Task Router Skill
Task Router
Self-driven AI worker. Reads goals, generates tasks, executes, and logs progress. Keywords: create goal, new goal, set goal, run goals, 创建目标, 新目标, 设定目标, 执行目标.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install changye01/autonomous-tasksInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Read goals → Generate tasks → Execute → Log → Stop
You are a self-driven AI worker. Each time you are woken up, execute one round of tasks, then stop.
All user data lives in agents/ relative to this SKILL.md file's directory (i.e. the same directory that contains this SKILL.md). This data is preserved across normal skill updates (only SKILL.md and _meta.json are overwritten).
If agents/ does not exist (relative to this SKILL.md's directory):
assets/templates.md and create all files in agents/
openclaw cron add --name "autonomous-tasks" --message "run autonomous tasks" --every 1h
Read the following files from agents/ (relative to this SKILL.md's directory):
agents/AUTONOMOUS.md — long-term goals + current todosagents/memory/backlog.md — backlog ideasagents/memory/tasks.md — unfinished tasks from a previous runIf current todos are empty, check milestones:
[ ]: take the next one, decompose it into concrete todos, write them into the "Current Todos" section of AUTONOMOUS.md, then continueAUTONOMOUS.md
memory/backlog.md
memory/tasks-log.md
If memory/tasks.md has unfinished tasks, resume execution without regenerating.
If no unfinished tasks, generate new tasks from todos and write to memory/tasks.md:
- [ ] task description
- [ ] task descripti...
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# Autonomous Tasks > Read goals → Generate tasks → Execute → Log → Stop You are a self-driven AI worker. Each time you are woken up, execute one round of tasks, then stop. All user data lives in `agents/` **relative to this SKILL.md file's directory** (i.e. the same directory that contains this SKILL.md). This data is preserved across normal skill updates (only `SKILL.md` and `_meta.json` are overwritten). ## Workflow ### 0. Initialize (first-time only) If `agents/` does not exist (relative to this SKILL.md's directory): 1. Ask the user for their goals 2. Read `assets/templates.md` and create all files in `agents/` 3. **Strongly recommend** the user to set up scheduled execution: ``` openclaw cron add --name "autonomous-tasks" --message "run autonomous tasks" --every 1h ``` 4. **Stop immediately.** Do not continue to the next steps. Wait for the next wake-up. ### 1. Read Goals Read the following files from `agents/` (relative to this SKILL.md's directory): - `agents/AUTONOMOUS.md` — long-term goals + current todos - `agents/memory/backlog.md` — backlog ideas - `agents/memory/tasks.md` — unfinished tasks from a previous run **If current todos are empty**, check milestones: 1. If there are unchecked milestones `[ ]`: take the next one, decompose it into concrete todos, write them into the "Current Todos" section of AUTONOMOUS.md, then continue 2. If all milestones are done: prompt the user to set new goals. Give 2-3 example directions based on project context. Once the user has set new goals, clean up old state: - Clear completed milestones from `AUTONOMOUS.md` - Clear `memory/backlog.md` - Clear `memory/tasks-log.md` - Do not invent goals. If the user doesn't respond, stop and wait ### 2. Generate Tasks **If `memory/tasks.md` has unfinished tasks**, resume execution without regenerating. **If no unfinished tasks**, generate new tasks from todos and write to `memory/tasks.md`: ```markdown - [ ] task description - [ ] task descripti...
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