Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
41.606 skill-uri din 1.950 de depozite · actualizat acum 6 minute
41.606 skill-uri
- miles-rl-trainingOrchestra-Research/AI-Research-SKILLsProvides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training large MoE models with FP8/INT4, needing train-inference alignment, or requiring speculative RL for maximum throughput.PlanificareFără avertismente★ 13,9 K↓ —
- pyvene-interventionsOrchestra-Research/AI-Research-SKILLsProvides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange intervention training, or testing causal hypotheses about model behavior.TestareFără avertismente★ 13,9 K↓ —
- axolotlOrchestra-Research/AI-Research-SKILLsExpert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal supportAlteleFără avertismente★ 13,9 K↓ —
- dart-collect-coverageflutter/agent-pluginsCollect coverage using the coverage packge and create an LCOV reportOficialAlteleFără avertismente★ 3,1 K↓ —
- mamba-architectureOrchestra-Research/AI-Research-SKILLsState-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.PlanificareFără avertismente★ 13,9 K↓ —
- alipay-uploadNoudreammis/social-auto-upload使用 social-auto-upload 的 `sau alipay` 登录支付宝生活号并发布视频。Use when 用户要向支付宝生活号发布视频或检查创作账号状态。AlteleFără avertismente★ 15,8 K↓ —
- huggingface-tokenizersOrchestra-Research/AI-Research-SKILLsFast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.ȘtiințăFără avertismente★ 13,9 K↓ —
- golden-rssyusufkaraaslan/Skill_SeekersUse when testing the rss golden buildTestareFără avertismente★ 15,2 K↓ —
- dart-use-ffigenflutter/agent-pluginsGuide agents to use `package:ffigen` to automatically generate FFI bindings instead of writing them manually. Use this skill when a task involves writing new FFI bindings, extending C/Objective-C/Swift integrations, or replacing hand-crafted `dart:ffi` setups.OficialRedactareFără avertismente★ 3,1 K↓ —
- dart-use-path-packageflutter/agent-pluginsCross-platform file and directory path manipulation, segment splitting, extension extraction, and context conversion using `package:path` and `package:file`. Use when writing, inspecting, joining, splitting, or refactoring file paths, directory names, or extensions, or replacing raw string path operations (`.split('/')`, `'$dir/$file'`, `.endsWith('.ext')`, `.replaceAll('\\', '/')`). Don't use for HTTP network URI routing, database query strings, or non-path string processing.OficialDateFără avertismente★ 3,1 K↓ —
- supabase-postgres-best-practicessupabase/agent-skillsPostgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pg_cron, pgmq), vector/semantic search (pgvector), and restoring dumps (pg_restore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.OficialDateFără avertismente★ 2,9 K↓ —Apare și în 1 alt depozit
- gguf-quantizationOrchestra-Research/AI-Research-SKILLsGGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.DevOpsFără avertismente★ 13,9 K↓ —
- social-auto-uploadNoudreammis/social-auto-upload为 social-auto-upload 提供总入口，按平台和内容类型选择对应发布流程。Use when 用户要在本仓库支持的平台发布视频、文章或图文，或需要把内容分发到多个指定平台。AlteleFără avertismente★ 15,8 K↓ —
- golden-epubyusufkaraaslan/Skill_SeekersUse when testing the epub golden buildTestareFără avertismente★ 15,2 K↓ —
- ara-research-managerOrchestra-Research/AI-Research-SKILLsRecords research provenance as a post-task epilogue, scanning conversation history at the end of a coding or research session to extract decisions, experiments, dead ends, claims, heuristics, and pivots, and writing them into the ara/ directory with user-vs-AI provenance tags. Use as a session epilogue — never during execution — to maintain a faithful, auditable trace of how a research project actually evolved.ȘtiințăFără avertismente★ 13,9 K↓ —
- gptqOrchestra-Research/AI-Research-SKILLsPost-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.DevOpsFără avertismente★ 13,9 K↓ —
- phoenix-observabilityOrchestra-Research/AI-Research-SKILLsOpen-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.DevOpsFără avertismente★ 13,9 K↓ —
- verl-rl-trainingOrchestra-Research/AI-Research-SKILLsProvides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.DevOpsFără avertismente★ 13,9 K↓ —
- azure-enterprise-infra-plannermicrosoft/skillsArchitect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 2 alte depozite
- azure-monitor-opentelemetry-pymicrosoft/skillsAzure Monitor OpenTelemetry Distro for Python. Use for one-line Application Insights setup with auto-instrumentation. Triggers: "azure-monitor-opentelemetry", "configure_azure_monitor", "Application Insights", "OpenTelemetry distro", "auto-instrumentation".OficialDevOpsFără avertismente★ 3,1 K↓ —
- azure-ai-voicelive-javamicrosoft/skillsAzure AI VoiceLive SDK for Java. Real-time bidirectional voice conversations with AI assistants using WebSocket. Triggers: "VoiceLiveClient java", "voice assistant java", "real-time voice java", "audio streaming java", "voice activity detection java".OficialDevOpsFără avertismente★ 3,1 K↓ —
- cost-estimationmicrosoft/skillsForecast Azure spend and price planned resources or workloads. WHEN: "forecast Azure spending", "project next month cost", "compare forecast to my planning target", "how much will Azure cost", "estimate VM cost", "compare storage tiers", "compare Azure regions", "retail price", "EA rate card", "negotiated pricesheet". DO NOT USE FOR: configured budget health or alerts, bill analysis, cost spikes, rightsizing, or commitments.OficialDevOpsFără avertismente★ 3,1 K↓ —Apare și în 1 alt depozit
- ray-dataOrchestra-Research/AI-Research-SKILLsScalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.DateFără avertismente★ 13,9 K↓ —Apare și în 1 alt depozit
- golden-html-multiyusufkaraaslan/Skill_SeekersUse when testing the multi-file html buildTestareFără avertismente★ 15,2 K↓ —
cherry-studio-feedback
CherryHQ/cherry-studio
DesignActualizat acum 18 ore
De la autor
Use when Cherry Studio 用户希望报告、提交或整理 BUG、UI/UX 问题或功能建议，但未明确要求创建 GitHub Issue。
Instalare
npx skills add CherryHQ/cherry-studio --skill cherry-studio-feedback -a claude-code
Se instalează în .claude/skills/cherry-studio-feedback/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (AGPL-3.0) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
La ce are acces
Doar instrucțiuniNu am văzut acces la rețeaLicență: AGPL-3.0
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