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 agentmods add skills/sisibeloved/cpython-optimize-skill/cinderx-env-cleannpx skills add sisibeloved/cpython-optimize-skill --skill cinderx-env-cleangit clone --depth 1 https://github.com/sisibeloved/cpython-optimize-skillWrote 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/sisibeloved/cpython-optimize-skill/cinderx-env-clean)<a href="https://agentmods.dev/skills/sisibeloved/cpython-optimize-skill/cinderx-env-clean"><img src="https://agentmods.dev/badge/skills/sisibeloved/cpython-optimize-skill/cinderx-env-clean.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 | $0.00052 | $0.00484 |
| Opus 5 | $0.00026 | $0.00242 |
| Sonnet 5 | $0.00010 | $0.00097 |
| Haiku 4.5 | $0.00005 | $0.00048 |
Grade A, and why
cinderx-env-clean 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 5d 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
CinderX Env Clean
只清理被破坏的 CPython/CinderX 实验环境。先由 cinderx-env-validate 证明不可复用，再执行清理。
清理对象
- 错误
editable install、残留 wheel、旧cinderx.__file__指向。 - 旧
build 目录、CMake/Ninja 产物、错版本 generated headers。 - 污染
venv、错误PYTHONPATH、坏LD_LIBRARY_PATH。 - 错误 Docker 容器、挂错源码的 bind mount、残留
pyperformance env。 patchlevel.h、SOABI、解释器微版本不一致造成的错版本头文件。- AArch64 RuntimeTests 中
/opt/python314构建为共享/PIC Python，导致_Python_LIBRARY_RELEASE指向libpython3.14.so、_PyThreadState_GetCurrent@plt、TLSDESC或DetectsThreadStateOffset失败。
保留对象
默认保留 cache：pip cache、Docker layer、可复用源码 checkout、历史 run.json / speedup.json / 日志。要删除 cache 必须说明原因。
反问 Gate
- 清理会删除非 cache 产物、历史日志、
run.json、core dump、HIR/jit.log 或用户工作目录时，必须询问。 - 同一 host/workspace 下有多个可疑环境且无法确认目标环境时，询问要清理哪一个。
- 无法判断应清理重建还是保留现场继续取证时，询问用户优先级。
输出
- 清理前环境指纹
- 清理了什么
- 保留了什么 cache
- 清理后需要调用的 bootstrap 步骤
不要用重新安装掩盖环境漂移；漂移原因要写清楚。
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.
- 5d ago First seen · 37 lines · 52 tokens per session scan A 405ddcb410d6
cinderx-env-clean is a skill published in the GitHub repository sisibeloved/cpython-optimize-skill (2 stars, last pushed 7d ago), licensed MIT. It adds 52 tokens to every session and 484 once invoked, about $0.0003 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 2026-08-31.
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