A library of practical AI-agent loops and an installable skill for finding, adapting, and designing repeatable agent workflows.
# Add to your Claude Code skills
git clone https://github.com/Forward-Future/loopyLast scanned: 6/28/2026
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}loopy is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Forward-Future. A library of practical AI-agent loops and an installable skill for finding, adapting, and designing repeatable agent workflows. It has 2,647 GitHub stars.
Yes. loopy passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/Forward-Future/loopy" and add it to your Claude Code skills directory (see the Installation section above).
loopy is primarily written in JavaScript. It is open-source under Forward-Future on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh loopy against similar tools.
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Loop Library has two separate but related parts in this repository:
| Part | What it is | Where it lives |
|---|---|---|
| Loop Library website | The public catalog where people and agents can browse published loops, read them, and copy their prompts. No installation is required. | Live website · all website code under loop-library/ (shell in loop-library/site/, database and rendering in loop-library/worker/) |
| Loopy skill | An optional installable guide that helps an AI agent discover, find, audit, repair, craft, run, debrief, save, or prepare loops for publication. It uses the website's live catalog when recommending or publishing loops. | source in skills/loopy/ |
The website is the library; Loopy is a companion way to work with it. You can browse or give an agent the website without installing Loopy. Installing Loopy adds the guided workflow, but it does not install or host the website.
Agents that do not have Loopy can use the published agent guide, agent instructions, JSON catalog, or plain-text catalog directly.
Each published loop tells an agent what to do, how to check its work, what to try next, and when to stop.
Most prompts ask an agent to do something once. A loop gives the agent a way to learn from the result and take the next useful step.
For example, a one-shot prompt might say:
Make this website faster.
A loop adds the feedback that makes the work repeatable:
Find the slowest page, make one focused improvement, and measure it again. Keep the change only if it helps. Repeat until every page meets the target or another pass stops producing a meaningful improvement.
Think of a loop as a playbook with feedback built in. It is useful when the first attempt probably will not be the final answer, such as fixing production errors, improving test coverage, reviewing a product, or keeping documentation current.
A good loop answers four simple questions:
AI agents can move quickly, but an open-ended instruction like "keep improving this" leaves too much room for guessing. A loop gives the work a clear finish line and a consistent way to judge progress.
That makes the work easier to trust and easier to repeat. The agent can compare results instead of relying on confidence, keep improvements instead of merely making changes, and stop when it succeeds or stops making progress. The same loop can also be reused by another person or agent without rebuilding the workflow from scratch.
Loops are not permission for an agent to run forever. The best ones are deliberately bounded. They include a real check, a clear stopping point, and a moment to hand control back to a person when judgment or approval is needed.
Loopy gives your agent direct access to the ideas in the library. You can use it to:
LOOPS.md when you ask, and
reuse those saved loops in later sessions.Loopy checks the live catalog when it recommends a published loop. It does not quietly start schedules, change production, publish content, or send messages on your behalf. Those actions still require the normal permissions and approvals.
You need Node.js and npx. Pick the platform you use:
| Platform | Install command |
|---|---|
| Codex | npx skills add Forward-Future/loopy --skill loopy --agent codex -g -y |
| Cursor | npx skills add Forward-Future/loopy --skill loopy --agent cursor -g -y |
| Claude Code | npx skills add Forward-Future/loopy --skill loopy --agent claude-code -g -y |
To install it for all three at once:
npx skills add Forward-Future/loopy \
--skill loopy \
--agent codex \
--agent cursor \
--agent claude-code \
-g -y
Using another agent? Run the interactive installer and choose from the agents it detects:
npx skills add Forward-Future/loopy --skill loopy -g
The command parts mean:
Forward-Future/loopy is the GitHub repository to install from.--skill loopy selects this skill from the repository.--agent ... selects the agent that should receive it.-g makes it available in all your projects. Leave -g off to install it
only in the current project.-y accepts the install prompts. Leave it off if you want to review the
choices interactively.If an agent was already open and Loopy does not appear, restart that agent.
The previous loop-library skill name remains available as a compatibility
alias for existing installations. Use loopy for all new installations and
explicit invocations.
The slash-command experience differs slightly by platform:
/skills, choose Loopy, then enter your request.
You can also mention it directly with $loopy./ in Agent chat, search for loopy, select it, and
add your request. You can also type /loopy directly./loopy followed by your request.You can also describe a matching task normally. These agents can load the Loopy automatically when your request clearly calls for it, but explicit invocation is the most predictable way to start.
For example, in Codex you can write:
$loopy Analyze this codebase and my coding threads for repeated work, then turn the strongest candidate into a reliable loop.
You do not need to know loop terminology. Invoke Loopy and say what you want to get done. It can take nine paths:
| Path | What it does | Example request |
|---|---|---|
| Discover | Inspects an authorized codebase, coding-thread history, or both for repeated work, then turns the strongest qualified candidate into a bounded loop. | Analyze this repository and my coding threads for work we have done more than once. Turn the best candidate into a loop. |
| Find | Searches the live catalog and recommends up to three published loops. It does not run them. | Find a published loop for keeping our documentation current. |
| Loop Doctor | Audits a loop you paste or name, explains material weaknesses, and repairs only those problems. | Audit this loop and repair only material problems: [paste loop] |
| Adapt | Tailors a useful loop to your real tools, limits, schedule, and definition of success. | Adapt the Overnight Docs Sweep to this repository and our existing checks. |
| Craft | Interviews you one question at a time about the outcome, definition of success, scope, checks, and stopping point, then creates a bounded loop when the catalog has no good fit. | Interview me and help me craft a loop for turning customer feedback into verified fixes. |
| Run | Executes an identified loop in bounded passes, applies its acceptance check, and returns an evidence-backed receipt. | Run the Overnight Docs Sweep in this repository. |
| Debrief | Analyzes one or more completed run receipts and recommends the smallest justified improvement. | Debrief this run receipt and tell me whether the loop needs to change. |
| Save | Saves a loop you want to keep into the project's LOOPS.md, then reuses saved project loops when they fit a later request. |
Save this loop to the project so we can reuse it. |
| Publish | Checks quality and catalog overlap, prepares an exact publication preview, and submits only after explicit approval. | Prepare this loop for publication in Loop Library. |
For example, in Claude Code or Cursor:
/loopy Find a loop for improving test reliability.
In Codex, choose Loopy from /skills, then send:
Find a loop for improving test reliability.
When Loopy delivers a loop that you want to keep for a project, ask it to save
the loop. It appends the accepted loop to LOOPS.md at the project root with a
name, one-sentence explanation, exact prompt, and save date. If the saved loop
is adapted from a published Loop Library loop, Loopy also records the source URL
and the source modified date it saw at save time.
Saved loops are project-local, not published Loop Library entries. In later
find or craft requests, Loopy reads LOOPS.md when it exists and can recommend
a matching saved loop, clearly labeled as the project's own loop. If a saved
adaptation points to a published source that has changed since it was saved,
Loopy gives a short heads-up and offers to compare before reuse.
Loopy saves only when you ask. It will not create LOOPS.md, edit another
saved loop,