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 lovstudio/skills --skill checkpointgit clone --depth 1 https://github.com/lovstudio/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/lovstudio/skills/checkpoint)<a href="https://agentmods.dev/skills/lovstudio/skills/checkpoint"><img src="https://agentmods.dev/badge/skills/lovstudio/skills/checkpoint.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.00822 |
| Opus 5 | $0.00019 | $0.00411 |
| Sonnet 5 | $0.00008 | $0.00164 |
| Haiku 4.5 | $0.00004 | $0.00082 |
Grade A, and why
lov-checkpoint 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 today.
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
项目存档 · Project Checkpoint
根据当前 Git 差异和历史记录保存项目里程碑及后续事项。
Triggers
Activate when
- “根据当前 Git 差异和历史记录保存项目里程碑及后续事项。”
- “Create a project checkpoint.”
Do not activate when
- 只是查询本 Skill 的说明，或请求与上述结果无关的任务；不执行实际业务操作。
- 用户仅要预览或审查时，不进入修改、提交或发布分支。
Execution boundary
自然语言请求即可触发；无需旧 slash 路径、参数插值或指定助手。明确解析当前请求中的 项目、目标文件、选项与输出位置；用当前宿主实际提供的文件、搜索、CLI 和浏览器能力。 项目依赖版本与外部 API 在执行时核实，不能假设示例是现行配置。随包脚本从 Skill 根解析， 业务文件从目标项目根解析。先读当前状态，保护已有未提交内容与其他任务的暂存区。 分析、预览请求保持只读；修改、提交、推送、部署和发布各依当前请求的明确范围执行。 不绕过保护、自动发送消息、强制结束用户进程或抢前台。失败保留可诊断原始错误。
Workflow
-
读取 Git 状态、暂存区、最近历史、.checkpoint_log 与项目指定记录文件。旧 Claude Code 记录可作为兼容输入，写新记录时不伪造任何宿主署名。
-
确定上次检查点到当前的真实变化，首次运行采用存在的提交范围。记录里程碑、验证证据、未解决事项和下一步，不凭修改时间断言文档过期。
-
在请求范围内修正与实现矛盾的 README 或配置说明，不重写仍有效内容；版本和 CHANGELOG 保持事实一致。
-
向 .checkpoint_log 安全追加 JSONL，记录时间、项目、分支、上个哈希、变化与验证结果；项目记录默认放检查点文档，不把每次日志塞进全局 Agent 指令。
-
用户要求检查点提交时仅暂存已核验的本次文件，检查最终暂存集合并执行正常 hooks；未授权提交时交付记录。报告日志与提交各自真实状态，重复运行避免空重复记录。
Composition
执行前读取 能力组合，按明确制品交接相邻能力。
Runtime context (shared)
运行前读取本包 skill.yaml 与 Profile 合同。优先级为当前请求、
项目上下文、本 Skill records、共享 preferences、brand/user Profile、安全默认值。
只读取声明字段；没有专用运行时的宿主可使用 scripts/profile_store.py 读取共享 Profile。
配置缺失只问影响结果的一个问题。用户明确要求长期保存的值通过该脚本原子写入，
报告实际路径；不保存推断、凭据或其他任务的资料。
What ships with it
12 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.
- cases/cases.json 653 B
- CHANGELOG.md 285 B
- LICENSE 1.0 KB
- pricing-card.yaml 425 B
- README.md 1.0 KB
- references/skill-composition.md 854 B
- references/user-profile.md 2.7 KB
- scripts/profile_store.py 8.3 KB runs code
- scripts/validate_skill.py 26 KB runs code
- skill-card.md 1.1 KB
- skill-card.yaml 1.5 KB
- skill.yaml 2.2 KB
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.
- today First seen · 66 lines · 38 tokens per session scan A e9fbe130c017
lov-checkpoint is a skill published in the GitHub repository lovstudio/skills (64 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 822 once invoked, about $0.0002 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 2026-09-07.
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