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Cxc Loop

Community
lidge-jun
cxc-loop

Use for PABCD completion loops. Triggers: cxc-loop, continue until done, HOTL, repeated PABCD, 루프 돌려, 끝까지 해줘, docs-first.

Overview

Publisherlidge-jun
Repositorycodexclaw
Skill namecxc-loop
Stars
51
Forks
10
Bundled files
6
LicenseMIT
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.

  • 6 bundled files

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

  • Open source

    Published by lidge-jun on GitHub. Read the source before you install it.

Installation

Install the Cxc 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.
    https://github.com/lidge-jun/codexclaw/tree/main/plugins/codexclaw/skills/loop
  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/lidge-jun/codexclaw.git /tmp/codexclaw
mkdir -p .claude/skills
cp -r /tmp/codexclaw/plugins/codexclaw/skills/loop .claude/skills/cxc-loop
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cxc 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 Cxc 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 Cxc 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.

cxc-loop — Scoped completion

Intent before activation

Bare operative cxc-loop means scoped HOTL; explicit HITL keeps human P/A/B pauses. Loading, explanation and review activate nothing. Explicit limits win. HOTL adds persistence, never permissions; report missing authority.

A leaf follows its packet, owns no goal/FSM and needs a grant to spawn. Dispatched tasks own their goal/FSM within their packet's grant. Before dispatch, read Dispatch surfaces (DISPATCH-SURFACE-01).

Use cxc-dev for safety, proof, complete selected reads, peer contact, async questions and installed-skill discovery. Select owners by task/class/risk/phase; preserve explicit-only and leaf-safe restrictions and resolve missing mandatory references before work.

Read before the action

ActionOwner
PABCD work or planningcxc-pabcd
HOTL entry, resumption or completion diagnosisRuntime lifecycle
Goalplan schema, CLI or amendmentDurable goalplan
Multi-cycle roadmapImplementation units
Repeated failure, reviewer FAIL or archetype selectionLoop engineering
Score optimization, plateau or mechanism comparisonOptimization + loop engineering above
Candidate divergenceDivergence tiers
Task dispatch or lane observationLane dispatch
Authorized subagent dispatchDelegation
Waiting on work or external processesWaiting
Composition, response projection or in-context computationNative execution

Execution invariants

  • ORCH-MANDATE-01 (STRICT): read persisted state before claiming loop entry/re-entry; binding and edges follow Phase control (SESSION-IDENTITY-01).
  • HOTL needs an ACTIVE host goal and in-flight cycle; HITL needs no goal. Missing capability/binding is a preflight failure, never armed continuation.
  • Follow cxc-pabcd's one-work-phase/one-cycle invariant; hooks neither choose nor advance phases.
  • LOOP-CONTINUE-01 (DEFAULT): after D or context loss, read the bound goalplan and ledger; preserve criteria and re-enter P while in-scope work remains under the active goal.
  • LOOP-UNIT-CHAIN-01 (DEFAULT): add genuinely new in-scope units through a P amendment to the same goal.
  • LOOP-CONTINUITY-01 (DEFAULT): next P quotes the previous D conclusion and direction, explains any change, and resumes from durable evidence.
  • LOOP-GIT-01 (DEFAULT): before checkpoints or publication, apply cxc-dev's git rules; declared stacks also read Stacked PRs.

Docs-first multi-cycle entry

LOOP-DOCS-FIRST-01 (DEFAULT): this entry is STRICT for HOTL. Two or more work-phases start with a goalplan skeleton and docs-only roadmap cycle. D locks the roadmap; implementation starts next cycle. Later P consumes/revalidates one prewritten decade doc. Scope discovered later pays this debt at next P. No production patches, deploys or implementation-complete claims in the roadmap cycle. Single-cycle work skips it; cxc-dev owns C0/C1 exceptions.

LOOP-READS-PABCD-01 (STRICT): before multi-cycle execution read implementation units above for roadmap contents/numbering; skeletons or empty decade docs do not satisfy it.

Completion and recovery

Report DONE, NOOP, BLOCKED, UNSAFE, NEEDS_HUMAN or BUDGET_EXHAUSTED as outcomes, not FSM phases or host goal statuses. DONE requires cxc-dev's fresh proof and the runtime-lifecycle completion gate (GOAL-COMPLETE-GATE-01); never weaken criteria. Exhaustion requires an actual stated bound. Compaction, wait timeout and Stop release prove neither success nor exhaustion; preserve evidence and recover through the applicable owner.

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 Cxc Loop AI skill do?

Use for PABCD completion loops. Triggers: cxc-loop, continue until done, HOTL, repeated PABCD, 루프 돌려, 끝까지 해줘, docs-first.

Why use Cxc Loop on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lidge-jun/codexclaw/tree/main/plugins/codexclaw/skills/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 Cxc 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 Cxc Loop?

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

Is the Cxc Loop AI skill free?

Yes. It is published on GitHub by lidge-jun 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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