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Task Planner Skill

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uluckyXH
task-planner-skill

任务规划师 Skill — 通过 CLI 工具创建任务、拆分模块、分配子任务

Overview

PublisheruluckyXH
RepositoryOpenMOSS
Skill nametask-planner-skill
Stars
1.3K
Forks
146
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by uluckyXH on GitHub. Read the source before you install it.

Installation

Install the Task Planner Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/uluckyXH/OpenMOSS.git /tmp/OpenMOSS
mkdir -p .claude/skills
cp -r /tmp/OpenMOSS/skills/task-planner-skill .claude/skills/task-planner-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Task Planner Skill in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Task Planner Skill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Task Planner Skill is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Task Planner Skill

你可以使用 task-cli.py 工具来管理任务系统。该工具位于本 Skill 目录下。

认证信息

  • API_KEY: <注册后填入>

工作流程

  1. 获取规则 → 2. 检查积分 → 3. 查看/创建任务 → 4. 创建模块 → 5. 创建子任务并分配 → 6. 收尾交付 → 7. 记录日志

可用命令

所有命令前缀:python task-cli.py --key <API_KEY>

规则

bash
rules                                     # 获取合并后的规则提示词(执行前必须调用)

任务管理

bash
task list                                 # 查看所有任务
task list --status active                 # 按状态过滤
task create "任务名" --desc "描述" --type once  # 创建任务
task get <task_id>                        # 查看任务详情
task edit <task_id> --name "新名" --desc "新描述"  # 编辑任务(仅 planning/active)
task status <task_id> active              # 更新任务状态
task cancel <task_id>                     # 取消任务

模块管理

bash
module list <task_id>                     # 查看任务下的模块
module create <task_id> "模块名" --desc "描述"  # 创建模块

子任务管理

bash
st list --task-id <task_id>               # 查看某任务下的子任务
st list --status blocked                  # 查看被标记 blocked 的子任务
st create <task_id> "子任务名" --deliverable "交付物" --acceptance "验收标准" --assign <agent_id>
st get <sub_task_id>                      # 查看子任务详情
st edit <sub_task_id> --name "新名" --acceptance "新标准"  # 编辑子任务(仅 pending/assigned)
st cancel <sub_task_id>                   # 取消子任务
st reassign <sub_task_id> <agent_id>      # 重新分配(blocked → assigned)

📄 列表命令默认返回全部数据。如数据较多,可加 --page N --page-size M 分页查看。返回结果包含 total(总数)和 has_more(是否还有更多)。

Agent 查看

bash
agents                                    # 查看已注册 Agent(ID、角色、状态、积分)
agents --role executor                    # 按角色过滤

积分

bash
score me                                  # 查看自己的积分
score logs --page 1 --page-size 10        # 查看积分明细(建议分页,避免数据过多)
score agent-logs <agent_id> --page 1 --page-size 10  # 查看指定 Agent 的积分明细
score leaderboard                         # 积分排行榜,分配时参考

📄 score logs 默认返回全部明细。如数据较多,可加 --page N --page-size M 分页查看。

通知

bash
notification                              # 查看通知渠道配置

日志

bash
log create "plan" "规划了xxx任务,分配给了xxx"
log mine                                  # 回顾工作记录(默认最近7天,最多20条)
log mine --action reflection              # 只看自省笔记
log list --sub-task-id <id>               # 查看某子任务的所有日志
log list --action blocked --days 3        # 扫描执行者求助日志
log list --days 30 --limit 50             # 最近30天,最多50条

注意事项

  • 每次执行前先运行 rules 获取最新规则
  • 每次唤醒时检查 score logs,有扣分则分析原因改进
  • 创建任务后状态默认为 planning,拆分完成后用 task status 改为 active
  • 分配子任务时参考 score leaderboard,优先选择高分 Agent
  • 留意 st list --status blocked,及时重新分配
  • type=recurringstatus=done 的子任务 → 创建同名新子任务开启下一轮
  • 所有子任务 done → 执行收尾交付(汇总交付物 → 任务状态改 completed → 发通知)

Frequently asked questions

What does the Task Planner Skill AI skill do?

任务规划师 Skill — 通过 CLI 工具创建任务、拆分模块、分配子任务

Why use Task Planner Skill on TypingMind?

Because you install it once and use it with any model. Task Planner Skill is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Task Planner Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/uluckyXH/OpenMOSS/tree/main/skills/task-planner-skill. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Task Planner Skill?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Task Planner Skill?

As many as you like. As long as a model supports skills, you can use Task Planner Skill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Task Planner Skill AI skill free?

Yes. It is published on GitHub by uluckyXH under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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