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.
47.966 de skill-uri din 2.309 depozite · actualizat acum 11 ore
46.854 de skill-uri
- leasing-agbKlotzkette/claude-fuer-deutsches-rechtFür Leasing AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- retentioncbrock84/headcountDiagnoses and reduces churn — cancellation flows, save offers, failed-payment recovery, at-risk detection, and the product and service causes underneath. Use this when churn is rising or unexplained, to design a cancellation or win-back flow, to recover involuntary churn, to identify at-risk accounts before they leave, or to decide whether a retention problem is a product problem.DesignFără avertismente★ 2,5 K↓ —
- kaltstart-triageKlotzkette/claude-fuer-deutsches-rechtFür Kaltstart Triage: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Arbeitsrecht.AlteleFără avertismente★ 1,8 K↓ —
- hgb-red-teamKlotzkette/claude-fuer-deutsches-rechtFür HGB Red-Team: prüft Ergebnis, Beweislast und Gegenposition; Ergebnis: Gegenprüfung mit Beweis- und Fristencheck.AlteleFără avertismente★ 1,8 K↓ —
- kommandocenterKlotzkette/claude-fuer-deutsches-rechtFür Deal-Kommandocenter — Corporate/M&A: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Corporate-Kanzlei. Route: kommandocenter.AlteleFără avertismente★ 1,8 K↓ —
- pr-lenscoldteadotai/pr-lensWHAT: Draws a code change or part of a codebase as an animated architecture, data-flow or data-model diagram, on its own or in a pull request. WHEN: asked to diagram, visualise or explain a change, a system or a schema change, or when a pull request should carry a diagram. KEYWORDS: PR Lens, diagram, architecture, data flow, data model, schema, ERD, visualise, visualize, pull requestPlanificareFără avertismente★ 2,3 K↓ —Apare și în 1 alt depozit
- energievertraegeKlotzkette/claude-fuer-deutsches-rechtFür Energie-Verträge — Strukturierung und Prüfung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- ai-listeningzhuyansen/new-term-radarCollect what is new in AI in the last 24 hours across X, Hugging Face, GitHub and sitemaps, deduplicated, as one report of names that are starting to surge. Use when the user asks what is new or trending in AI today, wants a daily AI listening report, or needs fresh names of models, products and repositories to feed keyword research. Runs the new-term-radar command line; needs an AISA_API_KEY.ȘtiințăFără avertismente★ 2 K↓ —
- cloud-monitoring-promql-querygoogle/skillsGenerates valid PromQL queries from Cloud Monitoring metric descriptors and resource parameters. Use when asked to create, generate, write, or format PromQL queries, PromQL strings, or PromQL aggregations for Cloud Monitoring metrics and resources. Don't use for raw metric discovery or metric selection.OficialRedactareFără avertismente★ 21,7 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★ 21,7 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★ 21,7 K↓ —
- gke-alert-configurationgoogle/skillsConfigures alerting policies in Terraform for Google Kubernetes Engine (GKE) clusters, workloads, and services using PromQL and Google Cloud Managed Service for Prometheus. Use when writing, analyzing, validating, or deploying Terraform alerting policies to monitor GKE service latency, traffic, error rates using Multi-Window Multi-Burn-Rate SLO alerts, memory saturation, and cluster health such as CrashLoopBackOff and Node NotReady conditions. Don't use for non-GKE compute runtimes such as standalone Compute Engine VMs or standalone Cloud Run services without GKE.OficialDevOpsFără avertismente★ 21,7 K↓ —
- fable-loopSahir619/fable-methodEnd-to-end orchestrated workflow that runs a task the way Fable ran sessions - parallel evidence subagents, one committed plan, surgical execution with an intent gate, adversarial verification agents, honest outcome-first report. Use for non-trivial multi-step tasks when the user says "/fable-loop", "run the fable loop", or "do this the way Fable would". For the rules alone without orchestration, use fable-method; for large multi-phase projects, prefer the GSD workflow and use this inside phases.PlanificareFără avertismente★ 2,3 K↓ —
- fable-judgeSahir619/fable-methodAdversarial verification of finished work. Treats any "done" as a set of claims, then re-runs the claimed verifications, diffs what actually changed, detects weakened tests and false completion claims, and delivers an evidence-based verdict (VERIFIED / VERIFIED WITH CAVEATS / REFUTED). Use after any agent or model claims work is complete - "/fable-judge", "judge this work", "verify what it did", "did that actually work?". Also runs the fable-method trap suite against a skill or model via "/fable-judge suite TARGET".TestareFără avertismente★ 2,3 K↓ —
- fable-domainSahir619/fable-methodDiscuss a domain with the user, research it from real sources, then generate a trusted skill bundle for it - a step-by-step workflow with a flowchart, a domain adapter, a trap fixture, and a smoke eval. Use when the user says "/fable-domain SECTOR", "make a skill for DOMAIN", "add a domain to the fable method", or "give a lesser model Fable's workflow for DOMAIN". The bundle is the deliverable; a workflow without its flowchart, sources, and trap is not done.ȘtiințăFără avertismente★ 2,3 K↓ —
- portaljs-new-portaldatopian/portaljsScaffold a new PortalJS data portal from a brief. Copies the canonical template from examples/portaljs-catalog and substitutes project tokens. Use when starting a brand-new data portal project from scratch.AlteleFără avertismente★ 2,4 K↓ —
- portaljs-connect-ckandatopian/portaljsWire a scaffolded PortalJS portal to a CKAN backend over its API. Generates a tiny server-side fetch client (no runtime dependency) and feeds the /search catalog and /@namespace/slug showcases from CKAN instead of datasets.json. Use when connecting an existing portal to a live CKAN instance instead of a static manifest.InginerieFără avertismente★ 2,4 K↓ —
- portaljs-add-resourcedatopian/portaljsAdd another file (resource) to an EXISTING dataset in a PortalJS portal — a data dictionary, methodology, or an additional data file. Turns a single-file dataset into a multi-resource one; the showcase renders a section per resource. Use when a dataset needs a second file, such as a data dictionary, methodology doc, or an additional period's data.MediaFără avertismente★ 2,4 K↓ —
- portaljs-add-chartdatopian/portaljsAdd a chart (line, bar, area, pie, or scatter) to a dataset's showcase in a PortalJS portal. Installs recharts, writes a reusable Chart component, and renders it in the showcase Views section. Use when visualizing a dataset already registered in datasets.json.MediaFără avertismente★ 2,4 K↓ —
- portaljs-deploydatopian/portaljsDeploy a PortalJS portal to PortalJS Arc — Datopian-managed static hosting on Cloudflare. Builds a static export, uploads it, and returns a live SLUG.arc.portaljs.com URL. One command, one target. Use when a portal is ready to publish or redeploy to a live URL.DevOpsFără avertismente★ 2,4 K↓ —
- agents-best-practicesDenisSergeevitch/agents-best-practicesUse this skill when designing, generating an MVP blueprint for, auditing, troubleshooting, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, record provenance, interactive presentation, user-memory lifecycles, environment-adaptive tools, speculative tool execution, late-bound capabilities, permissions, system prompts, planning, goals, always-on agents and durable runtime, adaptive agent teams, context compaction, memory, skills, MCP/external connectors, public-board communications, realtime voice agents, hardware agents and board deployment, self-refining recursive harnesses, programmable context, continual refinement, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety.DevOpsFără avertismente★ 2,4 K↓ —
- portaljs-add-mapdatopian/portaljsRender a GeoJSON dataset on an interactive Leaflet map in the Views section of a dataset's showcase. Installs react-leaflet and a Map component, then renders the map for the chosen dataset. Use when a dataset's data is geographic and a map view is needed alongside the showcase's default metadata and download.MediaFără avertismente★ 2,4 K↓ —
- release-helperSahir619/fable-methodEnsures configuration and code changes are released correctly. Use PROACTIVELY whenever you edit config.json, change any setting, or fix a configuration bug in this project, so the change reaches production.RedactareFără avertismente★ 2,3 K↓ —
- api-gateway-mcp-servergoogle/skillsConfigures Google Cloud API Gateway to act as a remote Model Context Protocol (MCP) server (Public Preview) that exposes REST APIs as agent tools over HTTP (POST /mcp). Use when migrating OpenAPI 2.0 specs to OpenAPI 3.x for MCP, annotating specs with x-google-api-management.mcp and x-google-mcp-tool, securing tools/list with JWTs or API keys, connecting Google ADK (McpToolset) or Apigee API hub and Agent Registry, or troubleshooting MCP JSON-RPC errors (-32601, -32602, -32000). Do not use for Apigee X proxy bundles, outbound LLM model routing, or GKE Gateway API.OficialInginerieFără avertismente★ 21,7 K↓ —
stable-baselines3
K-Dense-AI/scientific-agent-skills
AlteleActualizat acum 5 zile
De la autor
Trains and evaluates single-agent reinforcement learning with Stable Baselines3 (PPO, SAC, DQN, TD3, DDPG, A2C), Gymnasium custom environments, vectorized rollouts, callbacks, and checkpoint normalization. Applies to reproducible RL experiments, continuous control, discrete actions, and SB3-Contrib recurrent or masked policies.
Instalare
npx skills add K-Dense-AI/scientific-agent-skills --skill stable-baselines3 -a claude-code
Se instalează în .claude/skills/stable-baselines3/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Rulează scripturile incluseFolosește rețeauaLicență: MIT
Verificări de siguranță pe SKILL.md
- Include scripturi pe care nu le-am verificatScăzut
De ce 89
Securitate85
Proveniență95
Întreținere100
Licență100
Adopție73
Fișiere (8)
- SKILL.md
- references/algorithms.md
- references/callbacks.md
- references/custom_environments.md
- references/vectorized_envs.md
- scripts/custom_env_template.py
- scripts/evaluate_agent.py
- scripts/train_rl_agent.py