pufferlib
No security findings. Scanned 1 time, most recently 2026-10-21.
Second scanner: NVIDIA SkillSpector
The two scanners disagree: Cisco found nothing and SkillSpector says do not install. One of them has a blind spot here; read the skill before trusting either. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Version-aware guidance for PufferLib reinforcement-learning environments, vectorization, policies, PuffeRL training, evaluation, and safe checkpoint review. Covers the native 5.0 build and environment API, published 3.0.0 Gymnasium/PettingZoo adaptation, and a pinned historical 4.0 profile.
- Package
- 16 files, 142 KB
- SKILL.md
- 1779 words, 12+ sections
- Code
- Python (9)
- Allowed tools
ReadBashGrepPython- License
- MIT
- Compatibility
- Bundled CLIs require Python 3.10+ (standard library only). PufferLib 5.0 requires a native C/CUDA toolchain; CPU builds support evaluation, not training. PyPI 3.0.0 declares Python >=3.9 and needs a native source build with NumPy <2 and Gymnasium <=0.29.1. Native dependencies and network access are needed for installation; bundled checks require neither.
SKILL.md covers: PufferLib · Safe defaults · First local checks · Installation and provenance · Published 3.0.0 · Pinned 4.0 source · Environment workflow · 1. Validate the contract · 2. Adapt only after review · 3. Native environments · Vectorization workflow · Policy workflow
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 15 KB |
references/environments.md | doc | 11 KB |
references/integration.md | doc | 9.4 KB |
references/native-5.md | doc | 8.1 KB |
references/policies.md | doc | 7.2 KB |
references/training.md | doc | 13 KB |
references/vectorization.md | doc | 8.7 KB |
scripts/__init__.py | script | 62 B |
scripts/_common.py | script | 6.5 KB |
scripts/benchmark_vectorization.py | script | 8.1 KB |
scripts/env_contract_validator.py | script | 6.7 KB |
scripts/env_template.py | script | 7.1 KB |
scripts/inspect_checkpoint.py | script | 6.9 KB |
scripts/repro_plan.py | script | 5.9 KB |
scripts/train_template.py | script | 10 KB |
scripts/validate_plan.py | script | 18 KB |
External hosts referenced
github.com puffer.ai pypi.org arxiv.org gymnasium.farama.org docs.neptune.ai farama.org openreview.net api.wandb.ai docs.pytorch.org doi.org export.arxiv.org files.pythonhosted.org
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Environment variables referenced
WANDB_API_KEY NEPTUNE_API_TOKEN WANDB_BASE_URL
Package contents recorded 2026-10-22 at commit 593377bb0487. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/K-Dense-AI/scientific-agent-skills
- Raw scan result: skills-pufferlib-scan.json
- Badge for your README:
- Request a re-scan