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Loop

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QwenLM
loop

Create a loop that runs a prompt now and follows up either on a fixed schedule or through self-paced wakeups. Usage - /loop check the build, /loop 5m check the build, /loop check the PR every 30m. /loop list to show jobs, /loop clear to cancel all.

Overview

PublisherQwenLM
Repositoryqwen-code
Skill nameloop
Stars
27.9K
Forks
3.1K
Bundled files
7
LicenseApache-2.0
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.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Loop 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/QwenLM/qwen-code.git /tmp/qwen-code
mkdir -p .claude/skills
cp -r /tmp/qwen-code/packages/core/src/skills/bundled/loop .claude/skills/loop
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Loop 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 Loop 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 Loop 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.

/loop — run a prompt repeatedly

Subcommands

If the input (after stripping the /loop prefix) is exactly one of these keywords, run the subcommand instead of scheduling:

  • list — call CronList and display the results. Done.
  • clear — call CronList, then call CronDelete for every job returned. Confirm how many were cancelled. Done.

Parsing

Parse the input after removing the /loop prefix:

  1. Empty input (no prompt, no interval): the autonomous path — run a self-paced autonomous loop. See the Autonomous mode section.
  2. Leading interval token: if the first whitespace-delimited token matches ^\d+[smhd]$ (e.g. 5m, 2h), this is the fixed-interval recurring path. The rest is the prompt.
  3. Trailing "every" clause: otherwise, if the input ends with every <N><unit> or every <N> <unit-word> (e.g. every 20m, every 5 minutes, every 2 hours), this is the fixed-interval recurring path. Extract that interval and strip it from the prompt. Only match when what follows "every" is a time expression — check every PR has no interval.
  4. Prompt-only input: otherwise, the entire input is the prompt and this is the prompt-only self-paced path.

If an interval was given but the prompt is empty (e.g. /loop 5m), this is a fixed-interval autonomous loop — see the Autonomous mode section.

Examples:

  • 5m /babysit-prs → fixed interval 5m, prompt /babysit-prs (leading interval token)
  • check the deploy every 20m → fixed interval 20m, prompt check the deploy (trailing "every" clause)
  • run tests every 5 minutes → fixed interval 5m, prompt run tests (trailing "every" clause)
  • check every PR → prompt-only self-paced path, prompt check every PR ("every" is not followed by a time expression)
  • check the deploy → prompt-only self-paced path, prompt check the deploy
  • (empty) → self-paced autonomous loop (sentinel <<autonomous-loop-dynamic>>)
  • 5m → fixed-interval autonomous loop (interval 5m, sentinel <<autonomous-loop>>)

Prompt-only self-paced path

Use this path only when the user supplied a prompt and no interval.

  1. Do not call CronCreate for this path.
  2. If this tick opens with a <task-notification> block (a monitor or background event re-invoked you, not a bare /loop wakeup prompt), handle that event before re-running the prompt.
    • If the notification says the watched condition was met, cancel any pending fallback LoopWakeup with CronDelete if you still have its ID, then finish the loop.
    • If a monitor auto-stopped on idle or max-events, restart it once if the watch is still useful, re-arm the fallback, report the restart count to the user, and include that count in the LoopWakeup prompt or reason (for example, monitor restarted 1/1 time) so it survives context compaction. If it auto-stops again on the next tick, end the loop and report the repeated auto-stop to the user.
    • If the signal is ambiguous, re-arm a shorter follow-up and investigate on the next tick. If the signal remains ambiguous for three consecutive ticks, end the loop and report that the watch could not reach a clear conclusion.
  3. Run the parsed prompt immediately now.
    • If it is a slash command, invoke it via the Skill tool.
    • Otherwise, act on it directly.
  4. Before ending the turn, decide whether another check is useful.
    • Call LoopWakeup only if continued follow-up is useful.
    • Do not call LoopWakeup if the task is complete.
    • Do not call LoopWakeup if the task is blocked on user input or external state that cannot be checked later.
    • Do not call LoopWakeup just to keep polling when no useful next check exists.
    • If you started a background agent or a Monitor, it wakes you via a terminal <task-notification> on exit, failure, cancellation, or monitor auto-stop — so set LoopWakeup as a long fallback rather than a short poll. Do not omit it just because something is watching: the work may hang, or a Monitor may auto-stop on idle or max-events (and one owned by another agent routes its notification only to that agent). Omit LoopWakeup only on the terminal conditions above (complete, blocked, or repeated monitor auto-stop).
  5. When scheduling a continuation, call LoopWakeup with:
    • delaySeconds: the next useful delay in seconds. The runtime clamps to 60–3600 (1–60 min); follow the tool's own guidance on picking a value — it accounts for the prompt-cache window and for the fallback-heartbeat case when a background task will wake you.
    • prompt: /loop ${original prompt} plus any state the next tick must preserve, such as monitor restarted 1/1 time.
    • reason: a short reason for the chosen delay. Include the monitor restart count here when re-arming after an auto-stop.
  6. Briefly tell the user what was done now. If a wakeup was scheduled, include when the next check is expected. If no wakeup was scheduled because a notification ended the loop, mention whether the stale fallback was cancelled; if the wakeup ID was lost, ignore or answer the stale wakeup briefly when it fires.

Fixed-interval recurring path

Use this path only for inputs with a leading interval token or a trailing "every" clause.

Interval to cron

Supported suffixes: s (seconds, rounded up to nearest minute, min 1), m (minutes), h (hours), d (days). Convert:

Interval patternCron expressionNotes
Nm where N <= 59*/N * * * *every N minutes
Nm where N >= 600 */H * * *round to hours (H = N/60, must divide 24)
Nh where N <= 230 */N * * *every N hours
Nd0 0 */N * *every N days at midnight local
Nstreat as ceil(N/60)mcron minimum granularity is 1 minute

If the interval does not cleanly divide its unit (for example 7m gives uneven gaps at :56 to :00, or 90m is 1.5 hours which cron cannot express), pick the nearest clean interval and tell the user what you rounded to before scheduling.

Action

  1. Call CronCreate with:
    • cron: the expression from the table above
    • prompt: the parsed prompt from above, verbatim (slash commands are passed through unchanged)
    • recurring: true
    • durable: true if the user's language implies persistence ("keep doing this", "set this up permanently", "every day even after restart"). Otherwise omit (defaults to session-only).
  2. Briefly confirm: what is scheduled, the cron expression, the human-readable cadence, the auto-expiry (7 days after creation by default — the CronCreate tool description states the configured limit, which may differ or be disabled), and that they can cancel sooner with CronDelete (include the job ID).
  3. Then immediately execute the parsed prompt now. Do not wait for the first cron fire.
    • If it is a slash command, invoke it via the Skill tool.
    • Otherwise, act on it directly.

loop.md task-file mode

Use this when the user wants the loop to work a task list kept in a file (they say "work through my loop.md", "loop over the tasks in .qwen/loop.md", or point at such a file). Tasks live in .qwen/loop.md (project) or ~/.qwen/loop.md (home; project wins). Instead of a natural-language prompt, set the loop's prompt to a sentinel so each fire re-reads the file:

  • Self-paced (no interval) → LoopWakeup prompt: <<loop.md-dynamic>>
  • Fixed interval → CronCreate prompt: <<loop.md>> (with recurring: true, and durable: true if persistence is implied)

At each fire you receive either the full task list (first delivery, after the file changes, or after a compaction) or a short reminder to keep working the list established earlier. Work the tasks; in self-paced mode re-arm LoopWakeup with <<loop.md-dynamic>> only when continued follow-up is useful (same "don't re-arm if complete/blocked" rules as the prompt-only path). If .qwen/loop.md is absent at fire time, the loop falls back to autonomous mode (it keeps working autonomously instead of no-op'ing); a recreated file is picked up on the next fire. Confirm to the user in plain language ("looping over your .qwen/loop.md task list…"), not the raw sentinel.

Autonomous mode

Use this for a bare /loop (no prompt, no file) — the user wants you to keep their work moving while they're away. Arm the loop with an autonomous sentinel and run the first check now:

  • Self-paced (empty input) → LoopWakeup prompt: <<autonomous-loop-dynamic>>
  • Fixed interval (/loop <interval>, no prompt) → CronCreate prompt: <<autonomous-loop>> (with recurring: true, and durable: true if persistence is implied)

The first immediate check, and each scheduled fire, advance work the conversation already established — finish things the user started, maintain an in-progress PR (address review threads, fix failing CI, resolve conflicts), honor "I'll also…" commitments. You are a steward, not an initiator: act on what the transcript already established; never invent new work or make irreversible changes (push, delete, send) without clear authorization. If everything is genuinely quiet, say so in one sentence and stop. The first fire (and the first after a compaction) delivers fuller guidance; later fires send a short reminder pointing back to it. In self-paced mode re-arm LoopWakeup with <<autonomous-loop-dynamic>> (same "don't re-arm if complete/blocked" rules). Confirm to the user in plain language ("running an autonomous loop on your work…"), not the raw sentinel.

Input

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Loop AI skill do?

Create a loop that runs a prompt now and follows up either on a fixed schedule or through self-paced wakeups. Usage - /loop check the build, /loop 5m check the build, /loop check the PR every 30m. /loop list to show jobs, /loop clear to cancel all.

Why use Loop on TypingMind?

Because you install it once and use it with any model. Loop 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 Loop in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/QwenLM/qwen-code/tree/main/packages/core/src/skills/bundled/loop. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Loop?

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 Loop?

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

Is the Loop AI skill free?

Yes. It is published on GitHub by QwenLM under the Apache-2.0 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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