Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/majiayu000/claude-skill-registrynpx agentmods add skills/majiayu000/claude-skill-registry/agent-eyes-edrouhardmicrosoft-agent-canvas-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/majiayu000/claude-skill-registry/agent-eyes-edrouhardmicrosoft-agent-canvas-skills)<a href="https://agentmods.dev/skills/majiayu000/claude-skill-registry/agent-eyes-edrouhardmicrosoft-agent-canvas-skills"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/agent-eyes-edrouhardmicrosoft-agent-canvas-skills/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/majiayu000/claude-skill-registry/agent-eyes-edrouhardmicrosoft-agent-canvas-skills"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/agent-eyes-edrouhardmicrosoft-agent-canvas-skills.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00094 | $0.02364 |
| Opus 5 | $0.00047 | $0.01182 |
| Sonnet 5 | $0.00019 | $0.00473 |
| Haiku 4.5 | $0.00009 | $0.00236 |
Grade A, and why
agent-eyes 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 9d 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 — 286 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Eyes
Visual context analyzer for web pages. Provides AI agents with the ability to "see" web applications through screenshots, accessibility scans, DOM snapshots, and element descriptions.
Prerequisites
- Python 3.10+
uvpackage manager (recommended)- Playwright browsers installed:
playwright install chromium
Compact Mode (Token-Efficient Output)
All commands support --compact / -c flag for token-efficient output:
| Mode | Screenshot | DOM | A11y | Total Tokens |
|---|---|---|---|---|
| Standard | Base64 inline | depth=5, 20 children | Full violations | ~500K+ |
| Compact | File path only | depth=3, 10 children | Summary only | ~3-5K |
Use compact mode when context window size is a concern (which is most of the time).
# Compact context - reduces ~500K tokens to ~3-5K tokens
uv run $SKILL_DIR/agent_eyes.py context http://localhost:3000 --compact
# Compact screenshot - always saves to file, never returns base64
uv run $SKILL_DIR/agent_eyes.py screenshot http://localhost:3000 --compact
# Compact a11y - returns summary + top N issues only
uv run $SKILL_DIR/agent_eyes.py a11y http://localhost:3000 --compact
# Compact DOM - stricter limits on depth and children
uv run $SKILL_DIR/agent_eyes.py dom http://localhost:3000 --compact
Commands
All commands use uv run for automatic dependency management:
SKILL_DIR=".claude/skills/agent-eyes/scripts"
Screenshot
Capture full page or element screenshots:
# Full page screenshot (saves to .canvas/screenshots/)
uv run $SKILL_DIR/agent_eyes.py screenshot http://localhost:3000
# Element screenshot
uv run $SKILL_DIR/agent_eyes.py screenshot http://localhost:3000 --selector ".hero"
# Save to specific path
uv run $SKILL_DIR/agent_eyes.py screenshot http://localhost:3000 --output ./tmp/page.png
# Get as base64 (for inline context) - NOT recommended, use --compact instead
uv run $SKILL_DIR/agent_eyes.py screenshot http://localhost:3000 --base64
# RECOMMENDED: Compact mode - always saves to file, never returns base64
uv run $SKILL_DIR/agent_eyes.py screenshot http://localhost:3000 --compact
What ships with it
1 file 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.
- 9d ago First seen · 286 lines · 94 tokens per session scan A 2794260f8bc8
agent-eyes is a skill published in the GitHub repository majiayu000/claude-skill-registry (604 stars, last pushed yesterday), licensed MIT. It adds 94 tokens to every session and 2,364 once invoked, about $0.0005 per session on Opus 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.
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