_PROGRESS -> DONE
                │            │
                │block       │fail / block
                v            v
             BLOCKED      FAILED / BLOCKED

Auto-transitions (checked by heartbeat)

ConditionAction
All type: dev subtasks DONETask -> TESTING
All type: test subtasks DONETask -> REVIEW
First subtask dispatchedTask APPROVED -> IN_PROGRESS
Any subtask FAILEDAlert for human intervention
Subtask stuck 3+ heartbeatsAlert via Discord
Task past ETAAlert as overdue

Discord Formatting

The discord_formatter.py module generates formatted messages for Discord notifications. All formatting is pure string generation — no API calls.

Available formats:

  • Task created: New task announcement with priority and plan
  • Status update: Progress bars and subtask tree
  • Transition: State change with emoji indicators
  • Alert: Urgent stuck/overdue/failed alerts with human ping
  • Completion summary: Final report with subtask results
  • Heartbeat digest: Full summary of all active tasks

Progress bars render as: [████░░░░░░] 40%

Agent Capabilities

AgentKeyBest ForMax Parallel
Claude Codeclaude-codeDev, refactor, debug, docs3
EvaevaTest, validate, system-ops1

Agent selection priority:

  1. Preferred agent (if specified and capable)
  2. Match by preferred_types
  3. Match by broader capabilities
  4. Fallback to Eva

See references/agent-capabilities.md for full details.

Troubleshooting

Corrupted index.json

python3 scripts/task_engine.py rebuild-index --json

Scans all tasks/TASK-*/task.json files and reconstructs the index. Skips invalid/unreadable files.

Common errors

ErrorCauseFix
Invalid transition: X + 'event'Transition not allowed from current stateCheck references/state-transitions.md
Task TASK-XXX not foundTask doesn't exist or was archivedCheck tasks/ and tasks/archive/
Cannot archive: not terminalTask must be COMPLETED/FAILED/REJECTEDTransition to terminal state first
Agent at capacityMax parallel instances reachedWait for running subtasks to complete
Dependency not DONEBlocked by incomplete subtaskComplete blocking subtask first

JSON parse errors

The engine handles corrupt JSON files gracefully:

  • During check: skips bad tasks, logs warning, continues
  • During rebuild-index: skips unreadable files, reports in output
  • All CLI commands catch exceptions and return clean error messages (not tracebacks)

Data Location

  • Task files: /home/zeron/.openclaw/workspace/tasks/TASK-NNN/
  • Index: /home/zeron/.openclaw/workspace/tasks/index.json
  • Archive: /home/zeron/.openclaw/workspace/tasks/archive/
  • Config: /home/zeron/.openclaw/workspace/skills/task-engine/config/settings.yaml
  • Agent reference: /home/zeron/.openclaw/workspace/skills/task-engine/references/agent-capabilities.md
  • State transitions: /home/zeron/.openclaw/workspace/skills/task-engine/references/state-transitions.md

平台分布

OpenClaw

93.4%
按下载量换算3,750

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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