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 majiayu000/claude-skill-registry --skill agent-browser-chachamaru127-claude-code-harness-4git clone --depth 1 https://github.com/majiayu000/claude-skill-registryWrote 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-browser-chachamaru127-claude-code-harness-4)<a href="https://agentmods.dev/skills/majiayu000/claude-skill-registry/agent-browser-chachamaru127-claude-code-harness-4"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/agent-browser-chachamaru127-claude-code-harness-4/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-browser-chachamaru127-claude-code-harness-4"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/agent-browser-chachamaru127-claude-code-harness-4.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 | $0.00120 | $0.01734 |
| Opus 5 | $0.00060 | $0.00867 |
| Sonnet 5 | $0.00024 | $0.00347 |
| Haiku 4.5 | $0.00012 | $0.00173 |
Grade A, and why
agent-browser 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 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.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- agent-browser — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Browser Skill
ブラウザ自動化を行うスキル。agent-browser CLI を使用して、UI デバッグ・検証・自動操作を実行します。
トリガーフレーズ
このスキルは以下のフレーズで自動起動します：
- 「ページを開いて」「URLを確認して」
- 「クリックして」「入力して」「フォームに」
- 「スクリーンショットを撮って」
- 「UIを確認して」「画面をテストして」
- "open this page", "click on", "fill the form", "screenshot"
機能詳細
| 機能 | 詳細 |
|---|---|
| ブラウザ自動化 | See references/browser-automation.md |
| AI スナップショットワークフロー | See references/ai-snapshot-workflow.md |
実行手順
Step 0: agent-browser の確認
# インストール確認
which agent-browser
# 未インストールの場合
npm install -g agent-browser
agent-browser install
Step 1: ユーザーのリクエストを分類
| リクエストタイプ | 対応アクション |
|---|---|
| URL を開く | agent-browser open <url> |
| 要素をクリック | スナップショット → agent-browser click @ref |
| フォーム入力 | スナップショット → agent-browser fill @ref "text" |
| 状態確認 | agent-browser snapshot -i -c |
| スクリーンショット | agent-browser screenshot <path> |
| デバッグ | agent-browser --headed open <url> |
Step 2: AI スナップショットワークフロー（推奨）
ほとんどの操作で、まずスナップショットを取得してから要素参照で操作します：
# 1. ページを開く
agent-browser open https://example.com
# 2. スナップショット取得（AI 向け、インタラクティブ要素のみ）
agent-browser snapshot -i -c
# 出力例:
# - link "Home" [ref=e1]
# - button "Login" [ref=e2]
# - input "Email" [ref=e3]
# - input "Password" [ref=e4]
# - button "Submit" [ref=e5]
# 3. 要素参照で操作
agent-browser click @e2 # Login ボタンをクリック
agent-browser fill @e3 "[email protected]"
agent-browser fill @e4 "password123"
agent-browser click @e5 # Submit
Step 3: 結果の確認
# 現在の状態をスナップショットで確認
agent-browser snapshot -i -c
# または URL を確認
agent-browser get url
# スクリーンショットを取得
agent-browser screenshot result.png
クイックリファレンス
基本操作
| コマンド | 説明 |
|---|---|
open <url> |
URL を開く |
snapshot -i -c |
AI 向けスナップショット |
click @e1 |
要素をクリック |
fill @e1 "text" |
フォームに入力 |
type @e1 "text" |
テキストを入力 |
press Enter |
キーを押す |
screenshot [path] |
スクリーンショット |
close |
ブラウザを閉じる |
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.
- 8d ago First seen · 187 lines · 120 tokens per session scan A 81fcb79558c2
agent-browser is a skill published in the GitHub repository majiayu000/claude-skill-registry (604 stars, last pushed today), licensed MIT. It adds 120 tokens to every session and 1,734 once invoked, about $0.0006 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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