overthinkos/python-ml
languages/skills/python-ml/SKILL.md
GPU-accelerated Python ML environment with CUDA, PyTorch, and llama.cpp. No Jupyter server — use as a base for ML workloads or interactive shell. MUST be invoked before building, deploying, configuring, or troubleshooting the python-ml box.
development
Updated Jun 22, 2026
$ install --global
skillsauthnpx skillsauth add overthinkos/overthink-plugins python-mlInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Jun 22, 2026, 6:45 AM320.0s1 file scanned
SKILL.md
- name:
- python-ml
- description:
- |
python-ml
GPU-accelerated Python environment with ML libraries — PyTorch, transformers, vLLM, llama.cpp.
Box Properties
| Property | Value | |----------|-------| | Base | nvidia | | Candies | agent-forwarding, python-ml | | Platforms | linux/amd64 | | Registry | ghcr.io/overthinkos |
Candy Composition
The python-ml candy is a Tier 2 environment-owner meta-layer that:
- Owns the pixi.toml (core ML Python environment)
- Composes
llama-cpp(Tier 1 sub-candy) viacandy: [llama-cpp] - Installs vLLM 0.19 wheel via a cmd task (after pixi env is established)
Build order: pixi environment → llama-cpp (binaries) → vLLM 0.19 wheel
Full Candy Stack
fedora→nvidia(CUDA base)pixi→python(transitive)python-ml— ML pixi environment (Tier 2, owns pixi.toml)llama-cpp— llama.cpp binaries (Tier 1, viacandy:field)
Quick Start
charly box build python-ml
charly shell python-ml
# python -c "import torch; print(torch.cuda.is_available())"
Key Candies
/charly-languages:python-ml— ML Python packages via pixi (Tier 2 meta-layer)/charly-jupyter:llama-cpp— llama.cpp binaries (sub-candy)/charly-distros:cuda— GPU support (via nvidia base)
Related Boxes
/charly-distros:nvidia— parent (GPU without ML packages)/charly-jupyter:jupyter-ml— adds JupyterLab + collaboration + MCP + unsloth on top of ML stack/charly-jupyter:jupyter— legacy Jupyter with ML stack (monolithic)/charly-jupyter:unsloth-studio— fine-tuning UI with similar ML stack
Verification
After charly box build:
charly shell python-ml -c "python -c 'import torch; print(torch.cuda.is_available())'"— CUDA OKcharly shell python-ml -c "python -c 'import vllm; print(vllm.__version__)'"— vLLM OKcharly shell python-ml -c "ls ~/llama.cpp/llama-quantize"— llama.cpp OK
When to Use This Skill
MUST be invoked when the task involves the python-ml box, ML training environments, or GPU-accelerated Python. Invoke this skill BEFORE reading source code or launching Explore agents.
Related
/charly-image:image— image family umbrella (candy:image entries — those carryingbase:/from:— incharly.yml, build/validate/inspect/list)/charly-build:build— the embedded build vocabulary (distros, builders, init-systems)
Related Skills
overthinkos/plugin
tools
VerifiedTrustedCommunity
Use when authoring or modifying a charly PLUGIN — a candy with a `plugin:` block that contributes Providers (verbs/kinds/deploy-targets/steps/builders/commands), its own CUE schema, builtin (compiled-in) or external (out-of-tree git repo). Covers the unified Provider model, the per-plugin CUE-schema contract (single source → Go params for dev + schema-over-Describe RPC for runtime), the SDK, and the loader.
SKILL.mdUpdated Jun 22, 2026
overthinkos/cue
tools
VerifiedTrustedCommunity
The CUE data-validation / configuration CLI (cue), pinned to v0.16.1. Use when working with the cue candy, installing the cue binary into a box or onto a target:local dev host, or running the offline schema-vendoring pipeline that feeds charly's egress validation.
SKILL.mdUpdated Jun 16, 2026
overthinkos/egress
tools
VerifiedTrustedCommunity
CUE EGRESS validation — validating (and, where it adds value, generating) the config files charly WRITES to a system BEFORE the bytes hit disk. MUST be invoked before working on charly/egress.go, the vendored schemas under candy/plugin-egress/egress-schemas/vendor/, the ValidateEgress / registerVendoredEgressKind path, the offline `task cue:vendor` pipeline, or adding an egress schema for any written artifact (cloud-init, k8s manifests, traefik routes, runtime config, install ledger, systemd/quadlet units, ssh_config, libvirt XML).
SKILL.mdUpdated Jun 16, 2026
overthinkos/check-k8s
tools
VerifiedTrustedCommunity
Kubernetes cluster-probe declarative check verb — the `kube:` check verb (nodes, pods, ingress, storage class, addon health, apply/delete, and arbitrary resource GETs) served out-of-process by the candy/plugin-kube plugin (vendored client-go; no external kubectl required).
SKILL.mdUpdated Jun 14, 2026