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Found 2,405 Skills
Generates a self-contained Python experiment client that uses the ddtrace.llmobs SDK. Emits either a runnable .py script or a Jupyter .ipynb notebook matching the canonical DataDog reference notebook style. Use when the user says "generate Python experiment", "write an SDK experiment", "create a ddtrace experiment", "Python notebook experiment", "use the LLM Obs SDK", or has `ddtrace` installed and wants idiomatic SDK code.
Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions.
Manage multiple Alibaba Cloud accounts and batch-export Security Center (SAS) baseline and vulnerability reports via the aliyun CLI and Python scripts. Supports account list refresh, enable/disable, concurrent batch export of cloud platform configuration check (baselineCspm), system baseline risk (exportHcWarning), Linux/Windows/application/emergency vulnerability results across all managed accounts. Use this skill when users need to manage SAS multi-account settings, export baseline or vulnerability compliance data, or merge multi-account security reports into a single file.
Debug Hermes TUI slash commands: Python, gateway, Ink UI.
Install Holoscan SDK Python wheel via pip into a venv. Use for Python installs; not for native C++/apt or Conda installs.
Decide where files live in an ML experimentation project: reusable code in `src/<pkg>/`, one `# %%` script per experiment in `experiments/`, design notes + index in `journal/`, reports in `reports/`, agent-only probes in `scratch/`, narrative digest in `overview/summary.md`. Owns the layout, the file-creation rules (one file per experiment, ask before editing), and the jupytext `# %%` script convention. Never imposes `data/` — the user owns that. TRIGGER — any of: - Starting a new ML project / scaffolding a workspace. - About to create the first experiment file in a project. - About to create `src/<pkg>/data.py` / `features.py` / `pipeline.py` / `evaluate.py` for the first time. - About to write a `.ipynb` for experimentation — redirect to a `# %%` script under `experiments/`. - User asks where something should live, how to organize the project, or how to set up the workspace. - About to add a new experiment iteration — decide new file vs edit existing (ask the user). SKIP when: the file is clearly part of an already-populated module (e.g., adding a function to existing `features.py`); pure refactor inside a single existing file; pipeline declaration mechanics (`build-ml-pipeline`); evaluation mechanics (`evaluate-ml-pipeline`); skore symbol lookup (`python-api`). HOW TO USE: **first run the Detection table** below — if any signal matches, glue to existing conventions (do not rename or move folders). If no signal matches, scaffold the default layout. **Emit the Pre-flight checklist as visible text and read the Stop conditions before any file is created or edited.** Use templates in `templates/`; copy and adapt, do not rewrite from scratch.
Python >= 3.11 coding standards. Use when writing Python code. Requires type hints, return types, Google-style docstrings, trailing commas, explicit kwargs, StrEnum with auto(), dataclasses, pytest-style tests.
Analyze local scientific CSV, TXT, XLS, or XLSX data; recommend publication-informed charts and Chinese scientific palettes; freeze a reproducible plan; and automate editable figures through a callable local Origin/OriginPro installation on physical Windows 10/11 x64. Use for beginner “drop in a file and draw it” requests; XPS, XRD, XAS, PL/TRPL, DSC, NMR, FTIR/IR, UV-Vis, electrochemistry, medical/AI evidence, distribution, relationship, error-bar, bar, stacked, pie, Sankey, radar, heatmap, or verified 3D workflows; project-local Python setup; palette selection; and OPJU/PNG/PDF/TIF verification. Do not use on macOS, Linux, WSL, Wine/CrossOver, Parallels, or other VMs; to install or modify Origin; to redistribute reference images; or to claim an unverified Origin route.
Hunt Insecure Deserialization — Java gadget chains (ysoserial), PHP object injection (phpggc), Python pickle RCE, .NET BinaryFormatter, Ruby Marshal.load, JNDI/Log4Shell. RCE via deserialization is almost always Critical. Use when target runs Java, PHP serialization, Python pickle, .NET, or Ruby on Rails.
Configure environment via mise [env] SSoT. TRIGGERS - mise env, mise.toml, environment variables, centralize config, Python venv, mise templates, hub-spoke architecture, monorepo structure, subfolder mise.toml.
Complete survival analysis library in Python. Handles right-censored data, Kaplan-Meier curves, and Cox regression. Standard for clinical trial analysis and epidemiology.
Use when implementing well-scoped Python tasks with clear requirements, writing unit tests, and producing documented code for senior-developer review.