Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Alenryuichi/openmemory-plus --skill visual-testing-loopgit clone --depth 1 https://github.com/Alenryuichi/openmemory-plusWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alenryuichi/openmemory-plus/visual-testing-loop)<a href="https://agentmods.dev/skills/alenryuichi/openmemory-plus/visual-testing-loop"><img src="https://agentmods.dev/badge/skills/alenryuichi/openmemory-plus/visual-testing-loop/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alenryuichi/openmemory-plus/visual-testing-loop"><img src="https://agentmods.dev/badge/skills/alenryuichi/openmemory-plus/visual-testing-loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00046 | $0.01028 |
| Opus 5.5 | $0.00018 | $0.00411 |
| Sonnet 5.5 | $0.00009 | $0.00206 |
| Haiku 4.5 | $0.00005 | $0.00103 |
Grade A, and why
visual-testing-loop scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Visual Testing Loop
Overview
Automate the visual feedback loop for frontend development. No manual verification needed - Agent sees what users see and iterates autonomously.
Core principle: Generate → Serve → Screenshot → Analyze → Iterate (until satisfied)
When to Use
- Building new UI components or pages
- Iterating on visual design
- Verifying responsive layouts
- Testing dark/light themes
- Quality-checking before delivery
Prerequisites
Agent must have access to Playwright MCP tools:
browser_navigate_playwrightbrowser_take_screenshot_playwrightbrowser_snapshot_playwrightlaunch-process(for starting dev server)
The Loop
Phase 1: Generate
Create or modify the frontend code:
- Apply
frontend-designskill for aesthetic quality - Generate production-grade HTML/CSS/JS or React components
- Ensure code is runnable locally
Phase 2: Serve
Start a local development server:
# For static HTML
npx serve -p 3000 ./dist
# For React/Vite
npm run dev
# For Next.js
npm run dev
Keep server running (use wait=false for background process)
Phase 3: Screenshot
Capture the rendered output:
-
Navigate to the page:
browser_navigate_playwright → http://localhost:3000 -
Wait for page load:
browser_wait_for_playwright → wait for key elements -
Take screenshot:
browser_take_screenshot_playwright → save to file -
For full page:
browser_take_screenshot_playwright → fullPage: true
Phase 4: Analyze
Evaluate the screenshot against quality criteria:
Visual Checklist:
- Typography is distinctive (not generic fonts)
- Color palette is cohesive and intentional
- Layout has visual hierarchy
- Spacing is consistent
- No visual glitches or overflow
- Responsive at current viewport
- Matches intended aesthetic direction
Technical Checklist:
- All elements render correctly
- Images/icons load properly
- No console errors (check
browser_console_messages_playwright) - Interactive states work (hover, click)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 173 lines · 46 tokens per session scan A 80c1e5a073d4
visual-testing-loop is a skill published in the GitHub repository Alenryuichi/openmemory-plus (20 stars, last pushed 7mo ago), licensed MIT. It adds 46 tokens to every session and 1,028 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
run-app
USE WHEN: running, smoke-testing, or visually checking the apps - starting the worker-api / front-app dev servers, probing health, CORS, the 404 envelope and the SPA shell, rendering the SPA in a headless browser, reading local request traces, or probing a Worker Preview URL the user deployed. This is the project…
testing-pyramid
Test Distribution Analysis Command 🧪.
playwright-cli
Automate browser interactions, test web pages and work with Playwright tests.
screen-reader-testing
Test web applications with screen readers including VoiceOver, NVDA, and JAWS. Use when validating screen reader compatibility, debugging accessibility issues, or ensuring assistive technology support.
eval-dataset-design
A guide to creating reliable test sets for AI agents. Each evaluation task includes the request, the simulated user's behaviour, a reset starting state, and a success check that can be independently verified.
mobile-automation
Control Android and iOS devices, emulators and simulators — launch apps, tap, swipe, type, take screenshots, read the accessibility tree. Use when a task involves a mobile device or app, mobile UI testing, or reproducing a bug on a phone.