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 3 minute
49.409 skill-uri
- anpassenKlotzkette/claude-fuer-deutsches-rechtFür /anpassen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Technik-Governance.AlteleFără avertismente★ 1,8 K↓ —
- oracleLeoYeAI/agent-master-skillsUse the @steipete/oracle CLI to bundle a prompt plus the right files and get a second-model review (API or browser) for debugging, refactors, design checks, or cross-validation.DesignFără avertismente★ 2,2 K↓ —
- lernplanKlotzkette/claude-fuer-deutsches-rechtFür Staatsexamen-Lernplan: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- bgbKlotzkette/claude-fuer-deutsches-rechtFür BGB: Verhandlung, Vergleich und Eskalation: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Betreuungsrecht. Route: bgb.AlteleFără avertismente★ 1,8 K↓ —
- consulting-agbKlotzkette/claude-fuer-deutsches-rechtFür Consulting AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- jobs-to-be-donewondelai/skillsDiscover what customers truly need by analyzing the "job" they hire your product to do. Use when the user mentions "customer discovery", "why customers churn", "what job does this solve", "competing against luck", "product-market fit", "switching behavior", "milkshake moment", or "functional vs emotional jobs". Also trigger when investigating why users choose competitors, designing features around real customer needs, or reframing a value proposition. Covers JTBD interviews, competition analysis, and jobs-oriented roadmaps. For product positioning, see obviously-awesome. For rapid validation, see design-sprint. For non-leading interview technique, see mom-test.TestareFără avertismente★ 2,6 K↓ —Apare și în 2 alte depozite
- 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↓ —
- scenario-video-assemblyscenario-labs/skillsUse when generated clips must become a finished video on Scenario via MCP: cutting a shot list together, laying a timeline, concatenating with transitions, overlaying a logo or title card, adding a music bed or voiceover, burning in or exporting captions and subtitles, trimming and splitting, or producing vertical and square variants of one master. Keywords: edit, assemble, stitch, concat, compositor, timeline, layers, overlay, captions, SRT, ad, UGC, social cut.MediaFără avertismente★ 1,9 K↓ —
- bulk-rnaseqK-Dense-AI/scientific-agent-skillsPrepares bulk RNA-seq FASTQ, Salmon, STAR or featureCounts output for gene-level differential expression. Covers nf-core/rnaseq and standalone quantification, biological replication, strandedness, reference provenance, validated count assembly and a PyDESeq2 handoff. Use for FASTQ-to-counts analysis, nf-core/rnaseq configuration, STAR/Salmon quantification, or building a counts matrix for DESeq2. For single-cell data use scanpy; for statistical fitting alone use pydeseq2.ȘtiințăFără avertismente★ 56 K↓ —
- portfolio-strategycbrock84/headcountDecides where capital and attention go across business lines, products, and markets — what to fund, hold, harvest, or exit, and on what evidence. Use this to allocate budget across businesses, evaluate whether a product line should continue, decide whether to exit one, structure a portfolio review, or when several initiatives compete for the same limited investment.FinanțeFără avertismente★ 2,6 K↓ —
- polarsK-Dense-AI/scientific-agent-skillsHigh-performance DataFrame library for Python ETL, analytics, and pandas migration. It supports expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.DateFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- 007sickn33/agentic-awesome-skillsSecurity audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.SecuritateFără avertismente★ 49,1 K↓ —
- manage-skills-hubqufei1993/skills-hubUse this skill whenever an Agent needs to query, find, install, deploy, update, tag, adopt, diagnose, or safely remove Skills Hub content, including natural-language requests to manage Skills for Codex, Claude Code, Cursor, or another Agent. Always use the Skills Hub CLI workflow instead of editing Skill directories or the database.DevOpsFără avertismente★ 1,9 K↓ —
- cloud-logging-finopsgoogle/skillsAudits Cloud Logging costs for a Google Cloud project: the charges for log entries written to log buckets, the services, log streams and severities that drive them, and the log sinks that route them. Reconciles Cloud Billing export costs with Cloud Monitoring volume metrics, and generates a FinOps report with charts and copy-paste exclusion filters. Use when auditing Cloud Logging spend, finding logging waste, identifying top logging contributors, generating log cost reduction reports, or creating log sink exclusion filters. Don't use for querying log entries (use cloud-logging-query-generation), configuring Cloud Monitoring alerts, or querying metrics/traces.OficialRedactareFără avertismente★ 21,8 K↓ —
- scenario-veoscenario-labs/skillsUse when generating or extending video with Google Veo models on Scenario via MCP: text-to-video, image-to-video from a first frame, first and last frame transitions, reference-to-video (R2V) with asset or style reference images, native audio with dialogue, sound effects, and ambience, negative prompts, seeded reruns, extending a 16:9 clip, or choosing a quality, fast, or lite tier. Keywords: Veo 3.1, Veo 3.1 Fast, Veo 3.1 Lite, Extend Video, Google, T2V, I2V, V2V, 720p, 1080p.MediaFără avertismente★ 1,9 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↓ —
- intakeKlotzkette/claude-fuer-deutsches-rechtFür Intake und Eingangstriage: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- nature-figureYuan1z0825/nature-skillsCreate, revise, audit, and export manuscript scientific figures in Python or R. Use for 论文配图、科研绘图、多面板图 and submission-ready plots, or explicitly requested AI-generated graphical abstracts and mechanism schematics. Not for interactive dashboards, data cleaning, or statistics-only analysis.ȘtiințăFără avertismente★ 52 K↓ —
- cloud-monitoring-alert-configurationNougoogle/skillsConfigures Cloud Monitoring alerting policies using Terraform and PromQL across Cloud Run, Google Kubernetes Engine (GKE), Compute Engine, AI Hypercomputer reservations, Vertex AI Agent Engine, and generic Google Cloud resources. Use when creating, reviewing, migrating, or deduplicating Terraform alerting policies for latency, traffic, error rates, saturation, host or reservation maintenance, GPU XID insights, or AI agent telemetry. Don't use for standalone PromQL query authoring without alerting, log querying, or billing cost audits.OficialDevOpsFără avertismente★ 21,8 K↓ —
- scenario-team-adminscenario-labs/skillsUse when administering a Scenario team from an agent through MCP: restricting which models a team or project can run (model access control, allowlist, blocklist), inviting or removing team and project members, changing roles, capping a member's Creative Unit spend, creating or deleting projects, auditing API keys and their roles or scopes, or attributing consumption per user or model. Keywords: governance, model control, consumption cap, spend limit, API key hygiene, team admin, enterprise.InginerieFără avertismente★ 1,9 K↓ —
- unslop-uiNousickn33/agentic-awesome-skillsAudit and redesign AI-generated interfaces with product-specific visual direction, structured design passes, and optional snapshots or story video.DesignFără avertismente★ 49,1 K↓ —
- weaviatesickn33/agentic-awesome-skillsSearch, query, inspect, create, and import data into Weaviate vector database collections using bundled adapted scripts and references.DateFără avertismente★ 49,1 K↓ —
- google-maps-scraperMahanaicoach/google-maps-scraper-kitGoogle Maps scraper for lead generation. Turns a business type and a place into a clean CSV of local businesses by driving the kit's own Google Maps engine, running locally (with Python and a headless Chrome, or in Docker) as a REST API on localhost:8080. Returns 8 lead fields by default (name, phone, email, website, category, address, rating and review count), plus social profiles by default (Instagram, Facebook, LinkedIn, TikTok, YouTube, X; `--no-socials` skips them), row filters such as businesses without a website, or all 36 raw fields. Use when the user wants a lead list, "a list of [businesses] in [place]", local business data, contact enrichment for places (emails, phones, socials), or a whole-city run past Google's ~120 results per search. Do not use for scraping Instagram, TikTok, YouTube, X or any other social media platform directly.BrowserFără avertismente★ 2,2 K↓ —
- frame-a-proposalinkeep/open-knowledgeFrame a new design proposal (RFC-shape) under proposals/ — problem before solution, named beneficiary and observable change, real alternatives, honest drawbacks, and a live open-questions backlog. Read when asked to frame a proposal, write an RFC, propose a design, pitch a change, draft a PRD-style design doc, or open a design proposal for review. Do NOT read to record a decision after it is accepted (use record-a-decision), to write an implementation spec (use write-a-spec), to write a postmortem (use write-a-postmortem), or to review or critique an existing design (use review-a-design).DesignFără avertismente★ 4,8 K↓ —
ai-devkit-setup
codeaholicguy/ai-devkit
AlteleActualizat ieri
De la autor
AI DevKit · Check local AI DevKit readiness and run setup only when status shows onboarding or harness integration gaps.
Instalare
npx skills add codeaholicguy/ai-devkit --skill ai-devkit-setup -a claude-code
Se instalează în .claude/skills/ai-devkit-setup/ · 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 instrucțiuniFolosește rețeauaLicență: APACHE-2.0
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 89
Securitate100
Proveniență79
Întreținere100
Licență100
Adopție52
Fișiere (2)
- SKILL.md
- agents/openai.yaml