Scan training data for benchmark contamination — n-gram overlap, embedding similarity, and exact canary detection against 60+ evaluation datasets.
原文语言:英语
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SkillsMP 已收集 mkurman/zorai 中的 483 个 Skill。打开任一 Skill 可查看来源和详情。
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Scan training data for benchmark contamination — n-gram overlap, embedding similarity, and exact canary detection against 60+ evaluation datasets.
原文语言:英语
Audit dataset bias across protected attributes — demographic parity, equalized odds, representation gaps, and intersectional bias. Reports actionable gaps with per-group metrics.
原文语言:英语
Generate structured datasheets for datasets (Gebru et al. "Datasheets for Datasets" format) — purpose, composition, collection process, preprocessing, limitations, and licensing.
原文语言:英语
Compare two dataset versions and produce a structured diff — what was added, removed, changed, with row counts and field-level change summaries.
原文语言:英语
Hands-on implementation template and API reference for writing, tuning, debugging, and benchmarking Triton GPU kernels. Covers the full triton.language API surface, autotuning patterns, profiling workflows, and production integration.
原文语言:英语
Hands-on implementation template and API reference for writing, tuning, debugging, and benchmarking Triton GPU kernels. Covers the full triton.language API surface, autotuning patterns, profiling workflows, and production integration.
原文语言:英语
Tencent AngelSlim — accessible, comprehensive, and efficient toolkit for large model compression. Quantization (FP8/INT4/NVFP4/1.25-bit), pruning, speculative decoding (Eagle3), and diffusion model compression.
原文语言:英语
DistilQwen2.5 — Alibaba's industrial practices for training distilled open lightweight language models. Knowledge distillation from Qwen2.5 72B into smaller 0.5B-7B models.
原文语言:英语
Intel Neural Compressor — SOTA low-bit LLM quantization (INT8/FP8/INT4/NVFP4), sparsity, pruning, and distillation for PyTorch, TensorFlow, and ONNX Runtime.
原文语言:英语
Knowledge distillation techniques for model compression: logit-level, feature-level, and relation-based distillation. KD-Lib library and practical workflows for training student models.
原文语言:英语
Model compression techniques: pruning, knowledge distillation, and quantization. Covers compression ordering (P-KD-Q), tools, and evaluation metrics.
原文语言:英语
Structured and unstructured model pruning: weight pruning, attention head pruning, layer removal, and neural architecture search for efficient LLMs.
原文语言:英语
NVIDIA Model Optimizer — quantization, pruning, distillation, and speculative decoding for accelerating LLMs, diffusion models, and vision models on NVIDIA GPUs.
原文语言:英语
Use when the user wants a morning brief, start-of-day summary, routine-ready daily digest, or a concise operational overview combining calendar, tasks, PRs, and issues.
原文语言:英语
Use when the user wants an inbox cleanup summary, morning email triage, scheduled inbox sweep, or a concise action-oriented Gmail digest delivered to chat.
原文语言:英语
Use when the user wants a pull request review queue summary, morning PR check, stale PR scan, or a routine-ready GitHub triage summary delivered to chat.
原文语言:英语
Use when reviewing recent tamux goal run outputs, closure markers, ledgers, or evidence bundles to judge whether completion is credible or to identify remaining uncertainty.
原文语言:英语
Clean, normalize, and prepare raw datasets for analysis or ML. Covers missing value handling, deduplication, outlier treatment, type normalization, categorical encoding, and transformation logging.
原文语言:英语
Create reproducible train/validation/test splits with stratification, leakage prevention, and distribution validation. Covers random, stratified, grouped, and time-series split strategies.
原文语言:英语
Version datasets with checksums, manifests, and semantic versioning. Covers DVC integration, provenance tracking, release tagging, and reproducible dataset lifecycles.
原文语言:英语
Compute and analyze embeddings for dataset quality, distribution comparison, semantic deduplication, diversity measurement, and similarity-based filtering. Covers sentence-transformers, embedding space diagnostics, and 2025-2026 literature techniques (NeMo…
原文语言:英语
Load, stream, process, and publish datasets with the HuggingFace datasets library. Covers Apache Arrow-backed streaming for large datasets, map/filter operations, train/val/test splitting, interleaving, concatenation, and pushing to the Hub.
原文语言:英语
Audit label quality using confident learning (Northcutt et al.), cross-validation noise detection, and per-class error analysis. Identifies mislabeled examples for review.
原文语言:英语
Use locally-hosted LLMs (vLLM/SGLang) for dataset filtering, quality scoring, rewriting, labeling, and synthetic data generation. Covers LLM-as-judge scoring, structured output filtering, batch inference pipelines, and 2025-2026 techniques (DataRater,…
原文语言:英语
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
原文语言:英语
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
原文语言:英语
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
原文语言:英语
Use when implementing any feature or bugfix, before writing implementation code
原文语言:英语
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
原文语言:英语
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
原文语言:英语
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
原文语言:英语
Use when creating new skills, editing existing skills, or verifying skills work before deployment
原文语言:英语
Audit and improve web accessibility following WCAG 2.1 guidelines. Use when asked to "improve accessibility", "a11y audit", "WCAG compliance", "screen reader support", "keyboard navigation", or "make accessible".
原文语言:英语
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include…
原文语言:英语
Apply modern web development best practices for security, compatibility, and code quality. Use when asked to "apply best practices", "security audit", "modernize code", "code quality review", or "check for vulnerabilities".
原文语言:英语
Deep code optimization audit using parallel specialist agents. Each agent hunts for performance anti-patterns, inefficiencies, and suboptimal code using pattern-based detection (Grep/Glob) WITHOUT reading the full source code first — avoiding anchoring bias…
原文语言:英语
Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS", "optimize INP", "page experience optimization", or "fix layout shifts".
原文语言:英语
Create, debug, and iterate on GSD extensions (TypeScript modules that add tools, commands, event hooks, custom UI, and providers to GSD). Use when asked to build an extension, add a tool the LLM can call, register a slash command, hook into GSD events, create…
原文语言:英语
Expert guidance for creating, writing, building, and refining GSD skills. Use when working with SKILL.md files, authoring new skills, improving existing skills, or understanding skill structure and best practices.
原文语言:英语
Install and configure the GitHub CLI (gh) for AI agent environments where gh may not be pre-installed and git remotes use local proxies instead of github.com. Provides auto-install script with SHA256 verification and GITHUB_TOKEN auth with anonymous fallback.…
原文语言:英语