Loop Library has two separate but related parts in this repository:

The website is the library; the skill is a companion way to work with it. You can browse or give an agent the website without installing the skill. Installing the skill adds the guided workflow, but it does not install or host the website.

Agents that do not have the skill 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.

What is a loop?

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:

• What is the agent trying to accomplish?
• How will it know whether the latest attempt worked?
• What should it do with what it learned?
• When should it finish or ask for help?

Why loops are powerful

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.

What the Loop Library skill does

The Loop Library skill gives your agent direct access to the ideas in the library. You can use it to:

• Discover repeated work in a codebase, coding threads, or both and turn the strongest qualified candidate into a loop.
• Find a published loop that fits what you are trying to get done.
• Audit an existing loop for weak checks, unsafe actions, or unclear stopping behavior, then repair only the material problems.
• Adapt a useful loop to your tools, limits, and definition of success.
• Design a new loop through a short, plain-language conversation.
• Turn the result into a compact prompt you can use right away.

The skill checks the live catalog when it recommends a published loop. It does not quietly start schedules, change production, or send messages on your behalf. Those actions still require the normal permissions and approvals.

Install the skill

You need Node.js and npx. Pick the platform you use:

To install it for all three at once:

npx skills add Forward-Future/loop-library \
  --skill loop-library \
  --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/loop-library --skill loop-library -g

The command parts mean:

• Forward-Future/loop-library is the GitHub repository to install from.
• --skill loop-library 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 the skill does not appear, restart that agent.

Invoke the skill

The slash-command experience differs slightly by platform:

• Codex: type /skills, choose Loop Library, then enter your request. You can also mention it directly with $loop-library.
• Cursor: type / in Agent chat, search for loop-library, select it, and add your request. You can also type /loop-library directly.
• Claude Code: type /loop-library followed by your request.

You can also describe a matching task normally. These agents can load the skill 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:

$loop-library Analyze this codebase and my coding threads for repeated work, then turn the strongest candidate into a reliable loop.

Use Loop Library

You do not need to know loop terminology. Invoke the skill and say what you want to get done. It can take five paths:

For example, in Claude Code or Cursor:

/loop-library Find a loop for improving test reliability.

In Codex, choose Loop Library from /skills, then send:

Find a loop for improving test reliability.

Discover loops from your work

Discovery looks for recurring engineering work in the sources you put in scope. In a codebase, that can include scripts, CI and deployment configuration, tests, runbooks, maintenance commands, and repeated lifecycle patterns. In coding threads, it groups equivalent completed work even when the wording differs.

The skill requires at least two distinct thread occurrences before calling work repeated. A code pattern without run history is labeled as a potential loop, not proven recurrence. It then checks whether fresh feedback can change the next action, whether success can be verified, and whether the work has clear limits, stopping behavior, and approval boundaries. It also checks the live catalog to avoid recreating an existing loop.

The skill can inspect only repositories and coding threads that your agent can access and that you place in scope. If thread history is unavailable, it uses the codebase evidence and says so. A discovery result includes compact source evidence and either a new loop, an adaptation of a published loop, a short candidate slate when your choice matters, or a clean no-op when nothing truly fits.

When the skill finds or creates the right loop, it gives you a prompt to use with your agent. Review any placeholders, then ask the agent to run that prompt in the project you want it to work on. Selecting a loop does not start a schedule, deploy code, delete data, send messages, or grant new permissions; you must request those actions explicitly.

Every published loop also includes a few useful parts:

• Use when explains the problem the loop is meant to solve.
• Prompt is the copy-ready instruction for your agent.
• Verify defines the evidence that proves the work succeeded.
• Steps show the feedback cycle in a more readable form.
• Notes call out practical limits, risks, or setup details.
• Related loops point to nearby workflows that may fit better.

Explore or contribute

Visit the Loop Library to browse published loops, copy one into your own workflow, or submit a loop that has worked well for you.

Loop Library is a Forward Future project and is available under the MIT License.

LOOP_PUBLISH_TOKEN=... \
  npm --prefix worker run loop:publish -- /path/to/loop.json

LOOP_PUBLISH_TOKEN=... \
  npm --prefix worker run loops:import -- /private/path/bootstrap.json

LOOP_PUBLISH_TOKEN=... \
  npm --prefix worker run loops:export -- /private/path/catalog-backup.ndjson

LOOP_PUBLISH_TOKEN=... \
  npm --prefix worker run loops:restore -- /private/path/catalog-backup.ndjson

python3 -m http.server 4173 --directory site

npm ci --prefix worker
node --check site/script.js
node scripts/check.mjs
npm --prefix worker run check
python3 -m json.tool site/.herenow/data.json >/dev/null
python3 -m json.tool scripts/seo-geo-query-benchmark.json >/dev/null
git diff --check