the-loop

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• SKILL.md

SKILL.md (first lines)

# THE LOOP

A screenshot shows a moment; it cannot show a flow. THE LOOP records the
actual running target, watches the recording, and judges it against pass
criteria you state in plain language. The loop only observes — YOU apply
the fixes, then iterate. On pass it renders a before/after MP4 + GIF as
proof.

## UI / web page / desktop window

```bash
watch-skill loop start "<url | screen: | window:<title> | file>" "<pass criteria>" [--script '<json steps>']
# ...apply the suggested fixes to the code...
watch-skill loop iterate <loop_id>
```

- Pass criteria are ordinary sentences: "the checkout completes, no
  error toast ever appears, the total is never NaN". Negative claims
  ("never X") and exemplars ("a real price (like $29.00)") are both
  understood and enforced deterministically.
- `--script` replays the same clicks/fills every iteration, so the
  comparison is honest.
- Only call `iterate` after you actually changed something. It diffs
  against the previous iteration: fixed / unchanged / new.

## Generated video (Manim, Remotion, ffmpeg, AI-gen)

```bash
watch-skill loop video-gen "<what the video must show>" "<render command>" --output <file>
```

Re-runs the generator each iteration and judges the fresh render against
the spec.

## Game / simulation

```bash
watch-skill loop game "<canvas-url | window:<title> | screen:>" "<pass criteria>" [--run "<launch cmd>"]
```

Catches the failures screenshots miss: a NaN score counter, black
flicker frames, sprites that vanish mid-motion.

## Watch for a condition (monitoring)

```bash
watch-skill loop monitor "<folder | url | screen: | window:<title>>" "<condition>" [--interval 10] [--max-checks 10]
```

Bounded — it always terminates. Events land in `events.jsonl` under the
loop directory as structured records.

## Record without judging

```bash
watch-skill capture "<target>" [--duration 10]
```

Capture alone never critiques; it just records, analyzes, and indexes.
Use `loop start` when there are pass criteria.

From Pa1loh/PadraoAI, MIT.

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