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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.
45.604 skill-uri din 2.205 depozite · actualizat acum 16 ore
45.604 skill-uri
- mirrord-kafkametalbear-co/mirrordHelps DevOps engineers configure mirrord Operator's Kafka queue splitting feature end-to-end. Generates the MirrordSplitConfig and MirrordPropertyList Kubernetes CRD YAMLs (the current resources; MirrordKafkaTopicsConsumer + MirrordKafkaClientConfig are deprecated but still supported), the matching mirrord.json split_queues section with message_filter and jq_filter, and Helm value guidance. Use this skill whenever the user mentions Kafka splitting with mirrord, MirrordSplitConfig, MirrordPropertyList, MirrordKafkaClientConfig, MirrordKafkaTopicsConsumer, Kafka queue/topic splitting, configuring mirrord with Kafka, Kafka Streams splitting, MSK IAM auth, or troubleshooting Kafka splitting sessions. Also trigger on split_queues with queue_type Kafka, or connecting mirrord to a Kafka cluster. This is a Team/Enterprise feature of mirrord.DevOpsFără avertismente★ 5,4 K↓ —
- ppt-analysisOpenSenseNova/SenseNova-SkillsPPT (.pptx/.ppt) 全量解析。覆盖:所有 slide 文本/表格/图表提取、嵌入图片 caption、纯图片 slide 渲染识别、数据标签提取。DocumenteFără avertismente★ 5,9 K↓ —
- pivot-table-cross-analysisOpenSenseNova/SenseNova-Skills利用交叉表与热力图对分类数据进行多维度占比分析,适用于奖项分布、绩效评估或市场占有率等结构化数据的清洗与可视化。AlteleFără avertismente★ 5,9 K↓ —
- beylagrafana/skillsAuto-instrument an application's HTTP / gRPC / DB traffic with Grafana Beyla eBPF — no code changes, no SDK, no restart. Covers requirements (Linux 5.8+ with BTF, CAP_SYS_ADMIN, host PID), language matrix (Go / Java / Python / Ruby / Node / .NET / Rust / C++ / PHP), Docker + Helm + DaemonSet install, port- / process- / Kubernetes-metadata discovery, OTLP traces + Prometheus metrics export, routes decorator (cardinality control), trace sampling, and Grafana Cloud via Alloy. Use when adding observability to a service you can't recompile, instrumenting a closed-source binary, getting RED metrics + spans onto Tempo/Mimir without touching the app, or rolling Beyla as a cluster-wide DaemonSet — even when the user says "zero-code APM", "instrument legacy app", "trace this binary", "eBPF observability", or "no SDK" without naming Beyla.OficialDevOpsFără avertismente★ 290↓ —
- boltzaipoch/open-scienceStructure prediction for protein, nucleic-acid, and small-molecule complexes with Boltz-2 (Passaro & Wohlwend et al. 2025, github.com/jwohlwend/boltz). Reach for this skill to validate designed binders against a target, to co-fold a protein with a SMILES or CCD ligand, or to get an open-source AlphaFold3 alternative with optional binding-affinity prediction.ȘtiințăFără avertismente★ 5,4 K↓ —
- outlier-detection-and-quality-assessmentOpenSenseNova/SenseNova-Skills执行全面的异常值检测与数据质量评估,利用 IQR 方法识别异常值并结合偏度、峰度分析数据分布特征,适用于非正态分布数据的预处理阶段。AlteleFără avertismente★ 5,9 K↓ —
- formatted-export-with-parquetOpenSenseNova/SenseNova-Skills从多Sheet Excel文件中识别指定条件的记录,并将筛选结果以整行标红格式导出为Excel文件,适用于数据清洗、条件筛选与可视化标记场景。DocumenteFără avertismente★ 5,9 K↓ —
- humanizeepoko77-ai/im-not-aiAI가 쓴 한글 텍스트를 자연스럽게 윤문하는 진입 명령. humanize-korean 파이프라인을 shim 의 route_hint 가 정한 경로(light 1콜 · standard 2콜 · heavy 3+콜)로 실행하고 `--strict`면 heavy 고정. 트리거 — "/humanize".RedactareFără avertismente★ 6,2 K↓ —
- time-series-and-categorical-analysisOpenSenseNova/SenseNova-Skills对时间序列或分类数据进行多维度趋势分析、百分比清洗、绩效分级建模与预测,并生成高分辨率的可视化综合报告,适用于业务指标监控与预测场景。AlteleFără avertismente★ 5,9 K↓ —
- mcp-builderanthropics/skillsGuide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).OficialInginerieFără avertismente★ 183,6 K↓ —Apare și în 10 alte depozite
- openrlhf-trainingOrchestra-Research/AI-Research-SKILLsHigh-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.PlanificareFără avertismente★ 13,9 K↓ —
- get-prompt-from-imagewuyoscar/GPT-Image2-SkillAnalyze user-provided reference images and reverse-engineer high-fidelity AI image-generation prompts. Use when the user asks to recreate, imitate, reverse-engineer, or extract prompts from photographs, illustrations, 3D renders, products, characters, landscapes, typography, logos, posters, or other visual references. Do not use for requests that only require OCR or an ordinary image description.MediaFără avertismente★ 5,9 K↓ —
- excel-smart-analysis-and-cleaningOpenSenseNova/SenseNova-Skills对多 Sheet Excel 进行智能清洗、跨表核对与可视化分析。。DocumenteFără avertismente★ 5,9 K↓ —
- dynamic-percentage-and-large-file-analysisOpenSenseNova/SenseNova-Skills根据文件行数动态切换大文件处理策略(Parquet转换),通过逐行扫描或列匹配提取关键指标并计算占比、均值等统计量,最终输出结构化Excel报告及可视化图表。DocumenteFără avertismente★ 5,9 K↓ —
- vueantfu/skillsVue 3 Composition API, script setup macros, reactivity system, and built-in components. Use when writing Vue SFCs, defineProps/defineEmits/defineModel, watchers, or using Transition/Teleport/Suspense/KeepAlive.RedactareFără avertismente★ 6 K↓ —
- humanize-scanepoko77-ai/im-not-ai한글 글에 AI 티가 얼마나 있는지 재고, 실제로 고치면 어떻게 되는지 표본으로 보여주는 정찰 스킬. 실측 판별력 상위 6개만 본다. 워크스페이스·진단·게이트·서브에이전트 없이 이 대화 안에서 끝낸다(파일 0개, 서브에이전트 0회). 손볼 게 많다고 나오면 전수 윤문은 humanize-korean(=/humanize)으로 넘긴다. 트리거 — "이 글 AI 같아?", "AI 티 있나 봐줘", "스캔해줘", "윤문 돌릴 값어치 있나", "AI 티 점수", "quick humanize", "/humanize-scan".RedactareFără avertismente★ 6,2 K↓ —
- alerting-irmgrafana/skillsConfigure Grafana Alerting, Incident Response Management (IRM), and SLOs end-to-end — provisions Grafana-managed and data-source-managed alert rules, contact points (Slack/PagerDuty/email/webhook), notification policies with hierarchical matchers, silences, mute timings, on-call schedules and escalation chains, incident-management integrations, and SLOs with multi-window burn-rate alerts. Use when configuring alerts, debugging notification routing, setting up on-call rotations, declaring or managing incidents, defining SLOs, provisioning alerting via YAML or API, picking matchers for a notification policy, building a PagerDuty/Slack webhook receiver, or troubleshooting why an alert isn't firing — even when the user says "page me on errors", "alert me when X happens", "route this to the platform team", or "set up an SLO" without naming Alerting or IRM.OficialInginerieFără avertismente★ 290↓ —
- whisperOrchestra-Research/AI-Research-SKILLsOpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.MediaFără avertismente★ 13,9 K↓ —
- fleet-managementgrafana/skillsManage a fleet of Grafana Alloy collectors with Fleet Management — author Alloy pipelines once, target them via attribute matchers (`env="production"`, regex `region=~"us-.*"`), push remotely via OpAMP without restarting collectors. Covers pipeline create / update / matcher RPCs, collector attribute API, `remotecfg` bootstrap block (standalone + Helm), pre-deploy `alloy fmt` validation, the local Alloy UI at port 12345 for component health, and post-deploy `REMOTE_CONFIG_STATUS_APPLIED` verification. Use when standing up a Cloud Alloy fleet, pushing a config change to 200 collectors, hunting why one collector shows `REMOTE_CONFIG_STATUS_FAILED`, validating River syntax before saving, or wiring `discovery.kubernetes` → `prometheus.remote_write` — even when the user says "configure Alloy", "remote config the collectors", "push pipeline", "OpAMP", "collector is unhealthy", or "manage agent config centrally" without naming Fleet Management.OficialDevOpsFără avertismente★ 290↓ —
- esmfold2aipoch/open-scienceBiohub ESMFold2 / ESMFold2-Fast all-atom co-folding (Candido et al. 2026, github.com/Biohub/esm). Single-sequence and MSA modes; protein, DNA, RNA, ligand (CCD/SMILES), modified residues. FoldBench Ab-Ag 50-55%, PPI 70-77% DockQ-pass. Also covers the ESMC-{300M,600M,6B} protein language models from the same release: masked-LM logits, hidden states, mutation scoring, contact prediction, and the SAE interpretability head. MIT-licensed weights on HuggingFace org `biohub`. Use this skill when: (1) Predicting complex structures with single-sequence input, (2) Validating designed binders with ESMFold2-Fast, (3) Running ESMFold2 with MSA input, (4) Getting ESMC embeddings or per-residue mutation scores, (5) Choosing kernel backend and sampling-step settings for paper-faithful throughput.ȘtiințăFără avertismente★ 5,4 K↓ —
- test-value-evidencedotnet/skillsAssess tests for an identified code or test change, feature, PR or commit. USE FOR: review changed behavior or regression tests, prove pre-fix/missing behavior is detected, revision-bound red-green evidence. Polyglot. DO NOT USE without an identified change: hypothetical mutations or general suite blind spots (test-gap-analysis). Also exclude per-test readiness/A-F grades (grade-tests), coverage (coverage-analysis), new suites (code-testing), or mutation engines.TestareFără avertismente★ 5,7 K↓ —
- excel-bar-chart-visualizationOpenSenseNova/SenseNova-Skills读取多工作表Excel文件,自动处理合并单元格与数据清洗,进行交叉分组统计并生成带总计行的结果表,最后绘制支持中英文字体的美化柱状图,适用于多维度数据汇总与可视化分析。DocumenteFără avertismente★ 5,9 K↓ —
- commit-koepoko77-ai/im-not-aiAI(Claude 등)가 제안한 한글 커밋 메시지의 사무적·번역투 어휘("~을 수행함", "~을 진행함", "~적 개선을 실시함" 등)를 실제 개발자가 쓰는 자연스러운 한국어 커밋 메시지로 다듬는 스킬. humanize-korean과 달리 산문 문단이 아니라 1~2줄짜리 커밋 메시지 register에 특화되어 진단·청킹 없이 단일 콜로 즉시 처리한다. 트리거 — "커밋 메시지 자연스럽게", "커밋 메시지 다듬어줘", "이 커밋 메시지 AI 티 나", "commit message 한국어로 자연스럽게", "커밋 메시지 어색해", "커밋 메시지 사람처럼".InginerieFără avertismente★ 6,2 K↓ —
- grouped-statisticsOpenSenseNova/SenseNova-Skills对多 Sheet 的 Excel 文件进行行数统计、数据合并与前向填充。DocumenteFără avertismente★ 5,9 K↓ —
vercel-react-best-practices
zebbern/claude-code-guide
De la autor
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Instalare
npx skills add zebbern/claude-code-guide --skill vercel-react-best-practices -a claude-code
Se instalează în .claude/skills/vercel-react-best-practices/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Verificări de siguranță pe SKILL.md
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De ce 91
Fișiere (63)
- AGENTS.md
- README.md
- SKILL.md
- metadata.json
- rules/_sections.md
- rules/_template.md
- rules/advanced-event-handler-refs.md
- rules/advanced-init-once.md
- rules/advanced-use-latest.md
- rules/async-api-routes.md
- rules/async-defer-await.md
- rules/async-dependencies.md
- încă 51