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 cafe3310/public-agent-skills --skill git-snapshot-rollbackgit clone --depth 1 https://github.com/cafe3310/public-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/cafe3310/public-agent-skills/git-snapshot-rollback)<a href="https://agentmods.dev/skills/cafe3310/public-agent-skills/git-snapshot-rollback"><img src="https://agentmods.dev/badge/skills/cafe3310/public-agent-skills/git-snapshot-rollback/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/cafe3310/public-agent-skills/git-snapshot-rollback"><img src="https://agentmods.dev/badge/skills/cafe3310/public-agent-skills/git-snapshot-rollback.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 | $0.00024 | $0.00567 |
| Opus 5 | $0.00012 | $0.00283 |
| Sonnet 5 | $0.00005 | $0.00113 |
| Haiku 4.5 | $0.00002 | $0.00057 |
Grade A, and why
git-snapshot-rollback 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 10d 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.
What it actually says
Git Snapshot & Rollback
此技能通过自动化脚本确保在回退 Git 提交时，不仅保留了当前的尝试（Snapshot），还通过 ARCHIVE.md 构建了一个可追溯的决策链表。
核心工作流
1. 确认回退目标
- 获取用户想要回退到的目标 Commit Hash。
- 询问或总结回退的具体原因（Reason）。
2. 执行自动化回退脚本
- 在执行前，必须询问用户是否需要将存档分支推送到远端仓库。
- 使用
run_shell_command调用技能内置脚本：- 如果用户同意推送：
python3 <path_to_skill>/scripts/rollback.py <Target_Commit> "<Reason>" --push - 如果用户不同意推送（默认）：
python3 <path_to_skill>/scripts/rollback.py <Target_Commit> "<Reason>"
- 如果用户同意推送：
- 脚本将自动完成：
- Commit 当前所有未提交的变更。
- 创建
archive/{current_branch}/YYYY-MM-DD-HH-mm分支。 - 更新存档分支的
ARCHIVE.md记录。 - (可选) 将存档分支推送到远端。
- 回到原分支并执行
git reset --hard。 - 在原分支更新
ARCHIVE.md并提交回退记录。 - 列出当前所有领先于远程（未推送）的分支。
3. 结果验证
- 检查
ARCHIVE.md是否已正确记录了本次回退的双向链接。 - 确认当前分支已处于目标 Commit 状态。
记录规范
- 关于
ARCHIVE.md的具体格式，请参考 references/log-format.md。 - 每次回退的 Commit Message 必须包含来源存档分支的信息。
使用禁令
- 严禁在没有使用此技能的情况下直接执行
git reset --hard来放弃大量工作。 - 不得修改或删除
ARCHIVE.md中的历史记录。
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.
- 10d ago First seen · 47 lines · 24 tokens per session scan A 1bb932947b6e
git-snapshot-rollback is a skill published in the GitHub repository cafe3310/public-agent-skills (253 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 24 tokens to every session and 567 once invoked, about $0.0001 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 2026-08-30.
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