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/pyperformance-suite-runnpx skills add sisibeloved/cpython-optimize-skill --skill pyperformance-suite-rungit 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/pyperformance-suite-run)<a href="https://agentmods.dev/skills/sisibeloved/cpython-optimize-skill/pyperformance-suite-run"><img src="https://agentmods.dev/badge/skills/sisibeloved/cpython-optimize-skill/pyperformance-suite-run.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 | $0.00042 | $0.01414 |
| Opus 5 | $0.00021 | $0.00707 |
| Sonnet 5 | $0.00008 | $0.00283 |
| Haiku 4.5 | $0.00004 | $0.00141 |
Grade A, and why
pyperformance-suite-run 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 3d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pyperformance Suite Run
负责正式 pyperformance 运行。单 benchmark 调试先用 pyperformance-worker-run。
三类测试边界
- RuntimeTests 是功能测试。
- test_cinderx/lib test 是集成测试。
- pyperformance 是性能测试;正式性能测试前必须说明功能测试和集成测试是否已通过、跳过或仍待验证。
使用场景
- L3 相关子集
- L4 full 全量性能验证
- baseline/candidate 正式对照
- 生成
run.json
规则
- 用
python -m pyperformance run。 - 运行前必须读取
../using-cpython-optimize/references/pyperformance-env-contract.md,先列出 driver env、--inherit-environ、worker env 和 baseline/candidate 差异轴。 - 使用
--affinity前必须读取../using-cpython-optimize/references/pyperformance-affinity-guidance.md,说明它是 CPU 绑核参数;先检查当前可用 CPU,再把用户真实命令中的 affinity 映射到当前环境,不要逐字照抄不可用核号。 - CinderX JIT 口径必须证明真实 worker 启用 JIT:检查 CinderX
.pth、workerpyvenv.cfg/include-system-site-packages或等价PYTHONPATH、worker 内import cinderx/_cinderx、cinderx.__file__、cinderx.get_import_error()和cinderx.is_initialized()。 - 正式非 debug 命令形态必须包含
--affinity、--warmup、-b <benchmark-selector>(subset 时)、-o <result.json>和--inherit-environ。 --affinity必须落在当前nproc/lscpu/taskset -pc $$/ 容器 cpuset 显示的可用 CPU 内;高核号不可用时,重分配可用 CPU 并记录原始 affinity -> 实际 affinity。--inherit-environ至少覆盖代理、LD_LIBRARY_PATH、PYTHONPATH、插件开关和 JIT 关键变量。- 若
validation-skill-routerdeny 了 pyperformance 命令,不要把它当测试失败;先补齐pyperformance-env-contract.md要求的 worker venv /.pth/--inherit-environ/ JIT 初始化证据,再用CPYTHON_OPTIMIZE_HOOK_ACK=1前缀重试同一条正式命令。 - 不能在未完成前置证据时提前加
CPYTHON_OPTIMIZE_HOOK_ACK=1绕过 hook;ACK 只表示已经完成环境契约检查。 - 记录 warmup、loops、CPU affinity、容器线、Python、CinderX commit。
- 正式数据关闭 HIR/JIT dump、
--debug-single-value和临时诊断变量;这些只用于 L2 调试,不进入正式性能结论。 - subset/full 选择必须来自
validation-strategy的晋级理由。 - 文档和报告只写
<benchmark-selector>、<result.json>、<baseline.json>、<candidate.json>等占位,不硬编码具体 pyperformance 用例名或文件名。
命令形态
目标集合正式性能测试:
<env-vars> <python> -m pyperformance run \
--affinity=<cpu-list-or-set> \
--warmup <n> \
-b <benchmark-selector> \
--inherit-environ <comma-separated-env-list> \
-o <result.json>
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.
- 3d ago First seen · 77 lines · 42 tokens per session scan A 09aa28f65d16
pyperformance-suite-run is a skill published in the GitHub repository sisibeloved/cpython-optimize-skill (2 stars, last pushed 5d ago), licensed MIT. It adds 42 tokens to every session and 1,414 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 2026-08-31.
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