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 vladmdgolam/agent-skills --skill visual-feedback-loopgit clone --depth 1 https://github.com/vladmdgolam/agent-skillsWrote 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/vladmdgolam/agent-skills/visual-feedback-loop)<a href="https://agentmods.dev/skills/vladmdgolam/agent-skills/visual-feedback-loop"><img src="https://agentmods.dev/badge/skills/vladmdgolam/agent-skills/visual-feedback-loop.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00137 | $0.01275 |
| Opus 5 | $0.00068 | $0.00638 |
| Sonnet 5 | $0.00027 | $0.00255 |
| Haiku 4.5 | $0.00014 | $0.00128 |
Grade A, and why
visual-feedback-loop scanned grade A with 1 finding 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 8d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl http://localhost:3000/api/dev-screenshot How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Visual Feedback Loop
Capture, inspect, and compare visual output from a running web app during iterative development.
How It Works
Agent (CLI) Server Browser
|--- GET /api/dev-screenshot -->|--- SSE "capture" ----------->|
| ?param=value | |-- capture canvas
| |<-- POST { dataUrl } ---------|
| | writes:
| | .screenshots/{UTC}.webp
| | .screenshots/{UTC}.json (metadata)
| | .screenshots/latest.webp (convenience copy)
|<-- { ok, path, latest } ------|
Agent can't access the browser directly. Server relays: GET triggers → SSE notifies browser → browser captures and POSTs back → GET resolves.
Usage
Capture current view:
curl http://localhost:3000/api/dev-screenshot
Capture with params (app-specific — browser client interprets them):
curl 'http://localhost:3000/api/dev-screenshot?component=header&theme=dark'
curl 'http://localhost:3000/api/dev-screenshot?letter=б&depth=0.8'
Then read the result. Response includes path (timestamped file) and latest (convenience copy):
Read .screenshots/latest.webp
Visual Regression (pixel diff)
Compare against a ground truth screenshot using ImageMagick:
magick compare -metric RMSE .screenshots/ground-truth.webp .screenshots/latest.webp .screenshots/diff.webp
RMSE output: 0.01 = ~1% difference (rendering noise), 0.03+ = visible change. Save diff image for inspection.
Metadata Sidecars
Each screenshot gets a JSON sidecar with the same UTC timestamp:
{
"timestamp": "2026-02-25T08:22:12.655Z",
"git": { "commit": "0a5726f", "dirty": true },
"params": { "letter": "о", "chamferModel": "membrane", "cameraView": "front" },
"format": "webp",
"file": "2026-02-25T08-22-12-655Z.webp"
}
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 105 lines · 137 tokens per session scan A e90b368dfbbc
visual-feedback-loop is a skill published in the GitHub repository vladmdgolam/agent-skills (8 stars, last pushed 4d ago), licensed MIT. It adds 137 tokens to every session and 1,275 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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