ULC Loop
SkillAI & modelsStart a Unified Loop Controller session via Ralph Wiggum. Autonomously works through backlog, dispatches agents, and explores via QD when idle.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the ULC Loop skill
What this skill tells your AI
The instructions your AI receives, as published by kastalien-research/thoughtbox in .agents/skills/ulc-loop/SKILL.md and read by ahel’s review.
Start an autonomous improvement loop powered by Ralph Wiggum.
Setup
Parse arguments from: $ARGUMENTS
Defaults:
--budget: 5 (USD)--max-iterations: 20
Workflow
Step 1: Pre-flight Checks
-
Verify Ralph Wiggum plugin is installed:
ls .Codex/plugins/cache/Codex-plugins/ralph-wiggum/ 2>/dev/null || echo "NOT INSTALLED"If not installed, tell the user to run:
Codex plugin install ralph-wiggum@Codex-plugins -
Check for existing Ralph loop:
cat .Codex/ralph-loop.local.md 2>/dev/null && echo "ACTIVE" || echo "INACTIVE"If ACTIVE, warn: "A Ralph loop is already running. Run
/cancel-ralphfirst." -
Check git state is clean:
git status --porcelainIf dirty, warn and suggest committing first.
Step 2: Read the ULC Prompt
Read the ULC decision procedure from .Codex/skills/ulc-loop/ulc-prompt.md.
Step 3: Initialize ULC State
Create the initial ULC state file if it doesn't exist:
cat > .Codex/ulc-state.local.json << 'EOF'
{
"iteration": 0,
"cumulative_cost_usd": 0,
"budget_usd": <BUDGET>,
"actions": [],
"exploration_misses": 0,
"started_at": "<ISO timestamp>"
}
EOF
Replace <BUDGET> with the parsed budget value.
Step 4: Create Ralph State File
Write .Codex/ralph-loop.local.md with YAML frontmatter and the ULC prompt as the body:
---
active: true
iteration: 1
max_iterations: <MAX_ITERATIONS>
completion_promise: "BUDGET EXHAUSTED OR ALL WORK COMPLETE"
started_at: "<ISO timestamp>"
---
<contents of ulc-prompt.md>
Step 5: Confirm and Start
Output:
ULC Loop activated via Ralph Wiggum.
Budget: $<budget> USD
Max iterations: <max_iterations>
Completion promise: "BUDGET EXHAUSTED OR ALL WORK COMPLETE"
The loop will:
1. Check backlog for ready work
2. Dispatch sub-agents for substantial tasks
3. Explore via QD when backlog is empty
4. Stop when budget is exhausted or all work is complete
State file: .Codex/ulc-state.local.json
Ralph state: .Codex/ralph-loop.local.md
Starting first OODA cycle...
Then immediately begin executing the ULC prompt — perform the first OODA cycle (Observe → Orient → Decide → Act).
Notes
- The ULC prompt is re-fed by Ralph's stop hook on each iteration
- Inter-iteration continuity is via
.Codex/ulc-state.local.jsonand git - Sub-agents are dispatched via Task tool with
subagent_type: "general-purpose" - Cost tracking is approximate — the agent estimates based on model and turns
- The loop does NOT push to remote — human reviews and pushes
Signals
- GitHub stars
- 64
- Forks
- 20
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
ulc-loop- Source
- github.com/kastalien-research/thoughtbox