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.
git clone --depth 1 https://github.com/cpuguy96/StepCOVNetWrote 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/rules/cpuguy96/stepcovnet/python-environment)<a href="https://agentmods.dev/rules/cpuguy96/stepcovnet/python-environment"><img src="https://agentmods.dev/badge/rules/cpuguy96/stepcovnet/python-environment/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/rules/cpuguy96/stepcovnet/python-environment"><img src="https://agentmods.dev/badge/rules/cpuguy96/stepcovnet/python-environment.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 | $0.00605 | $0.00605 |
| Opus 5.5 | $0.00242 | $0.00242 |
| Sonnet 5.5 | $0.00121 | $0.00121 |
| Haiku 4.5 | $0.00060 | $0.00060 |
Grade A, and why
python-environment 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 1mo 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python environment
Windows development model
StepCOVNet on Windows uses two environments:
| Layer | Where | Purpose |
|---|---|---|
| Windows venv | venv\ beside the clone |
pytest, lint, CPU scripts — any clone path |
| WSL Linux venv | default $HOME/stepcovnet-venv-wsl in WSL |
TensorFlow/PyTorch CUDA — not tied to a Windows username path |
GPU scripts that call wsl_gpu.maybe_dispatch_for_training re-exec in WSL and translate the current clone path automatically. Do not hardcode /mnt/c/Users/... or C:\Users\....
Override WSL venv location: WSL_VENV or STEPCOVNET_WSL_PYTHON. Opt out of WSL dispatch: STEPCOVNET_NO_WSL=1.
STEPCOVNET_NO_WSL=1 silently forces Windows CPU — it does not fall back to GPU. Never set it for training, decode, or MERT extraction (measured ~3.5× slower on an AR decode); reserve it for CPU-only debugging where you intend to skip CUDA.
Decision
| Workload | Where | Executable |
|---|---|---|
| pytest, lint, edits, CPU scripts | Native Windows | venv\Scripts\python.exe (from repo root) |
Training, MERT --device=cuda, any CUDA on Windows |
WSL | "${STEPCOVNET_WSL_PYTHON:-$HOME/stepcovnet-venv-wsl/bin/python}" |
Do not use bare python, pytest, or pip from PATH.
Windows venv (CPU)
Run from repository root:
venv\Scripts\python.exe -m pytest ...
venv\Scripts\python.exe -m pip ...
WSL GPU (summary)
Full command templates: wsl-gpu-stepcovnet skill.
Shared shell vars: scripts/wsl_common.sh. Bootstrap: scripts/wsl_ensure_env.sh. Always source scripts/wsl_gpu_env.sh before TensorFlow import. Set STEPCOVNET_IN_WSL=1. If already inside WSL, do not nest another wsl call.
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.
- 1mo ago First seen · 48 lines · 605 tokens per session scan A 1c0ef1e42b1c
python-environment is a cursor rule published in the GitHub repository cpuguy96/StepCOVNet (22 stars, last pushed 5d ago), licensed Apache-2.0. It adds 605 tokens to every session, about $0.0024 per session on Opus 5.5. 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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