Agent skill

Task Runner

by LeoYeAI in LeoYeAI/openclaw-master-skills

Persistent task queue system. An agent skill from LeoYeAI/openclaw-master-skills.

MITAuto-check passedProductivity & Automation

Install Task Runner

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill task-runner -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills task-runner --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/autonomous-task-runner .claude/skills/task-runner && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
task-runner
GitHub stars
2.2k
Token cost
~4.1k tokens
SKILL.md length
1,295 words
Files
10 (incl. references)
Skills in repo
1,215
Repo updated
First seen
Licence
MIT

At a glance

Persistent task queue system. An agent skill from LeoYeAI/openclaw-master-skills.

  • Works in 12 steps: First Run Setup (auto-configure on first… → Load queue → Parse tasks from message → …
  • Tasks that involve Scheduled and recurring tasks
  • SKILL.md covers Two Operating Modes, A1 — Triggers, Configuration and A3 — Outputs, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Task Runner is an agent skill from LeoYeAI/openclaw-master-skills. Persistent task queue system. Users add tasks at any time via natural language; tasks are stored in a single persistent queue file and executed asynchronously via subagents. A heartbeat/cron dispatcher wakes periodically to check pending tasks, spawn workers, and report completions. The system never "finishes" — it always remains ready for the next task.

Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files (for example `CHANGELOG.md`, `README.md` and `STATUS.json`).

It sits in Productivity & Automation, covering Scheduled and recurring tasks, Background jobs and Subagents. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Tasks that involve Scheduled and recurring tasks
  • Tasks that involve Background jobs
  • Tasks that involve Subagents

Example prompts

  • “finishes”
  • “/task-runner”

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. First Run Setup (auto-configure on first use)
  2. Load queue
  3. Parse tasks from message
  4. Assign IDs
  5. Build task objects
  6. Append to queue and save
  7. Confirm to user
  8. Handle control commands
  9. Load queue
  10. Check for work
  11. Check running tasks for completion
  12. Dispatch pending tasks

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Task Runner loads about 4.1k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 1,295 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~92
When it runs · the whole SKILL.md, loaded when a task matches
~4.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,295 words, ~4,072 tokens.

Download SKILL.mdSave it as .claude/skills/task-runner/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
task-runner
description
Persistent task queue system. Users add tasks at any time via natural language; tasks are stored in a single persistent queue file and executed asynchronously via subagents. A heartbeat/cron dispatcher wakes periodically to check pending tasks, spawn workers, and report completions. The system never "finishes" — it always remains ready for the next task.
metadata.author
skill-engineer
metadata.version
2.1.0
metadata.owner
main agent (any agent with access to the full tool suite)
metadata.tier
general

Task Runner Skill

A persistent, daemon-style task queue. Users add tasks at any time. A dispatcher runs on every heartbeat to check the queue and execute pending work via subagents. Tasks accumulate, complete, and are archived — the queue itself never closes.


Two Operating Modes

This skill has two distinct modes with different triggers and behaviors:

ModeTriggerPurpose
INTAKEUser message containing task intentParse message → add tasks to queue → confirm → immediately run DISPATCHER
DISPATCHERAfter INTAKE (primary) · Heartbeat/cron (backup)Read queue → dispatch pending tasks → report completions

Both modes read and write the same persistent queue file.


A1 — Triggers

Mode 1: INTAKE (user message)

Activate INTAKE mode when the user's message matches any of the following patterns:

PatternExamples
Explicit task add"add task", "add these tasks", "task:", "new task"
Delegation"do this for me", "do these for me", "handle these", "can you do X"
Framing"I need you to", "help me with", "I need", "I want you to"
List framing"task list", "my tasks", "queue these", "work on these"
Control commands"skip T-03", "retry T-02", "mark T-01 done", "cancel T-04"
Status check"show tasks", "task status", "what's in the queue", "what are my pending tasks"
Compound askAny message with 2+ distinct action items (bullets, numbers, "and also", "then")

Do NOT activate INTAKE for:

  • Pure single-question lookups answered in one sentence ("what time is it?")
  • Scheduling-only requests with no actual task ("remind me in 20 min")
  • Single web search requests ("google X")
  • The heartbeat systemEvent (that's DISPATCHER mode)
Mode 2: DISPATCHER (inline after INTAKE, heartbeat, or cron)

Activate DISPATCHER mode when triggered by:

  • Immediately after INTAKE — runs in the same turn, right after tasks are queued (primary path)
  • HEARTBEAT.md check during a heartbeat poll (backup: catches retries and completions)
  • systemEvent: "TASK_RUNNER_DISPATCH: check queue and run pending tasks" (backup)
  • Any scheduled/cron trigger registered for task-runner (backup)

Configuration

VariableLocationDefaultDescription
TASK_RUNNER_DIRTOOLS.md~/.openclaw/tasks/Directory for queue file and deliverables
TASK_RUNNER_MAX_CONCURRENTTOOLS.md2Max tasks running simultaneously
TASK_RUNNER_MAX_RETRIESTOOLS.md or env3Max retry attempts before marking blocked
TASK_RUNNER_ARCHIVE_DAYSTOOLS.md7Days after which done/blocked tasks are archived

How to configure — add to TOOLS.md:

## Task Runner
TASK_RUNNER_DIR=~/.openclaw/tasks/
TASK_RUNNER_MAX_CONCURRENT=2
TASK_RUNNER_MAX_RETRIES=3
TASK_RUNNER_ARCHIVE_DAYS=7

Queue file path: ${TASK_RUNNER_DIR}/task-queue.json (single persistent file, NOT dated — accumulates all tasks over time)


A3 — Outputs

OutputPath / ChannelDescription
Queue file${TASK_RUNNER_DIR}/task-queue.jsonSingle persistent queue; all tasks
Per-task completion messageChat notificationSent immediately when a task finishes (done or blocked)
Deliverable filesTask-specific pathsFiles produced by tasks (when applicable)
INTAKE confirmationChatSent after adding tasks to queue

Mode 1: INTAKE — Step-by-Step

Goal: Convert user message into structured task objects, append to queue, confirm.

Step 0 — First Run Setup (auto-configure on first use)

Run this check before anything else, every INTAKE invocation:

CHECK whether ${TASK_RUNNER_DIR}/task-queue.json exists
IF file does NOT exist:
  → This is the first run. Auto-configure everything silently before proceeding.

  [1] Create directory:
      exec: mkdir -p ${TASK_RUNNER_DIR}

  [2] Initialize queue file:
      WRITE ${TASK_RUNNER_DIR}/task-queue.json with default structure:
      { "lastId": null, "tasks": [], "archivedCount": 0 }

  [3] Register heartbeat entry:
      READ HEARTBEAT.md (create it if missing)
      IF "Task Runner Dispatcher" is NOT already in the file:
        APPEND the following block (with a blank line before it):

        ## Task Runner Dispatcher
        Every heartbeat: check ${TASK_RUNNER_DIR}/task-queue.json
        - If pending or running tasks exist → run DISPATCHER mode (task-runner skill)
        - If nothing pending → HEARTBEAT_OK (skip)

      WRITE the updated HEARTBEAT.md

  [4] Register backup cron job:
      CALL cron tool with:
        action: "add"
        job:
          name: "Task Runner Dispatcher"
          schedule: { kind: "every", everyMs: 900000 }
          payload: { kind: "systemEvent", text: "TASK_RUNNER_DISPATCH: check queue and run pending tasks" }
          sessionTarget: "main"
          enabled: true

  [5] Notify user:
      "⚙️ Task Runner initialized.
       Heartbeat dispatcher registered in HEARTBEAT.md.
       Backup cron job registered (runs every 15 minutes).
       Your tasks will execute automatically."

  → THEN continue with normal INTAKE steps below.

IF file already exists:
  → Skip Step 0 entirely. Proceed directly to Step 1.

Idempotency rule: Step 0 only fires on true first run (queue file absent). It will never double-register the heartbeat entry or create duplicate cron jobs.


Step 1 — Load queue
READ ${TASK_RUNNER_DIR}/task-queue.json
IF file does not exist:
  Initialize with default structure (see references/queue-schema.md)
  Set lastId = null
Step 2 — Parse tasks from message

Split user message into individual tasks using these cues:

  • Numbered lists (1., 2., 3.)
  • Bulleted lists (-, *, •)
  • Explicit separators ("first", "also", "and then", "next")
  • Compound sentences with multiple imperatives
  • Single task: entire message is one task
Step 3 — Assign IDs

Continue from lastId in the queue file:

  • If lastId = "T-05", next task is T-06
  • If lastId = null, start at T-01
  • Format: T-NN (zero-padded, minimum 2 digits; expand to 3 when N > 99)
Step 4 — Build task objects

For each parsed task, create a JSON object (schema in references/queue-schema.md):

  • Set id, description, goal, status = "pending", added_at
  • Set retries = 0, maxRetries from config
  • Leave execution fields null
Step 5 — Append to queue and save
APPEND new task objects to queue.tasks[]
UPDATE queue.lastId to the last assigned ID
WRITE updated queue file to disk
Step 6 — Confirm to user
Added T-06: [description]. Starting now...

For multiple tasks:

📋 Added 3 tasks to queue:
• T-06: [description]
• T-07: [description]
• T-08: [description]
Starting dispatcher now...

Then immediately run DISPATCHER mode (Steps 1–5 below) in the same turn. Do not exit and wait for the next heartbeat. Tasks must start executing immediately. The heartbeat/cron dispatcher is a backup for retries and completion checks — not the primary execution path.

Step 7 — Handle control commands
CommandAction
skip T-NNSet status = "skipped"; save; confirm
retry T-NNReset status = "pending", retries = 0; save; confirm
cancel T-NNSet status = "skipped", blocked_reason = "cancelled by user"; save; confirm
mark T-NN doneSet status = "done", completed_at = now; save; confirm
show tasks / task statusRead queue; render status table (see A5 templates)

Mode 2: DISPATCHER — Step-by-Step

Goal: Check queue, dispatch pending tasks, track running tasks, report completions.

Step 1 — Load queue
READ ${TASK_RUNNER_DIR}/task-queue.json
IF file does not exist OR tasks array is empty:
  → HEARTBEAT_OK (silent, nothing to do)
  → EXIT
Step 2 — Check for work
pending_tasks = tasks where status = "pending"
running_tasks = tasks where status = "running"

IF pending_tasks is empty AND running_tasks is empty:
  → HEARTBEAT_OK (silent)
  → EXIT
Step 3 — Check running tasks for completion

For each task with status = "running":

IF subagent_session is set:
  CHECK subagent session status

  IF session is DONE:
    READ deliverable from session output
    RUN verification (see references/verification-guide.md)
    IF verification passes:
      SET status = "done"
      SET deliverable, deliverable_path, completed_at
      NOTIFY user: ✅ T-NN done — [summary]
    ELSE (verification failed):
      TREAT as failure (see retry logic below)

  IF session is FAILED or ERROR:
    IF retries < maxRetries:
      INCREMENT retries
      ADD to strategies_tried
      SET status = "pending"  ← will be re-dispatched this cycle
    ELSE:
      SET status = "blocked"
      SET blocked_reason, user_action_required, completed_at
      NOTIFY user: 🚫 T-NN blocked — [reason + unblock steps]

  IF session is STILL RUNNING:
    Leave as-is (will check again next heartbeat)
Step 4 — Dispatch pending tasks
currently_running = count of tasks with status = "running"
slots_available = maxConcurrent - currently_running

FOR EACH pending task (in order of added_at), up to slots_available:
  PICK execution strategy (see references/task-types.md)
  SPAWN subagent with task description and strategy
  SET status = "running"
  SET subagent_session = spawned session ID
  SET started_at = now

Subagent instructions template:

You are executing task [T-NN] for the task-runner skill.

Task: [description]
Goal: [goal]
Type: [task_type]
Strategy: [selected strategy from task-types.md]

Execute the task. When complete:
1. Report the result clearly
2. Note any deliverable file path if a file was created
3. If blocked, explain exactly why and what the user needs to do

Do not start any other tasks. Focus only on this one.
Step 5 — Save and exit
WRITE updated queue file (status changes, subagent_session IDs)

If any notifications were sent (done/blocked), this is an active heartbeat response. If only silent dispatching occurred, this is still a heartbeat response (not HEARTBEAT_OK). Only return HEARTBEAT_OK when there was truly nothing to do (no pending, no running tasks).


Show full SKILL.md (504 more words)Show less

A5 — Output Format Templates

INTAKE confirmation (single task)
Added T-06: [description]. Queue now has N pending tasks.
INTAKE confirmation (multiple tasks)
📋 Added N tasks to queue:
• T-06: [description]
• T-07: [description]

Starting now...
Task status table (on demand)
📋 Task Queue — [N total, N pending, N running, N done, N blocked]

ID    Status      Description
T-01  ✅ done      [description] → [deliverable summary]
T-02  🔄 running   [description] (started [time ago])
T-03  ⏳ pending   [description]
T-04  🚫 blocked   [description] — [blocked_reason short]
T-05  ⏭️ skipped   [description]
Task done notification
✅ T-NN done — [one-sentence summary of what was accomplished]
[deliverable: link or file path, if applicable]
Task blocked notification
🚫 T-NN blocked after [N] attempts

What was tried:
- [Strategy 1]: [result]
- [Strategy 2]: [result]

Why it's blocked:
[Clear plain-English explanation]

To unblock:
1. [Concrete step #1]
2. [Concrete step #2 if needed]

Reply "retry T-NN" once ready.
Task skipped
⏭️ T-NN skipped — as requested.

A6 — Heartbeat Integration

Heartbeat and cron setup is automatic. Step 0 of INTAKE mode handles this on first use — no manual configuration required.

Role of heartbeat/cron (backup only)

Tasks are dispatched immediately after INTAKE — heartbeat and cron are backups only.

The backup dispatcher handles:

  • Retry dispatch: tasks that failed and were reset to pending
  • Completion checks: polling running subagent sessions for done/blocked status
  • Recovery: tasks that were pending when no user message triggered INTAKE

Users should never need to wait for a heartbeat for a freshly added task.

What gets configured automatically

HEARTBEAT.md entry (injected on first INTAKE):

markdown
## Task Runner Dispatcher
Every heartbeat: check ${TASK_RUNNER_DIR}/task-queue.json
- If pending or running tasks exist → run DISPATCHER mode (task-runner skill)
- If nothing pending → HEARTBEAT_OK (skip)

Backup cron job (registered on first INTAKE):

every 15 min → systemEvent: "TASK_RUNNER_DISPATCH: check queue and run pending tasks"
sessionTarget: main
Manual setup (if needed)

If for any reason auto-setup did not run (e.g., queue file was pre-created externally), delete ${TASK_RUNNER_DIR}/task-queue.json and send any task — Step 0 will fire.


A7 — Success Criteria

INTAKE mode succeeds when:
  1. All tasks from user message parsed and assigned IDs
  2. Tasks appended to queue file (file saved to disk)
  3. Confirmation sent to user with task IDs and count
  4. DISPATCHER mode triggered immediately in the same turn
  5. Subagents spawned for pending tasks before INTAKE turn ends
DISPATCHER mode succeeds when:
  1. Queue file read without error
  2. All running tasks checked for completion (done/blocked notifications sent as needed)
  3. Pending tasks dispatched up to maxConcurrent slots
  4. Queue file saved with updated states
  5. User notified for every task that reached a terminal state this cycle
Ongoing system health:
  • Queue file is never corrupted (always valid JSON)
  • Tasks older than archiveDays days with terminal status are archived/removed
  • lastId always increments (no ID reuse)
  • maxRetries respected before any task is marked blocked

Edge Cases

SituationBehavior
Queue file missing (first run)Run Step 0 auto-setup: create dir, init queue, register heartbeat + cron; notify user
Queue file missing (manually deleted)Step 0 re-fires: re-initializes queue; does NOT re-register heartbeat/cron (idempotent check)
Queue file corrupt/invalid JSONLog error, notify user, do not overwrite; ask user to inspect
Task description is ambiguousAssign unknown type; dispatcher will attempt classification + fallback
maxConcurrent already reachedDispatcher skips dispatching; checks again next heartbeat
User adds task while dispatcher is runningRace-safe: dispatcher reads, processes, writes atomically per cycle
Task depends on another task's outputSet blocked_reason = "depends on T-NN-1 which is pending/blocked"
User says "retry T-NN"Reset to pending, retries = 0, strategies_tried = []
All tasks blockedNotify user: "All tasks are blocked. Review unblock instructions above."
20+ tasks added at onceDispatcher dispatches in batches of maxConcurrent; all tasks eventually run
Subagent session ID lostMark task as pending again; will re-dispatch next cycle
Archive: done tasks > archiveDays oldMove to ${TASK_RUNNER_DIR}/archive/YYYY-MM.json; remove from main queue

A8 — File Organization

${TASK_RUNNER_DIR}/
  task-queue.json          ← single persistent queue (all active tasks)
  archive/
    2026-01.json           ← archived tasks (done/blocked, older than archiveDays)
    2026-02.json

Queue file schema is documented in references/queue-schema.md.


References

  • references/queue-schema.md — Queue JSON format (complete field reference)
  • references/task-types.md — Task type catalog and strategy selection
  • references/verification-guide.md — Verification logic per task type
  • tests/test-triggers.json — Trigger test cases (positive and negative)

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (references) in skills/autonomous-task-runner of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • CHANGELOG.md
  • README.md
  • STATUS.json
  • _meta.json
  • references/queue-schema.md
  • references/task-types.md
  • references/verification-guide.md
  • skill.yml
  • tests/test-triggers.json

Open the folder on GitHubat commit e5199b5

Compare with similar skills

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Questions about Task Runner

What does Task Runner do?

Persistent task queue system. An agent skill from LeoYeAI/openclaw-master-skills. Task Runner is an agent skill from LeoYeAI/openclaw-master-skills. Persistent task queue system.

When should I use Task Runner?

Task Runner fits situations like: tasks that involve Scheduled and recurring tasks; tasks that involve Background jobs; tasks that involve Subagents.

How do I install Task Runner in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill task-runner -a claude-code`. Or copy the skill folder (skills/autonomous-task-runner in LeoYeAI/openclaw-master-skills) into .claude/skills/task-runner in your project. Claude Code loads it when a task matches its description.

How do I install Task Runner in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill task-runner -a codex`. Or copy the skill folder (skills/autonomous-task-runner in LeoYeAI/openclaw-master-skills) into .agents/skills/task-runner in your project. Codex loads it when a task matches its description.

Can I use Task Runner in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill task-runner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/task-runner, .gemini/skills/task-runner, .github/skills/task-runner and .opencode/skills/task-runner in your project.

What does Task Runner need to run?

SKILL.md names no scripts, command-line tools or credentials: Task Runner is instructions for the agent only.

Does Task Runner access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Task Runner safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Task Runner use?

Task Runner is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Task Runner use?

About 4.1k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.7k tokens, read only when the agent opens those files.

What are the alternatives to Task Runner?

Skills that share tags, products or a category with Task Runner: Cron (shibing624/agentica, 352 stars), Worker Development (ChatbotXIO/ChatbotX, 878 stars), Convex Crons (openclaw/clawhub, 9.5k stars) and Frappe Impl Scheduler (Impertio-Studio/Frappe_Claude_Skill_Package, 187 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Task Runner?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,158 GitHub stars. The repository holds 1,215 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.