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.
48.622 de skill-uri din 2.355 de depozite · actualizat acum 18 ore
48.622 de skill-uri
- unpinned-dependencycisco-ai-defense/skill-scannerDemonstrate a package dependency that is not locked to an exact versionAlteleFără avertismente★ 2,7 K↓ —
- torchdrugK-Dense-AI/scientific-agent-skillsBuilds and troubleshoots TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, protein representation learning, and knowledge graph reasoning. Use when code imports torchdrug or needs its datasets, models, tasks, or Engine.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- drawiogithub/awesome-copilotGenerate draw.io diagrams as .drawio files and export to PNG/SVG/PDF with embedded XMLDocumenteFără avertismente★ 40,7 K↓ —
- concealed-actioncisco-ai-defense/skill-scannerConceal an agent action from the user who requested the taskProductivitateFără avertismente★ 2,7 K↓ —
- assured-workloads-basicsNougoogle/skillsProvisions, inspects, updates, and deletes Google Cloud Assured Workloads V1 compliant folders, CMEK settings, Sovereign Controls by Partners, and service usage restrictions. Use when creating, listing, describing, updating, or deleting an Assured Workloads workload for any compliance regime or data boundary (FedRAMP, DoD IL2/IL4/IL5, ITAR, CJIS, Healthcare, Sovereign Controls by Partners, or Regional Data Boundaries). Don't use for brownfield assessments or custom frameworks (use assuredworkloads-environment-assessor or assuredworkloads-frameworks-*), or non-compliant folders.OficialJuridicFără avertismente★ 21,8 K↓ —
- 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★ 2,6 K↓ —
- biopythonK-Dense-AI/scientific-agent-skillsProvides Biopython workflows for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Supports batch processing, custom molecular-biology pipelines, BLAST automation, structure analysis, and motif analysis.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- 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★ 51,7 K↓ —
- scveloK-Dense-AI/scientific-agent-skillsPerforms RNA velocity analysis with scVelo from spliced and unspliced single-cell RNA counts. Fits deterministic or dynamical models, examines gene phase portraits, builds velocity graphs, estimates relative latent time, and ranks velocity-associated genes. Use for directional trajectory hypotheses and kinetic-model diagnostics alongside Scanpy; velocity alone does not establish cell fate or causal drivers.AlteleFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- waypoint-bioK-Dense-AI/scientific-agent-skillsSupports work with Outpost Bio's open microbiome foundation models - the Waypoint checkpoints (Waypoint-6m, Waypoint-45m, Waypoint-170m), the Atlas pretraining corpus, the Compass eight-task benchmark, or the `waypoint` CLI from the `waypoint-bio` package. Covers embedding microbiome samples, fine-tuning on taxonomic abundance data, benchmarking a checkpoint on Compass, pretraining a GPT-2 model on taxonomic abundance profiles, and converting MetaPhlAn, Kraken2, QIIME 2, or MGnify abundance tables into waypoint format.InginerieFără avertismente★ 55,6 K↓ —
- threat-modelingcbrock84/headcountIdentifies what could go wrong in a system before it is built or changed — the assets worth attacking, the entry points, the trust boundaries, and the controls that actually address the realistic threats. Use this when designing a feature or system, when a change touches authentication, data handling, payments, or external input, before a security review, or when deciding which security work is worth doing at all.SecuritateFără avertismente★ 2,6 K↓ —
- fluidsimK-Dense-AI/scientific-agent-skillsPlans, configures, inspects, restarts, and analyzes bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and HPC safety checks. Use for FluidSim solver selection, parameter review, FFT/MPI setup, output diagnostics, or restart compatibility.PlanificareFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- hypogenicK-Dense-AI/scientific-agent-skillsPlans and audits use of ChicagoHAI HypoGeniC/HypoRefine for LLM-assisted hypothesis generation from labeled text datasets. Use for the `hypogenic` package, its task configs, hypothesis banks, or HypoBench datasets—not for manual hypothesis formulation or scientific validation.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- ml-kit-genai-prompt-apiandroid/skillsAnalyzes Android codebases to implement ML Kit GenAI Prompt API. Use this skill to send natural language requests on-device to Gemini Nano, use structured output with Prompt API, implement prefix caching, optimize the current prompt, or apply best practices."OficialInginerieFără avertismente★ 10,2 K↓ —
- rowanK-Dense-AI/scientific-agent-skillsRowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.DevOpsFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- neuropixels-analysisK-Dense-AI/scientific-agent-skillsAnalyzes Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.InginerieFără avertismente★ 55,6 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-cluster-autoscalergoogle/skillsTrigger on mention of GKE cluster autoscaler, node autoscaling, node pool auto-creation / node auto-provisioning. Provides guidance on enabling and optimizing cluster autoscaler, best practices, and troubleshooting issues such as nodes not scaling up or down, zonal stockouts, or capacity buffers. Do not use for ComputeClass-specific YAML generation or priority configuration (defer to gke-compute-classes skill).OficialPlanificareFără avertismente★ 21,8 K↓ —
- matlabK-Dense-AI/scientific-agent-skillsBuilds, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.TestareFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- qiskitK-Dense-AI/scientific-agent-skillsBuilds, simulates, transpiles, and executes quantum circuits with Qiskit and IBM Quantum Runtime. Use for Qiskit 2.x circuits and operators, V2 Sampler or Estimator primitives, target-aware transpilation, local or noisy simulation, IBM QPU execution, Runtime sessions or batches, error mitigation, and Qiskit ecosystem packages.AlteleFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- outbound-prospectingcbrock84/headcountFinds, qualifies, and reaches prospects through cold outreach — list building, qualification criteria, cold email and multi-channel sequences, and the follow-up that actually gets replies. Use this to build a prospect list, write cold outreach, fix a sequence that is not getting responses, define qualification criteria, or decide whether a segment is worth pursuing.RedactareFără avertismente★ 2,6 K↓ —
- hypothesis-generationK-Dense-AI/scientific-agent-skillsFormulates evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Used when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.ȘtiințăFără avertismente★ 55,6 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★ 21,8 K↓ —
- chief-product-officercbrock84/headcountAn 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.JuridicFără avertismente★ 2,6 K↓ —
data-modeling
cbrock84/headcount
DateActualizat 18 oct. 2026
De la autor
Designs the warehouse and semantic layer — source-to-mart structure, dimensional modeling, grain, slowly changing dimensions, and the metric layer analytics reads through. Use this to design or restructure a warehouse, model a new source, decide on grain or table structure, build a semantic or metric layer, or diagnose why queries are slow, wrong, or impossible to write.
Instalare
npx skills add cbrock84/headcount --skill data-modeling -a claude-code
Se instalează în .claude/skills/data-modeling/ · 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
Niciun avertisment.
De ce 89
Securitate100
Proveniență80
Întreținere100
Licență100
Adopție53
Fișiere (2)
- SKILL.md
- references/sources.md