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New Loop

OrganizationPopular
AI-Builder-Club
new-loop

Spin up a new loop (domain) in a file-based knowledge base — bootstrap the substrate if it's missing, gather the loop's charter, scaffold domains/<loop>/README.md, then do ONE real test run and record it in the loop's Timeline and LOG.md. Use when the user says "set up a new loop", "create a domain", "start a new beat/workstream", or names a recurring job they want the agent to own.

Overview

PublisherAI-Builder-Club
Repositoryskills
Skill namenew-loop
Stars
1.3K
Forks
159
Bundled files
4
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.

  • 4 bundled files

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

  • Open source

    Published by AI-Builder-Club on GitHub. Read the source before you install it.

Installation

Install the New 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/AI-Builder-Club/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/new-loop .claude/skills/new-loop
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable New 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 New 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 New 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.

new-loop — spin up a new loop

A loop (a domain) is a recurring thread of work the agent owns: a charter, a cadence, and the artifacts it produces. This skill creates one, proves it works with a single real run, and leaves behind a domains/<loop>/README.md that is the loop's live state.

When to use

The user wants to stand up a new workstream/beat/job (e.g. "a weekly SEO loop", "a support triage loop", "a competitor-watch loop"). Don't use this for a one-off task — that's a backlog line in an existing domain, or a doc/signal.

Inputs to gather (ask only what's missing)

Infer from the request; ask a short clarifying round only for what you can't:

  1. name — kebab-case, the loop's home folder (domains/<name>/). Keep it short.
  2. goal — one line: the outcome this loop drives.
  3. cadencemanual / daily / weekly / a cron expr. Default manual.
  4. what it does — what it consumes (signals? data? an inbox? a URL?) and produces (signals? docs? a report? code changes shipped via /verify?).
  5. tools/data — sources or credentials it needs (point at a setup skill or .env; never inline secrets).

If the request is already specific, infer all five and just confirm in your summary.

Procedure

1. Bootstrap the substrate (one-time; skip if already set up)

Check the knowledge-base repo root for:

  • ARCHITECTURE.md and LOG.md, and
  • a CLAUDE.md that has a "Knowledge base" section.

All present → the substrate exists; skip to Step 2. Anything missing → read references/KNOWLEDGE_SETUP.md and follow it — it copies in ARCHITECTURE.md + LOG.md, creates signals/ docs/ domains/ with their README schemas, and injects the knowledge-base section into CLAUDE.md (or scaffolds one from references/CLAUDE.template.md). It's idempotent: it only creates what's missing.

(Read references/ARCHITECTURE.md once if you haven't — it's the model this skill instantiates.)

2. Scaffold the loop README

Create domains/<name>/README.md from the domain template (in domains/README.md, also quoted in references/KNOWLEDGE_SETUP.md), filled with the gathered inputs. Required sections: frontmatter (kind: domain, domain, status: active, goal, cadence), a 2–4 line description, ## Current focus, ## Backlog (to-dos inline — they stay in the README until they earn a task kind), and an empty ## Timeline. Add ## Evidence & analysis / ## Metrics placeholders if relevant.

Collision check: if domains/<name>/ already exists, stop and ask whether to update it instead of overwriting.

3. Do ONE real test run

The point of the skill: prove the loop actually runs, not just that the folder exists.

Actually run the loop once, at small scale — do whatever it's meant to do (triage a few real tickets, pull one real SERP, fetch the inbox, draft one comment, run one analysis query, scope one code change…). Use real tools/data where you can; if a credential is missing, do the furthest-reachable dry run and note the gap.

Producing an artifact is optional — a legit run may surface nothing worth filing. Only create a signal/doc if the run genuinely produced one.

Two required outputs regardless:

  • Append one dated line to the loop README's ## Timeline: YYYY-MM-DD | test run — <what you did and found / "nothing actionable yet">.
  • Append one entry to LOG.md (its grammar):
    ## YYYY-MM-DD · <loop-name> loop created + first run · #ops
    What: <one line — what the loop is and what the first run did/found>.
    Refs: domains/<name>/README.md (new)[, any artifact created].

4. Report back

Summarize: the loop's charter (the five inputs), what the test run did/found, any artifacts created (or "none — nothing actionable this run"), missing tools/credentials to wire up, and how to run it again (cadence + entry point). Keep it tight.

Notes

  • Don't gold-plate the scaffold. A loop README is live state, not a spec — start lean; let it accrete via its Timeline.
  • One loop = one separable workstream. If what the user described is really part of an existing loop, add it there (a backlog line + a domain: tag) instead of a near-duplicate.
  • For loops that ship code, the loop's run works in an isolated git worktree and ships via the /verify skill (proof + PR), giving each parallel agent its own isolated stack via crabbox-setup (sibling harness skills in this plugin). Point the README's Backlog at them.

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 New Loop AI skill do?

Spin up a new loop (domain) in a file-based knowledge base — bootstrap the substrate if it's missing, gather the loop's charter, scaffold domains/<loop>/README.md, then do ONE real test run and record it in the loop's Timeline and LOG.md. Use when the user says "set up a new loop", "create a domain", "start a new beat/workstream", or names a recurring job they want the agent to own.

Why use New Loop on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AI-Builder-Club/skills/tree/main/skills/new-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 New 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 New Loop?

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

Is the New Loop AI skill free?

It is published on GitHub by AI-Builder-Club. Check the repository for licensing terms. 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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