Visual ValidationSAFE
What started as an opinionated Claude Code setup kit is now an autonomous AI engineering command center
Overview
What started as an opinionated Claude Code setup kit is now an autonomous AI engineering command center
3a4a7596e97eOBSERVED · 2026-10-13Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| claude-code | mentioned |
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"` |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.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (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.
3a4a7596e97efull audit observations/trust-audit/skill/alinaqi__visual-validation.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-13 | 3a4a7596e97e | SAFE | B | 89 | first audit |
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.