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.
49.395 de skill-uri din 2.375 de depozite · actualizat acum 38 de secunde
49.395 de skill-uri
- pnpmLeoYeAI/agent-master-skillsNode.js package manager with strict dependency resolution. Use when running pnpm specific commands, configuring workspaces, or managing dependencies with catalogs, patches, or overrides.PlanificareFără avertismente★ 2,2 K↓ —Apare și în 2 alte depozite
- gke-ai-troubleshooting-tpu-vbar-oomgoogle/skillsDiagnoses and prevents vbar_control_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar_control_agent crashes, memory cgroup OOMs in serial console logs, tpu-device-plugin metrics checksum corruption errors, or custom TPU metrics collection conflicts on GKE TPU v6e nodes. Don't use for general non-TPU container OOM troubleshooting or standard GKE node lifecycle operations.OficialProductivitateFără avertismente★ 21,8 K↓ —
- display-glasses-with-jetpack-compose-glimmerandroid/skillsProvides guidelines for developing projected Android XR apps for display glasses using the Jetpack Compose Glimmer UI toolkit. Covers Glimmer design principles, workflows, and interaction models for the glasses form factor. Use this skill to build an Android XR Augmented Experience app with Jetpack Compose Glimmer. Don't use for audio-only AI glasses without a display, non-glasses Android XR headsets (spatial panels or 3D volumes with Jetpack Compose for XR), or phone and tablet Material 3 UIs.OficialDesignFără avertismente★ 10,3 K↓ —
- auto-empirical-research-skillsbrycewang-stanford/Auto-Empirical-Research-SkillsRoute empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows, or an end-to-end run from raw data all the way to a finished Word (.docx) manuscript, without reading the entire repository at once.ȘtiințăFără avertismente★ 4,9 K↓ —
- google-cloud-solution-multi-agent-securitygoogle/skillsDesigns, deploys, and secures Google Cloud Agent Gateway solutions. Use when the user needs to configure multi-agent security, ingress (CLIENT_TO_AGENT), or egress (AGENT_TO_ANYWHERE) patterns involving Model Armor, IAP, and Agent Registry. Don't use for general Cloud Load Balancing or basic VPC setup not related to Agent Gateways.OficialSecuritateFără avertismente★ 21,8 K↓ —
- litert-lmandroid/skillsBuilds an Android app that runs an open text LLM on the device, on the CPU or the GPU, with the LiteRT-LM Kotlin API (com.google.ai.edge.litertlm:litertlm-android). Use this skill when creating a chat, summarization, or extraction feature with a .litertlm model from Hugging Face litert-community (Gemma, Qwen, Llama, Phi), including the Gradle dependency, the GPU manifest entries, getting the model file onto the device, Engine initialization off the main thread, a streamed multi-turn Conversation with sendMessageAsync, and the AndroidViewModel and Compose screen. Don't use for running .tflite vision, audio, or embedding models with the CompiledModel API, for image or audio input, tool calling, or NPU backends, or for converting models.OficialMediaFără avertismente★ 10,3 K↓ —
- gke-ai-troubleshooting-jobset-interruptiongoogle/skillsDiagnoses GKE JobSet interruptions, restarts, and preemptions for AI/ML training workloads autonomously. Use when troubleshooting JobSet restart loops, spot VM preemptions, node readiness failures, host VM issues, or coordinator worker crashes. Don't use for general GKE cluster creation, basic workload deployment, or non-JobSet application issues.OficialDevOpsFără avertismente★ 21,8 K↓ —
- nuxtLeoYeAI/agent-master-skillsNuxt full-stack Vue framework with SSR, auto-imports, and file-based routing. Use when working with Nuxt apps, server routes, useFetch, middleware, or hybrid rendering.MediaFără avertismente★ 2,2 K↓ —Apare și în 1 alt depozit
- cloud-monitoring-chart-generationgoogle/skillsGenerates Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos on Google Cloud from resolved PromQL or ListTimeSeries queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery or TimeSeriesFilter datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus or ListTimeSeries queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.OficialDesignFără avertismente★ 21,8 K↓ —
- agent-platform-skill-registrygoogle/skillsInteract with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills. Use this skill to enable agents to register functionality or discover new capabilities.OficialAlteleFără avertismente★ 21,8 K↓ —
- esmK-Dense-AI/scientific-agent-skillsUses the Biohub esm Python SDK for ESM3 protein generation, ESMC embeddings, and ESMFold2 all-atom folding. Applies to local model inference and Biohub hosted clients, including former Forge workflows; distinguishes the separate legacy fair-esm distribution.ȘtiințăFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- cloud-databases-onboardinggoogle/skillsGuides users through discovering their database requirements, recommends a Google Cloud database based on a recommendation matrix, and assists in database creation. Use when a user asks 'What database service should I use?', 'Help me pick a database', or when a user wants to create a new database on Google Cloud. Don't use for general Google Cloud maintenance, managing existing databases, or database migrations.OficialDateFără avertismente★ 21,8 K↓ —
- huashu-prompt-savealchaincyf/huashu-skills自动识别Prompt类型并分类保存（技术/内容/教学/产品/通用）。当用户提到"保存prompt"、"记录prompt"、"整理prompt"时使用。AlteleFără avertismente★ 2,2 K↓ —
- huashu-video-checkalchaincyf/huashu-skills基于MrBeast策略检查视频标题、封面和开头钩子。当用户提到"视频标题"、"封面图"、"点击率"、"CTR"、"观看时长"时使用。MediaFără avertismente★ 2,2 K↓ —
- memoKlotzkette/claude-fuer-deutsches-rechtFür Internes Rechtsgutachten: Gutachten-Gerüst: erstellt Entwurf mit Antrag, Beweis und Anlagen; Ergebnis: Schriftsatz mit Begründungs- und Anlagenlogik.AlteleFără avertismente★ 1,8 K↓ —
- zeitleisteKlotzkette/claude-fuer-deutsches-rechtFür Zeitleiste des Datenschutzvorfalls — minutiöse Rekonstruktion: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- agent-platform-alert-configurationgoogle/skillsConfigures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (such as Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI deployments.OficialSecuritateFără avertismente★ 21,8 K↓ —
- agent-platform-inferencegoogle/skillsConnects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or generate code for calling Gemini or OpenMaaS models, authenticate with GenAI SDK, OpenAI SDK, or legacy Agent Platform SDK, configure base URLs and global/regional endpoints, or troubleshoot 429 Resource Exhausted (DSQ), 400 User Validation, or 404 Not Found errors. Don't use for deploying models to endpoints or for running model evaluations.OficialTestareFără avertismente★ 21,8 K↓ —
- scenario-chatgpt-pet-updatescenario-labs/skillsUse when changing an existing ChatGPT pet or Codex pet sprite sheet with Scenario: fixing a broken row, frame, jump or edge, regenerating one animation state, adding the sixteen look directions to a 1536x1872 v1 sheet, giving the pet a new outfit, color or accessory, renaming it in its pet.json, or checking a pet sheet and previewing it as an animated GIF.MediaFără avertismente★ 1,9 K↓ —
- secops-detection-engineeringgoogle/skillsAuthor, validate, test, and deploy YARA-L 2.0 detection rules and evaluate end-to-end detection coverage gaps in Google SecOps. Use when writing new detection rules, tuning existing rules, validating syntax, testing logic against historical telemetry, or evaluating detection coverage against threat intelligence blogs, CVE disclosures, and Threat Detection Opportunities (TDOs) using synthetic UDM events and long-running coverage analysis. Don't use for alert triage (use secops-triage), deep forensic event reconstruction on infected hosts (use secops-investigate), or case management operations (use secops-cases).OficialSecuritateFără avertismente★ 21,8 K↓ —
- agent-platform-eval-flywheelgoogle/skillsMeasures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when generating synthetic user scenarios, evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing failures, comparing results before and after a fix, or when guidance is needed on Agent Platform eval methodology — including dataset schema, LLM-as-judge scoring, and common failure causes. For fine-tuning, use agent-platform-tuning. For general production deployment, use agent-platform-deploy.OficialDevOpsFără avertismente★ 21,8 K↓ —
- migrate-to-rustgoogle/skillsClones, analyzes, plans, and migrates legacy codebases (C++, Fortran, Java, Python, C, Shell) from a GitHub URL or local directory to a modern, high-performance, deterministic, 100% Safe Rust architecture, tracking live telemetry across every task bucket, test failure/fix cycle, and Profile-Guided Optimization (PGO) stage, and producing a first-person AI storytelling report and interactive HTML infographic. Use when migrating a GitHub repository or local codebase to Rust, porting legacy C++, Fortran, Python, or Java workloads to memory-safe Rust, designing Struct-of-Arrays (SoA) or SIMD Rust architectures, or optimizing Rust ports with LLVM PGO. Don't use for unrelated non-Rust refactoring or single-line syntax questions.OficialTestareFără avertismente★ 21,8 K↓ —
- agent-platform-tuninggoogle/skillsAgent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).OficialDevOpsFără avertismente★ 21,8 K↓ —
- dbt-sf-to-bq-translatorgoogle/skillsTranslates Snowflake dbt SQL models to Standardized BigQuery SQL. Handles SQL compilation, Jinja macro placeholder masking, BigQuery Translation Service migration workflows, AST-based config transformations, explicit type casting, JSON extraction standardization, and deduplication. Use when migrating Snowflake dbt pipelines or models to BigQuery on Google Cloud. Don't use for generic BigQuery queries or non-Snowflake SQL migrations.OficialDateFără avertismente★ 21,8 K↓ —
android-profiler
android/skills
OficialDesignActualizat acum 5 zile
De la autor
Records and analyzes Android performance data and diagnoses performance bottlenecks across user apps, system apps, and system services, even if the user does not explicitly mention profiling or traces. Use when: recording system traces, CPU call stacks, Vulkan GPU/DRM memory, or Java/native heap profiles; analyzing Perfetto traces for UI jank, frame drops, ANRs, or app startup latency issues; investigating CPU bottlenecks, IPC/Binder storms, or thread scheduling stalls; diagnosing battery drain, modem power rails, and kernel wake locks; debugging memory pressure, Low Memory Kills (LMK), OOMs, leaks, and allocation churn; performing A/B baseline trace comparisons to find regressions; executing ad hoc PerfettoSQL queries on Android traces.
Instalare
npx skills add android/skills --skill android-profiler -a claude-code
Se instalează în .claude/skills/android-profiler/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (Personalizată sau neclară) 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: Personalizată sau neclară
Verificări de siguranță pe SKILL.md
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De ce 89
Securitate100
Proveniență100
Întreținere100
Licență45
Adopție63
Fișiere (26)
- SKILL.md
- analysis/analysis_orchestrator.md
- analysis/workflows/perfetto-sql/perfetto_sql.md
- analysis/workflows/perfetto-trace-analysis/perfetto_trace_analysis.md
- analysis/workflows/perfetto-trace-analysis/references/hints/hints_cpu.md
- analysis/workflows/perfetto-trace-analysis/references/hints/hints_graphics.md
- analysis/workflows/perfetto-trace-analysis/references/hints/hints_io.md
- analysis/workflows/perfetto-trace-analysis/references/hints/hints_ipc.md
- analysis/workflows/perfetto-trace-analysis/references/hints/hints_memory.md
- analysis/workflows/perfetto-trace-analysis/references/hints/hints_power.md
- analysis/workflows/perfetto-trace-analysis/references/per_candidate_analysis.md
- analysis/workflows/perfetto-trace-analysis/references/triage.md
- încă 14