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.
49.409 skill-uri din 2.375 de depozite · actualizat acum 6 ore
49.409 skill-uri
- scenario-model-trainingscenario-labs/skillsUse when generated assets must keep a consistent style, character, or product look and references stop scaling, or when a user asks to train a custom model through the Scenario MCP, fine-tune a LoRA, clone a voice, curate a training dataset, choose a base model, set epochs and sample prompts, estimate training cost, diagnose a trained model that lost its identity or has one epoch, or generate with a trained model. Keywords: custom model, LoRA, dataset curation, epoch previews.AlteleFără avertismente★ 1,9 K↓ —
- dsh-speed-up-perfNouqufei1993/skills-hub调查性能问题或优化实际测量的用户路径时使用，建立优化前后对照，保留正确性、失败行为和真实运行证据。AlteleFără avertismente★ 1,9 K↓ —
- embedded-payment-keycisco-ai-defense/skill-scannerDemonstrate a credential-shaped payment key embedded in instructionsAlteleFără avertismente★ 2,7 K↓ —
- cs-aeoNouLeoYeAI/agent-master-skillsAnswer Engine Optimization (AEO) specialist agent. Use when content needs to be optimized for citation by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) rather than for traditional search rankings. Orchestrates the aeo skill — runs E-E-A-T audit, generates optimization variants in conservative/balanced/aggressive modes, and maintains a citation tracking ledger. Industry-aware (8 industries with calibrated thresholds). Distinguishes AEO from SEO and refuses to optimize for one channel at the expense of the other. Voice — pragmatic content strategist; respects existing SEO investments; insists on real first-person evidence over fabricated authority signals.FinanțeFără avertismente★ 2,2 K↓ —
- cirqK-Dense-AI/scientific-agent-skillsGoogle quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.DesignFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- oil-uiActualizatoil-oil/oil-ui设计、改进和评审网站、App、后台与组件的界面：探索设计方向、生成多风格同屏对比页，并基于真实截图打磨视觉层级；按请求交付对比页、设计说明、设计稿或可运行界面。只负责设计判断，不用于纯业务逻辑、接口构建、无界面变化的代码整理，或改法已完全明确的日常修改（如改文案、调数量、删指定元素、复用现有样式，哪怕带有“优化”字样）。已安装 oil-ui-pro 时交给 oil-ui-pro。DesignFără avertismente★ 2,7 K↓ —
- what-if-oracleK-Dense-AI/scientific-agent-skillsSupports structured what-if scenario analysis for research planning, experimental contingencies, and scientific project decisions. Explores favorable, reference, adverse, wild-card, contrarian, and second-order scenarios with explicit assumptions, evidence, and decision triggers. Use to stress-test a research plan under uncertainty; scenario narratives do not estimate causal effects or calibrated forecast probabilities.TestareFără avertismente★ 56 K↓ —
- backupLeoYeAI/agent-master-skillsBackup and restore openclaw configuration, skills, commands, and settings. Sync across devices, version control with git, automate backups, and migrate to new machines.InginerieFără avertismente★ 2,2 K↓ —
- depmapK-Dense-AI/scientific-agent-skillsRetrieves and analyzes Cancer Dependency Map (DepMap) release data, including CRISPR Chronos gene effects, cancer model annotations, omics biomarkers, and PRISM drug sensitivity. Supports cancer-selective dependency, co-essentiality, and candidate synthetic-lethality analyses with release-aware identifiers and statistical checks.AlteleFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- clinical-reportsK-Dense-AI/scientific-agent-skillsCreates safety-bounded draft structures and runs local deterministic checks for clinical case, diagnostic, trial, safety, and aggregate research reports. Use only with synthetic, de-identified, or aggregate inputs and verified source-fact manifests; every output requires qualified review.ȘtiințăFără avertismente★ 56 K↓ —
- 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↓ —
- kaltstart-triageKlotzkette/claude-fuer-deutsches-rechtHauptworkflow für Notariatsmitarbeiter: führt Kundenunterlagen bis zur konkreten Urkunden- oder Anmeldevorlage an den Notar. Wählt zwischen Entwurf, Änderung und Vollzug, übernimmt belegte Daten und steuert nur den benötigten Fachskill samt gezielten Rückfragen.AlteleFără avertismente★ 1,8 K↓ —
- blog-taxonomyAgriciDaniel/claude-blogSuggest tags and categories for a blog post from its content, audit a site's tag and category health, and, only after the user approves a shown plan, sync tags and categories to WordPress, Shopify, Ghost, Strapi, or Sanity. suggest and audit are read-only; sync is dry-run by default and never deletes, merges, or edits post content. Use when the user says "tag suggestions", "taxonomy audit", "sync tags", "WordPress tags", "Shopify tags". Not for keyword research (blog-brief) or schema markup (blog-schema).RedactareFără avertismente★ 2,6 K↓ —
- working-with-legacy-codewondelai/skillsSafely change and test untested codebases using Feathers' "Working Effectively with Legacy Code". Use when the user mentions "legacy code", "no tests", "untested codebase", "how do I test this", "seams", "characterization tests", "golden master", "sprout method", "afraid to change this code", "monster method", "dependency breaking", or "inherited a messy codebase". Also trigger when changing code without tests safely, getting a class under test when constructors, statics, or singletons block it, adding features to tangled modules, or planning incremental test coverage for an old codebase. Covers the legacy-code change algorithm, seams, characterization tests, sprout/wrap, and dependency-breaking techniques. For refactoring code that already has tests, see refactoring-patterns. For day-to-day code quality, see clean-code.InginerieFără avertismente★ 2,6 K↓ —Apare și în 2 alte depozite
- pyhealthK-Dense-AI/scientific-agent-skillsBuilds and validates PyHealth clinical machine-learning pipelines for EHR, signals, imaging, and medical codes. Use for PyHealth dataset loading, MIMIC-III/IV, eICU or OMOP prediction tasks, patient-level evaluation, mortality/readmission/length-of-stay modeling, medication recommendation, sleep staging, Trainer checkpoints, and ICD/ATC/NDC/RxNorm mapping.ȘtiințăFără avertismente★ 56 K↓ —Apare și în 1 alt depozit
- high-output-managementwondelai/skillsManage for output using Grove's "High Output Management": a manager's output is their organization's output, raised by high-leverage activities. Use when the user mentions "high output management", "managerial leverage", "one-on-ones", "1:1 agenda", "OKRs", "performance review", "task-relevant maturity", "delegation", "meeting overload", "new manager", "how do I run a 1:1", or "just got promoted to manager". Also trigger when structuring a manager's calendar and meeting cadence, designing team metrics, running planning, coaching delegation, or preparing performance reviews. Covers leverage, production principles, meetings as the medium of management, decisions, OKRs, and task-relevant maturity. For intrinsic motivation, see drive-motivation. For a company operating system, see traction-eos.PlanificareFără avertismente★ 2,6 K↓ —Apare și în 2 alte depozite
- archify-tuningtt-a1i/archifyImprove Archify diagram accuracy, visual quality and complete authoring speed with fewer repairs. Use for generation experiments or evaluating changes to layout, routing, diagnostics, authoring instructions and acceptance rules against actual diagrams and agent traces.AlteleFără avertismente★ 93 K↓ —
- eval-driven-devgithub/awesome-copilotImprove AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.TestareFără avertismente★ 40,8 K↓ —
- huashu-motionalchaincyf/huashu-motionMotion graphics, launch videos and explainers as editable code. A director picks the motion language for your product; you point at frames to change them. 动画、发布片、解说视频，指着画面改。RedactareFără avertismente★ 2,2 K↓ —
- engage-sdk-integrationandroid/skillsHelps developers integrate, debug, and resolve Play Engage SDK implementation issues. Use when adding Engage SDK support, generating publishing code, mapping data classes to entities, or fixing SDK-related errors.OficialInginerieFără avertismente★ 10,3 K↓ —
- sevoLeoYeAI/agent-master-skillsSEVO — Agent 自动研发流水线。从需求定义、架构设计到验证发布全流程自动化。npm install sevo-pipeline 即可使用。AlteleFără avertismente★ 2,2 K↓ —
- foundry-agentic-loopgithub/awesome-copilotBuild agentic solutions on Microsoft Foundry, GitHub and Azure: hosted agents, toolbox tools and skills, Foundry IQ grounding and a React/FastAPI app. Three modes: rapid prototyping in an existing Foundry project; spec-driven development (SDD), where the foundry-agentic-loop-workflow runs Specify, Implement, Verify and Deploy to create the Foundry project and deploy with azd, or one phase runs alone; and Improve, which refines this skill and the workflow from past runs. Use for Agentic Loop requests and canvas actions, or end-to-end agent solutions from architecture to Azure deployment. Not for isolated Azure administration or unrelated UI edits.DevOpsFără avertismente★ 40,8 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↓ —
- 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★ 21,8 K↓ —
monetizing-innovation
wondelai/skills
DesignActualizat alaltăieri
De la autor
Design products and pricing around validated willingness to pay, from Ramanujam & Tacke's "Monetizing Innovation". Use when the user mentions "pricing", "how much should we charge", "willingness to pay", "pricing page", "packaging", "freemium vs free trial", "are we leaving money on the table", "nobody buys at this price", "price increase", or "good-better-best". Also trigger when designing or auditing pricing and packaging, validating willingness to pay before building, segmenting customers by value, or choosing between subscription, usage-based, and freemium models. Covers price-before-product, willingness-to-pay talks, the four failures (feature shock, minivation, hidden gem, undead), leader/filler/killer packaging, and behavioral pricing. For offers and guarantees, see hundred-million-offers. For what customers value, see jobs-to-be-done.
Instalare
npx skills add wondelai/skills --skill monetizing-innovation -a claude-code
Se instalează în .claude/skills/monetizing-innovation/ · 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
Doar instrucțiuniNu am văzut acces la rețeaLicență: MIT
Verificări de siguranță pe SKILL.md
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De ce 89
Securitate100
Proveniență81
Întreținere100
Licență100
Adopție54
Fișiere (6)
- SKILL.md
- references/case-studies.md
- references/four-failures.md
- references/monetization-models.md
- references/packaging-tiers.md
- references/wtp-conversations.md