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.
48.168 de skill-uri din 2.325 de depozite · actualizat acum 18 ore
48.168 de skill-uri
- usus-modernusKlotzkette/claude-fuer-deutsches-rechtFür Usus Modernus: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- app-store-optimizationcbrock84/headcountImproves visibility and conversion in the App Store and Google Play — metadata, keywords, screenshots, ratings, and the listing experience that turns an impression into an install. Use this to audit or optimize an app listing, plan a launch listing, diagnose poor install conversion, or improve store search visibility.MarketingFără avertismente★ 2,5 K↓ —
- interview-mepedrohcgs/claude-code-my-workflowInteractive interview that formalizes a fuzzy research idea into a structured spec (RQ, hypotheses, identification, data needs, empirical strategy). Use when user says "interview me", "help me think through this idea", "I have a half-baked idea", "formalize this into a project", "walk me through framing a study". Multi-turn Q&A; saves spec to disk. NOT for lit review (`/lit-review`) or ideation from scratch (`/research-ideation`).PlanificareFără avertismente★ 1,7 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↓ —
- exploratory-data-analysisK-Dense-AI/scientific-agent-skillsPerforms bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain formats are reference-only and unknown formats fail closed.DateFără avertismente★ 55,5 K↓ —
- seedance-car-vehicleLearnPrompt/awesome-seedanceThe machine has to stay one machine while the camera does all the work. Lock the vehicle part by part, then fill the runtime with a numbered cut list that moves the camera every second. Use when the user wants a Seedance 2.5 / 2.0 video prompt for this kind of clip (Cars and vehicles at speed; 中文触发词: 汽车与载具速度片, 汽车, 赛车, 摩托, 载具), or asks how published cases of this type were prompted. Read references/cases.md before drafting.MediaFără avertismente★ 2,4 K↓ —
- gutachten-uebungKlotzkette/claude-fuer-deutsches-rechtFür Gutachtenstil-Übung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- wear-widgetsandroid/skillsCreate, migrate, update, and verify Wear OS widgets using Glance Wear and Remote Compose in an Android project. Use this skill when implementing GlanceWearWidget, GlanceWearWidgetService, WearWidgetDocument, Remote Compose UI primitives (RemoteColumn, RemoteRow, RemoteBox, RemoteText, RemoteImage, RemoteButton), local state with rememberMutableRemoteInt and valueChange, click actions with pendingIntentAction, widget provider XML containers (SMALL and LARGE), rectangular widget picker PNG previews, or migrating legacy ProtoLayout TileService tiles to Wear OS widgets. Don't use for mobile home screen AppWidgetProvider or GlanceAppWidget implementations, watch face complications, or full-screen Wear OS activities.OficialDesignFără avertismente★ 10,1 K↓ —
- market-research-reportsK-Dense-AI/scientific-agent-skillsBuilds evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.ȘtiințăFără avertismente★ 55,5 K↓ —
- uncertainty-and-unitsK-Dense-AI/scientific-agent-skillsTracks physical units and propagates measurement uncertainty in scientific calculations using pint and uncertainties. Use for unit conversion and dimensional checking, GUM uncertainty budgets, Type A and Type B evaluation, coverage factors and expanded uncertainty, Monte Carlo propagation, significant-figure and plus-minus reporting, error propagation through curve fits, CODATA constants, auditing Python code for stripped units or broken uncertainty propagation, and order-of-magnitude plausibility checks using dimensionless groups (Reynolds, Peclet, Damkohler, Knudsen, Biot, Womersley), characteristic scales such as diffusion time or Debye length, and observed magnitude ranges. Trigger on "is this number physically reasonable", "sanity check these units", "what regime is this flow in", or a result that looks off by orders of magnitude.ȘtiințăFără avertismente★ 55,5 K↓ —
- ai-search-optimizationcbrock84/headcountOptimizes for AI assistants and AI-generated answers — being retrievable, being cited, and being represented accurately when a model answers on your behalf. Use this when traffic is shifting from links to AI answers, when a brand is misrepresented or absent in AI responses, when planning content for retrieval rather than ranking, or when deciding how AI search changes an existing SEO program.MarketingFără avertismente★ 2,5 K↓ —
- markitdownK-Dense-AI/scientific-agent-skillsConverts heterogeneous documents and selected URIs to Markdown with Microsoft MarkItDown for text analysis, search, and LLM/RAG ingestion. Covers safe local conversion, streams, Office/PDF/data formats, batch workflows, plugins, vision OCR, Azure extraction, and the official MCP server.DevOpsFără avertismente★ 55,5 K↓ —
- waerme-quartierKlotzkette/claude-fuer-deutsches-rechtFür Wärme, Quartier und Fernwärme: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- stable-baselines3K-Dense-AI/scientific-agent-skillsTrains 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.AlteleFără avertismente★ 55,5 K↓ —
- mini-context-graphgithub/awesome-copilotA persistent, compounding knowledge base combining Karpathy's LLM Wiki pattern with a structured knowledge graph. Ingest documents once — the LLM writes wiki pages, extracts entities/relations into the graph, and stores raw content for evidence retrieval. Knowledge accumulates and cross-references; it is never re-derived from scratch.ProductivitateFără avertismente★ 40,6 K↓ —
- pkpd-modelingK-Dense-AI/scientific-agent-skillsPharmacokinetic and pharmacodynamic modelling and simulation - non-compartmental analysis, compartmental and population PK, PK/PD and exposure-response, TMDD, PBPK orientation, bioequivalence, allometric scaling and first-in-human dose, drug interaction prediction, and Bayesian therapeutic drug monitoring. Use when analysing concentration-time data, deriving exposure metrics, fitting PK or PD models, or evaluating dosing regimens. Triggers include "pharmacokinetics", "pharmacodynamics", "PK/PD", "NCA", "non-compartmental", "AUC", "Cmax", "lambda z", "half-life", "clearance", "volume of distribution", "compartmental model", "population PK", "popPK", "NONMEM", "nlmixr2", "Pharmpy", "Monolix", "exposure-response", "Emax", "EC50", "indirect response", "effect compartment", "TMDD", "PBPK", "bioequivalence", "RSABE", "ABEL", "allometric scaling", "first-in-human", "MABEL", "drug-drug interaction", "DDI", "ICH M12", "concentration-QTc", "therapeutic drug monitoring", "MIPD", and "dosing regimen".AlteleFără avertismente★ 55,5 K↓ —
- industriekundenKlotzkette/claude-fuer-deutsches-rechtFür Industriekunden — Sonderregelungen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 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★ 10,1 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★ 10,1 K↓ —
- statistical-powerK-Dense-AI/scientific-agent-skillsCalculates sample sizes and statistical power for study planning. Applies when someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for complex designs — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Also handles requests that only mention an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-analysis.TestareFără avertismente★ 55,5 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★ 10,1 K↓ —
- 13c-metabolic-fluxK-Dense-AI/scientific-agent-skillsEstimates intracellular metabolic fluxes from steady-state carbon-13 isotope-tracing measurements using validated atom maps, mfapy isotope simulation, constrained multistart fitting, and flux-profile diagnostics. Use for 13C-MFA, carbon tracing, mass isotopomer distributions (MDVs/MIDs), positional isotopomers, parallel tracer experiments, and determining whether labeling data constrain a pathway flux. Distinguishes measured-label inference from COBRA flux balance analysis and flags experiments requiring nonstationary MFA.AlteleFără avertismente★ 55,5 K↓ —
- nature-paper-cardYuan1z0825/nature-skillsBuild a structured deep-reading Paper Card for one scientific paper, analysing methods, experiment-to-claim evidence, limitations, and research ideas. Use for 论文精读卡、方法拆解、证据链分析; not full-paper bilingual translation or formal peer review.ȘtiințăFără avertismente★ 51,6 K↓ —
- 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★ 55,5 K↓ —
chief-revenue-officer
cbrock84/headcount
De la autor
An agent organization structured as a company — 15+ departments, 125+ skills, each independently installable, citing the standards and regulators that settle the question. Runs in Claude Code and ChatGPT.
Antetul nu a putut fi citit (invalid YAML: YAMLParseError: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Owns the revenue); afișăm numele folderului.
Instalare
npx skills add cbrock84/headcount --skill chief-revenue-officer -a claude-code
Se instalează în .claude/skills/chief-revenue-officer/ · 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.
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- SKILL.md