14,465 tagged Data and AI, measured the same way as everything else here.
Browse within: cursor-rules 10deep-learning 7machine-learning 7Multi-Agent 6PyTorch 6ai-governance 6meok-ai-labs 6nvidia-gpu 6nvidia-warp 6physics 6Autonomous Agents 5agents-md 5ai-assistant 5aider 5
Skill Claude CodeCodex
Design YAML extraction templates for record types (model, list, set). Use when user says: "design model template", "create item list extraction", "extract items", "deduplicate entities". Trigger: User wants to extract structured records, lists, or deduplicated entities. Skip: User mentions graph, relations, or…
Instructions file CodexOpenCode
AGENTS.md instructions for liustack/modlens, covering project overview (for ai agent), goal, scope, technical approach and code organization.
Plugin Claude Code
Build Vizro dashboards from concept to deployment. Enforces a 2-phase workflow covering requirements, layout design, visualization selection, implementation with Python, and testing.
Skill Claude CodeCodex
Build a Visual Data Dictionary — an interactive qsv viz smart dashboard (a Data Schematic) driven by an LLM-inferred JSON Schema data dictionary, with the dictionary browsable beside the charts. Use when the user asks for a visual data dictionary, a documented dashboard, a dictionary-driven dashboard or Data…
Skill Claude CodeCodex
Use when fitting equations to data with PySR or SymbolicRegression.jl, when a user wants an interpretable formula, symbolic model, scaling law, or empirical relation discovered from numeric data, or when debugging a PySR search that is slow, stuck, or giving poor equations.
Instructions file CodexOpenCode ✓ vendor
AGENTS.md instructions for NVIDIA/Model-Optimizer, covering agent instructions for modelopt, repository orientation, coding guidelines, iterative development and contributing and pr readiness.
Instructions file ✓ vendor
Claude Code instructions for NVIDIA/Model-Optimizer, a project described as: A unified library of SOTA model optimization techniques like quantization, distillation, pruning, neural architecture search, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks like…
Plugin Claude Code ✓ vendor
Skills for Model Optimizer development, quantization, deployment, and evaluation.
Skill Claude CodeCodex ✓ vendor
Deterministic end-to-end driver for day-0 quantized-checkpoint releases — chains PTQ → evaluation → comparison with enforced gates between stages (the evaluation stage deploys the checkpoint itself), and returns a publish decision (ACCEPT / REGRESSION / ANOMALOUS / INFEASIBLE). Use when the user asks to "release a…
Skill Claude CodeCodex ✓ vendor
Triage a failed EAGLE3 pipeline run. Identifies which step failed (data synthesis, hidden state dump, training, or benchmark), diagnoses root cause from logs, and suggests fixes. Use when user reports an EAGLE3 pipeline failure or asks why a specific step failed. Also helps debug new model support issues.
Skill Claude CodeCodex ✓ vendor
Evaluates accuracy of quantized or unquantized LLMs using NeMo Evaluator Launcher (NEL). Triggers on "evaluate model", "benchmark accuracy", "run MMLU", "evaluate quantized model", "run nel". Handles deployment, config generation, and evaluation execution. Not for quantizing models (use ptq), deploying/serving models…
brycewang-stanford/Auto-Empirical-Research-Skills
Plugin Claude Code
Explicit 8-step empirical-analysis pipeline in the traditional Python econometrics stack (pandas + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml). Data cleaning → variable construction → Table 1 → diagnostics → estimation (OLS / IV / DID / RDD / PSM / SCM / DML / Causal Forest) → robustness…
Skill Claude CodeCodex
Configure feedback functions and selectors for TruLens evaluations.
Skill Claude CodeCodex
Instrument LLM apps with TruLens OTEL-based tracing - from setup to debugging and optimization.
Skill Claude CodeCodex
Improve a prompt on the evaluations workbench through a measured loop. Score the baseline first, then duplicate the target column, form a hypothesis from failing rows, edit the copy's prompt draft, run, compare pass rate and cost, and repeat until the numbers hold. Use when the user asks to optimize or improve a…
Agent
After a valid blind comparison, unblind the result and explain why the winner performed better. Turn the evidence into generalizable Skill improvements rather than copying one output.
Skill Claude CodeCodex
Write effective prompts for Jimeng Seedance 2.0 multimodal AI video generation. Use when users want to create video prompts using text, images, videos, and audio inputs with the @ reference system. Covers camera movements, effects replication, video extension, editing, music beat-matching, e-commerce ads, short…
Skill Claude CodeCodex
Chinese-language guidance for writing prompts for Seedance 2.0, an AI video generator that can use text, images, video, and audio.
Command Claude Code
Build the LLM Wiki knowledge graph.
zLanqing/codex-claude-academic-skills
Skill Claude CodeCodex
Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify…
Skill Claude CodeCodex
Use when creating, monitoring, validating, or documenting low-memory Hugging Face Jobs or local runs that quantize split BF16/FP16 GGUF model repos into custom quant GGUF repos with skippy-quantize.
Instructions file GitHub Copilot
Copilot instructions for modelscope/evalscope, a project described as: A streamlined and customizable framework for efficient large model (LLM, VLM, AIGC) evaluation and performance benchmarking.
Instructions file CodexOpenCode
AGENTS.md instructions for modelscope/evalscope, covering agents.md, setup, build, lint, test, docs generation and quick eval.
Skill Claude CodeCodex
LLM evaluation & inference performance testing via the evalscope CLI. Translates natural language requests into evalscope commands for: (1) Model accuracy evaluation — runs 160+ benchmarks against local checkpoints or API endpoints (OpenAI-compatible, Anthropic, LiteLLM); (2) Performance stress testing — TTFT, TPOT…
At most 3 mods per repository are shown here — the rest are on their repository pages: