Atlas / Skills / alinaqi / Visual Validation

Visual ValidationSAFE

skills/alinaqi/visual-validation

What started as an opinionated Claude Code setup kit is now an autonomous AI engineering command center

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
1 documented
License
MIT
Stars
707
01

Overview

What started as an opinionated Claude Code setup kit is now an autonomous AI engineering command center

Read from source at commit 3a4a7596e97eOBSERVED · 2026-10-13
02

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
claude-codementioned
03

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: visual-validation
description: Autonomous screenshot verification — captures, compares, and AI-evaluates UI changes for visual regressions
when-to-use: When a UI or static-asset change needs visual verification before shipping
user-invocable: false
effort: medium
---

# Visual Validation — Autonomous Screenshot Verification

## Philosophy

Every UI change should be visually verified before it ships. Peekaboo captures pixel-accurate screenshots. The system compares before/after and flags visual regressions. No manual "looks good to me" — the machine verifies what the machine built.

## Autonomous Flow

```
static/* files modified (detected by auto-review-hook or E2E testkit)
    ↓
peekaboo image --mode screen → ~/.maggy/visual-verify/after-{ts}.png
    ↓
Compare with latest baseline (previous after-*.png)
    ↓
AI evaluation: Gemini Flash analyzes screenshot for visual regressions
    ↓
Report: CLEAN or REGRESSION_DETECTED with specific issues
```

## Quick Commands

```bash
# Install
brew install steipete/tap/peekaboo

# Capture full system screenshot
peekaboo image --mode screen --retina --path /tmp/screen.png

# Capture specific window
peekaboo image --mode window --app "Google Chrome" --path /tmp/window.png

# Verify Maggy dashboard after code change
peekaboo image --mode window --app "Google Chrome" --path ~/.maggy/visual-verify/after-$(date -u +%Y%m%d-%H%M%S).png

# Compare two screenshots
ls -la ~/.maggy/visual-verify/after-*.png  # review before/after pairs
```

## Autonomous Verification Flow (Claude Code)

```bash
# After making any static/ file change, Claude should:
1. git add maggy/maggy/static/ && git diff --stat HEAD  # check what changed
2. Restart Maggy: lsof -ti :8080 | xargs kill && python3 -m maggy.main &
3. Wait for health: curl -s http://localhost:8080/api/health
4. Capture screenshot: peekaboo image --mode screen --path ~/.maggy/visual-verify/after-$(date -u +%Y%m%d-%H%M%S).png
5. Compare with latest baseline in ~/.maggy/visual-verify/
6. AI evaluation: ~/bin/gemini-api --flash "Analyze this screenshot for visual regressions"
7. Report findings
```

## Maggy Dashboard Verification

```bash
# One-shot verification
curl -s http://localhost:8080/api/health && \
peekaboo image --mode screen --path ~/.maggy/visual-verify/verify.png && \
echo "✓ Dashboard verified — screenshot at ~/.maggy/visual-verify/verify.png"
```

## Integration Points

### Auto-Review Hook (already wired)
- Detects `static/` changes in git diff
- Auto-captures Peekaboo screenshot
- Saves before/after pairs in `~/.maggy/visual-verify/`

### E2E Testkit Plugin
- Visual regression testing as part of `POST /api/testkit/run`
- Compares screenshots against baselines
- Flags pixel differences above threshold

### Build-in-Public Plugin
- Peekaboo screenshots replace AI-generated images
- Real product captures for LinkedIn/X posts

## When to Use

| Scenario | Command |
|----------|---------|
| After static/ change | `peekaboo image --mode screen --path ~/.maggy/visual-verify/after.png` |
| Before committing UI change | Run verification flow above |
| Reviewing dashboard | Screenshot + AI analysis |
| Build-in-public post | Auto-captured by plugin |
| Cross-browser check | `peekaboo image --mode window --app "Safari"` |
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-13 · audit v0.4.1 · source sha 3a4a7596e97efull audit observations/trust-audit/skill/alinaqi__visual-validation.json · Report an issue / request a re-scan
05

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-133a4a7596e97eSAFEB89first audit
06

Questions

What does the Visual Validation skill do?

What started as an opinionated Claude Code setup kit is now an autonomous AI engineering command center

Is Visual Validation safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Visual Validation access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does Visual Validation work with?

Its documentation mentions claude-code. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (3a4a7596e97e), read on 2026-10-13. The repository is watched, and a new audit runs when it changes — this is the first audit.

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