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.
49.399 de skill-uri din 2.375 de depozite · actualizat acum 29 de minute
49.399 de skill-uri
- 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★ 56 K↓ —
- labarchive-integrationK-Dense-AI/scientific-agent-skillsIntegrates with the official LabArchives ELN REST-like API and Inventory API v1. Supports regional endpoint selection, signed-request construction, user authorization and UID flows, local LA container validation, and verified LabArchives integration workflows.InginerieFără avertismente★ 56 K↓ —
- continuous-discoverywondelai/skillsBuild a weekly cadence of customer touchpoints using Opportunity Solution Trees, assumption mapping, and interview snapshots. Use when the user mentions "continuous discovery", "opportunity solution tree", "weekly interviews", "assumption testing", "discovery habits", "product trio", "outcome-based roadmap", "how do I talk to customers regularly", "we keep building things nobody uses", or "connect research to the roadmap". Also trigger when setting up regular customer feedback loops, prioritizing which experiments to run, or tying discovery insights to delivery work. Covers experience mapping, co-creation, and prioritizing opportunities. For interview technique, see mom-test. For team structure, see inspired-product.TestareFără avertismente★ 2,6 K↓ —Apare și în 2 alte depozite
- codebase-wikiinkeep/open-knowledgeHow to work in a Codebase Wiki project (the `codebase-wiki` starter pack): an agent-authored, source-grounded wiki of the surrounding codebase. Read when the project has a `wiki/` knowledge base with `architecture/`, `modules/`, `flows/`, `concepts/`, and `guides/` sections plus `wiki/OVERVIEW.md`, or when asked to generate or refresh a wiki of this codebase. Carries the per-folder rules and freshness + log discipline, summarizes the audience/depth knobs and source-reference convention, and bundles the full generate/refresh procedure in `references/`. Complements the platform `open-knowledge` skill; does not replace it.PlanificareFără avertismente★ 4,8 K↓ —
- 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★ 56 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★ 56 K↓ —
- api-design-principleswshobson/agentsMaster REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.DesignFără avertismente★ 42,1 K↓ —
- scientific-slidesK-Dense-AI/scientific-agent-skillsBuilds slide decks and presentations for research talks. Used for making PowerPoint slides, conference presentations, seminar talks, research presentations, thesis defense slides, or any scientific talk. Provides slide structure, design templates, timing guidance, and visual validation. Works with PowerPoint and LaTeX Beamer.DocumenteFără avertismente★ 56 K↓ —
- gke-workload-securitygoogle/skillsAudits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (`audit_cluster.sh`), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (`gVisor`), enforcing Pod Security Standards (`restricted` labeling) and pod securityContext, and mounting Secret Manager secrets via CSI (`SecretProviderClass`). Use when auditing workload security posture, isolating namespaces, applying pod security standards, or configuring network policies and secret volume mounts. Don't use for Workload Identity (use gke-workload-identity), cluster-wide control plane security, RBAC hardening, Binary Authorization, Shielded Nodes, or enabling platform-level GKE add-ons (use gke-platform-security instead).OficialSecuritateFără 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↓ —
- writing-workflowinkeep/open-knowledgeHow to work in a Writing Pipeline project (the `writing-pipeline` starter pack): a three-stage drafting flow, ideas → drafts → published. Read when the project has these folders, OR when asked to capture an idea, start or revise a draft, review a piece before it ships, or publish it. Carries the stage flow and review behaviors so that guidance does not live inside template bodies or folder descriptions. Complements the platform `open-knowledge` skill; does not replace it.RedactareFără avertismente★ 4,8 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★ 56 K↓ —
- hugging-scienceK-Dense-AI/scientific-agent-skillsDiscovers and evaluates scientific datasets, models, methodology posts, and Spaces through the Hugging Science catalog. Used when selecting scientific ML resources in biology, chemistry, genomics, materials, climate, physics, astronomy, medicine, mathematics, protein design, single-cell analysis, or PDE modeling, and when checking their actual datasets, Transformers, native-runtime, Inference Providers, or Gradio interfaces.ȘtiințăFără avertismente★ 56 K↓ —
- sales-compensation-and-territorycbrock84/headcountDesigns quotas, territories and commission plans that produce the behavior the business needs — sizing territories against real potential, setting quotas people can hit often enough to believe in, choosing what to pay on, handling accelerators, draws, clawbacks and disputes, and changing a plan without destroying trust. Use this to build or fix a comp plan, allocate territories, work out why reps are chasing the wrong deals, or plan a mid-year change.PlanificareFără avertismente★ 2,6 K↓ —
- open-notebookK-Dense-AI/scientific-agent-skillsOrganizes research with the self-hosted Open Notebook alternative to NotebookLM. Supports source ingestion (PDFs, web pages, audio, video, and Office documents), cited document chat, text and vector search, notes, custom transformations, and multi-speaker podcasts. Use when automating Open Notebook through its REST API or configuring its local or cloud AI providers, including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral.MediaFără avertismente★ 56 K↓ —
- copilot-pr-autopilotgithub/awesome-copilotCopilot left 14 review comments on your PR — half are nits. Hours of fix → reply → resolve → re-request, and each round lands MORE comments. This skill runs loop engineering: auto-triggers Copilot Code Review via GraphQL (no @copilot mention), triages every open thread (Copilot, humans, advanced-security) with a fix / decline / escalate rubric, dispatches parallel fix sub-agents that obey the repo build/test/lint conventions, commits per iteration, replies+resolves citing the pushed SHA, then re-triggers until HEAD is reviewed with zero threads awaiting the agent's reply (remaining open threads are explicit hand-offs to the human — escalated declines, design tradeoffs). You merge a clean PR; the bot runs it. Trigger phrases: "address copilot comments", "run a copilot review loop", "fix this PR", "iterate on copilot feedback". Repo-agnostic, gh CLI + PowerShell. Full autopilot needs repo Triage/Write; external PR authors get single-iteration mode plus manual re-trigger (UI 🔄 or substantive-commit push).SecuritateFără avertismente★ 40,8 K↓ —
- silivilleLeoYeAI/agent-master-skillsGives any AI agent a persistent identity in SiliVille (硅基小镇) — a multiplayer AI-native metaverse. Farm, steal crops, post to the town feed, build social graphs, and store long-term memories via a simple REST API.InginerieFără avertismente★ 2,2 K↓ —Apare și în 1 alt depozit
- scorecard-marketingwondelai/skillsBuild quiz and assessment funnels that generate qualified leads at 30-50% conversion. Use when the user mentions "quiz funnel", "scorecard", "lead magnet", "score-based segmentation", or "lead qualification". Also trigger when designing self-assessment tools, building calculators or graders for marketing, or creating personalized result pages that drive conversions. Covers concept hooks, question design, dynamic results by tier, and automated follow-up sequences. For landing page conversion, see cro-methodology. For full marketing plans, see one-page-marketing.MarketingFără avertismente★ 2,6 K↓ —Apare și în 2 alte depozite
- dsh-pre-push-checksNouqufei1993/skills-hub在交付或推送前验证改动时使用，核实项目必需检查、当前构建产物和真实用户行为，区分通过、失败、未运行与环境阻塞。AlteleFără 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↓ —
- consolidate-notesinkeep/open-knowledgePromote existing research into a stable-status canonical article under `articles/` in a Knowledge Base project (the `knowledge-base` starter pack). Read when a decision has actually been made and the team wants the source-of-truth written down, or when asked to consolidate, canonicalize, promote research, or supersede an older article. Carries the decision-confirmation gate, the `supersedes:` chain that keeps the evidence trail intact, and the canonical voice. Does not conduct new research — that is the sibling `research-with-sources` skill.ProductivitateFără avertismente★ 4,8 K↓ —
- einstieg-routingKlotzkette/claude-fuer-deutsches-rechtFür Einstieg und Routing: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Jurastudium.AlteleFără avertismente★ 1,8 K↓ —
- nmrglueK-Dense-AI/scientific-agent-skillsProcesses calibrated one-dimensional complex NMR free-induction decays with nmrglue into phased spectra, peak candidates, and signed integration regions. Use for raw 1D NMR processing, ppm-axis verification, apodization, Fourier transformation, manual phasing, baseline correction, or reproducible spectral integration.PlanificareFără avertismente★ 56 K↓ —Apare și în 2 alte depozite
- 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★ 21,8 K↓ —
agents-best-practices
DenisSergeevitch/agents-best-practices
DevOpsActualizat 19 oct. 2026
De la autor
Use 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.
Instalare
npx skills add DenisSergeevitch/agents-best-practices --skill agents-best-practices -a claude-code
Se instalează în .claude/skills/agents-best-practices/ · 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
Proveniență81
Întreținere100
Licență100
Adopție54
Fișiere (5)
- .gitignore
- LICENSE
- README.md
- SKILL.md
- icon.jpeg