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.
8.582 de skill-uri din 252 de depozite · actualizat acum 5 minute
570 de skill-uri
- gamma-cost-tuningjeremylongshore/tons-of-skills-marketplaceOptimize Gamma usage costs and manage API spending. Use when reducing API costs, implementing usage quotas, or planning for scale with budget constraints. Trigger with phrases like "gamma cost", "gamma billing", "gamma budget", "gamma expensive", "gamma pricing".PlanificareFără avertismente★ 2,9 K↓ —
- castai-rate-limitsjeremylongshore/tons-of-skills-marketplaceBuild a CAST AI REST client that respects endpoint-specific throttling, bounded retries, and an explicit request budget. Use when a job receives 429 responses, polls CAST AI, or fans out across clusters and organizations. Trigger with: "handle CAST AI rate limits", "stop CAST AI 429s", "make CAST AI polling safe".PlanificareFără avertismente★ 2,9 K↓ —
- cohere-rate-limitsjeremylongshore/tons-of-skills-marketplaceImplement Cohere endpoint-aware throttling, bounded retry, and queue backpressure from current limits and observed responses. Use when handling 429s or planning throughput. Trigger with "Cohere rate limit", "Cohere throttling", or "Cohere 429".PlanificareFără avertismente★ 2,9 K↓ —
- fathom-cost-tuningjeremylongshore/tons-of-skills-marketplaceOptimize Fathom API usage and plan selection. Trigger with phrases like "fathom cost", "fathom pricing", "fathom plan".PlanificareFără avertismente★ 2,9 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★ 21,5 K↓ —
- gke-compute-classesgoogle/skillsConfigures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto Provisioning configuration or general GKE cluster creation.OficialPlanificareFără avertismente★ 21,5 K↓ —
- loresickn33/agentic-awesome-skillsMarkdown project memory for AI agents. Use for decisions, architecture, conventions, monorepo scopes, `.lore/`, or `lore` commands; not native `/init`/`/compact` or generic init/compress/audit/query.PlanificareFără avertismente★ 48,2 K↓ —
- protocolsio-integrationK-Dense-AI/scientific-agent-skillsReads, validates, and safely exports protocols.io data with current official REST/MCP contracts, or creates non-executing mutation plans. The bundled client makes bounded official-host GET requests only with explicit --execute. Use only for tasks explicitly targeting protocols.io or an exact protocols.io protocol version.PlanificareFără avertismente★ 53,4 K↓ —
- nansen-wallet-profilerinternet-court/internet-court-skillWallet profiler — balance, PnL, labels, transactions, counterparties, related wallets, batch, trace, compare. Use when analysing a specific wallet address or comparing wallets.PlanificareFără avertismente★ 6,8 K↓ —
- nansen-prediction-marketsinternet-court/internet-court-skillPolymarket screeners — discover trending events, top markets by volume, and search for specific markets. Use when browsing what's happening on prediction markets.PlanificareFără avertismente★ 6,8 K↓ —
- treatment-plansK-Dense-AI/scientific-agent-skillsFormats and structurally validates local treatment-plan documentation after clinical decisions have already been supplied and verified by authorized licensed professionals. Use for source traceability, clinician-authored intervention records, goals and checkpoints, shared-decision records, reconciliation handoffs, and release gates—not for clinical decision-making.PlanificareFără avertismente★ 53,4 K↓ —
- pennylaneK-Dense-AI/scientific-agent-skillsBuilds and differentiates PennyLane quantum circuits, hybrid PyTorch or JAX models, molecular VQE and QAOA workflows. Use for variational quantum algorithms, quantum machine learning, simulator validation, and moving validated circuits to provider plugins. For hardware-specific compilation use qiskit or cirq; for open-system dynamics use qutip.PlanificareFără avertismente★ 53,4 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★ 53,4 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★ 53,4 K↓ —
- matchmsK-Dense-AI/scientific-agent-skillsProcesses, cleans, compares, and searches tandem mass spectra with matchms. Use for MS/MS file I/O, metadata harmonization, peak filtering, spectral similarity, library matching, score matrices, and molecular-similarity networks. Use pyopenms instead for LC-MS feature detection or proteomics pipelines.PlanificareFără avertismente★ 53,4 K↓ —
- qutipK-Dense-AI/scientific-agent-skillsSimulate and audit closed and open quantum-system models with QuTiP 5, including deterministic, trajectory, steady-state, spectral, and phase-space workflows. Use for local quantum-dynamics work where physical assumptions, dimensions, and numerical convergence must be explicit.PlanificareFără avertismente★ 53,4 K↓ —
- aeonK-Dense-AI/scientific-agent-skillsThis skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.PlanificareFără avertismente★ 53,4 K↓ —
- pylabrobotK-Dense-AI/scientific-agent-skillsDevelops and reviews PyLabRobot lab-automation resources, liquid-handling plans, offline simulations, and supported-device integrations. Supports PyLabRobot protocols and API questions; keep physical execution behind an explicit operator safety gate.PlanificareFără avertismente★ 53,4 K↓ —
- 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★ 4,6 K↓ —
- portaljs-architectdatopian/portaljsRecommend a data-portal architecture (storage, compute, catalog, access, hosting, metadata) from stated needs, then hand off to the build skills. The advisory entry point. Use when starting a new data-portal project and the underlying architecture has not yet been decided.PlanificareFără avertismente★ 2,4 K↓ —
- fable-loopSahir619/fable-methodEnd-to-end orchestrated workflow that runs a task the way Fable ran sessions - parallel evidence subagents, one committed plan, surgical execution with an intent gate, adversarial verification agents, honest outcome-first report. Use for non-trivial multi-step tasks when the user says "/fable-loop", "run the fable loop", or "do this the way Fable would". For the rules alone without orchestration, use fable-method; for large multi-phase projects, prefer the GSD workflow and use this inside phases.PlanificareFără avertismente★ 2,3 K↓ —
- fable-methodSahir619/fable-methodA step-by-step problem-solving loop (classify the ask, define done, gather evidence, decide, act surgically, verify by observation, report outcome-first). Use when the user says "/fable-method", "use the fable method", or "approach this like Fable", or proactively when starting any multi-step task that no task-specific skill covers. Subcommands - plan (stop after the plan), audit (grade finished work against the loop), report (rewrite an answer outcome-first).PlanificareFără avertismente★ 2,3 K↓ —
- game-jamgamedev-skills/awesome-gamedev-agent-skillsPlan and ship a game under a jam deadline: lock scope to the clock, schedule the hours, cut features, and submit on time. Use for a game jam (Ludum Dare, GMTK Jam, Global Game Jam), a 48-hour or weekend build, or scoping and submitting a jam entry.PlanificareFără avertismente★ 2,2 K↓ —
- input-systemsgamedev-skills/awesome-gamedev-agent-skillsArchitect game input — action mapping (abstracting keys into named actions), rebinding with conflict detection and persistence, multi-device support (keyboard, gamepad, touch), analog deadzones, and feel features like input buffering and coyote time, plus accessibility. Engine-neutral. Use when the user mentions input mapping, rebind controls, gamepad support, deadzone, input buffering, coyote time, or accessible controls.PlanificareFără avertismente★ 2,2 K↓ —