Prp Loop

CommunityPopular

Wirasm

prp-loop

Runs the detached, resumable PRP pipeline in fresh headless CLI sessions, cycling plan, implementation, PR, review, and corrections with persisted state and safety bounds. Use only when the user explicitly asks to "run the full PRP loop", "run this detached", "continue across context windows", use headless autonomous execution, resume a saved loop, or invokes /prp-loop. Use prp-issue for ordinary end-to-end delivery.

Overview

Publisher	Wirasm
Repository	`prp`
Skill name	`prp-loop`
Stars	2.2K
Forks	607
Bundled files	1
License	MIT
Links	Skill source Repository

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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Wirasm on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/Wirasm/prp.git /tmp/prp
mkdir -p .claude/skills
cp -r /tmp/prp/plugins/prp-core/skills/prp-loop .claude/skills/prp-loop

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prp 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 Prp 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 Prp 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.

PRP Loop — autonomous cyclic pipeline

Launch the orchestrator that drives plan → implement (commit + PR) → review and loops review → fix until the PR review is clean (or limits are hit). It runs headless claude -p once per stage and tracks progress in ~/.prp/<key>/state/prp-loop.state.json.

Run it

Start a new loop with the user's request as the feature argument:

bash
uv run ${CLAUDE_PLUGIN_ROOT}/skills/prp-loop/scripts/prp_loop.py "$ARGUMENTS"

Resume a halted or in-progress loop:

bash
uv run ${CLAUDE_PLUGIN_ROOT}/skills/prp-loop/scripts/prp_loop.py --resume

Defaults: --max-cycles 3, --max-implement-iterations 10, base branch auto-detected. Pass --validate "<cmd>" to give the loop an authoritative green check (exit 0 = pass).

Stop after a stage (`--until`)

Pass --until <stage> (plan | implement | pr | review | fix) to halt once that stage completes:

bash
uv run ${CLAUDE_PLUGIN_ROOT}/skills/prp-loop/scripts/prp_loop.py "$ARGUMENTS" --until implement

--until implement runs plan → implement and stops once validations are green and the implementation skill has committed and opened its PR — no review.

UX note: the retired Ralph loop was single-session and interactive (a Stop-hook fed the prompt back in the same session). prp-loop --until implement is headless instead — it drives fresh claude -p sessions per iteration and you resume/inspect via the state file rather than watching it live.

What it does

plan — prp-plan writes the plan under the project's PRP store at $PRP_DIR/plans/<feature>.plan.md.
implement — prp-implement executes and validates the plan, commits the work, and opens the PR (bounded by --max-implement-iterations).
pr compatibility — if an older implementation run did not open a PR, prp-pr does so once.
review — prp-review runs its current default review, writes the canonical report, and publishes that complete report to GitHub.
cycle — if the verdict needs fixes, the complete report, plan, and live PR feed into a fresh prp-implement correction pass → push → re-review, up to --max-cycles. Ready to merge → done; review incomplete → halt.

Safety

Fully autonomous (--dangerously-skip-permissions). Operates only on the feature branch — it refuses to PR from main/master/development/the base branch.
Halts with state preserved on: implement/fix not green after the iteration limit, review still dirty after --max-cycles, a fix pass with no new commit (no progress), failed push, or any stage error.
Inspect or resume via ~/.prp/<key>/state/prp-loop.state.json.

Notes

This orchestrator is self-contained and uses no Stop-hook. It owns both loops itself and detects "green" from each stage's VALIDATION: GREEN sentinel (or the --validate command). The PRP skills it calls are invoked verbatim and never modified.

Bundled files

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

scripts/prp_loop.py24 KB

Frequently asked questions

What does the Prp Loop AI skill do?

Why use Prp Loop on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Wirasm/prp/tree/development/plugins/prp-core/skills/prp-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 Prp 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 Prp Loop?

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

Is the Prp Loop AI skill free?

Yes. It is published on GitHub by Wirasm 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

PRP Loop — autonomous cyclic pipeline

Run it

Stop after a stage (--until)

What it does

Safety

Notes

Bundled files

Frequently asked questions

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Stop after a stage (`--until`)