Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/nebius/nebius-physical-ainpx agentmods add skills/nebius/nebius-physical-ai/pre-pr-validationWrote 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/nebius/nebius-physical-ai/pre-pr-validation)<a href="https://agentmods.dev/skills/nebius/nebius-physical-ai/pre-pr-validation"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/pre-pr-validation/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/nebius/nebius-physical-ai/pre-pr-validation"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/pre-pr-validation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00037 | $0.02440 |
| Opus 5 | $0.00018 | $0.01220 |
| Sonnet 5 | $0.00007 | $0.00488 |
| Haiku 4.5 | $0.00004 | $0.00244 |
Grade A, and why
pre-pr-validation 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 yesterday.
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 — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-PR Validation
Every pull request runs lint and docs drift, unit and browser tests, security
regressions, harness guardrails, secret scanning, and confidentiality scanning.
Security regression / security-regression requires both the scanner comparison
and hostile-input runtime tests on every PR, merge queue candidate, and main push.
Its workflow has no path filters. Verify actual required contexts in branch
protection before claiming merge enforcement. image-security-scan also applies
to Docker and image-security changes.
All of them are reproducible locally. Run them in cost order so the cheap ones catch the common mistakes before you spend minutes on the full suite.
For how the test suite itself behaves — markers, hermetic fixtures, parallel
runs, live-infra expectations — use skills/atomic/testing-conventions/SKILL.md.
This skill is the gate map.
Use The Repo Virtualenv
npa/.venv/bin/python (Python 3.12). Never bare python. The make targets
default PYTHON to bare python and cd into npa/ first, so pass an
absolute path:
make test PYTHON=/workspace/npa/.venv/bin/python
The Ladder
# 1. Lint — seconds. This matches CI and `make lint` across all of npa/.
npa/.venv/bin/python -m ruff check npa
# 2. Onboarding smoke — ~20s.
make test-smoke PYTHON=/workspace/npa/.venv/bin/python
# 3. Guardrails — ~50s, ~2000 static contract assertions. Highest signal per second.
npa/.venv/bin/python -m pytest npa/tests/guardrails -q
# 4. The tests for what you touched — seconds to a minute.
npa/.venv/bin/python -m pytest npa/tests/cli/test_<tool>_cli.py -q
# 5. Full unit suite — minutes. This is the PR gate.
make test PYTHON=/workspace/npa/.venv/bin/python
# 6. Docs drift — ~1-2 min. Only when CLI commands or options changed.
bash scripts/build_docs.sh --check
# 7. Confidentiality, diff-scoped — seconds.
npa/.venv/bin/python -m npa.guardrails.confidentiality \
--repo-root . --diff-range origin/main..HEAD --built-in-nebius-infra
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.
- yesterday Changed · +59 lines 3033ad5638d8
- 9d ago First seen · 147 lines · 37 tokens per session scan A 2090369a24d8
pre-pr-validation is a skill published in the GitHub repository nebius/nebius-physical-ai (27 stars, last pushed today), licensed Apache-2.0. It adds 37 tokens to every session and 2,440 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 2026-08-30.
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