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.
46.700 de skill-uri din 2.243 de depozite · actualizat acum 14 ore
46.700 de skill-uri
- figma-automationdavepoon/buildwithclaudeAutomate Figma tasks via Rube MCP (Composio): files, components, design tokens, comments, exports. Always search tools first for current schemas.DesignFără avertismente★ 3,7 K↓ —
- ramp-observabilityjeremylongshore/tons-of-skills-marketplaceInstrument Ramp API clients, webhook consumers, deferred tasks, and accounting syncs with safe service and financial-correctness signals. Use when defining dashboards, alerts, traces, or reconciliation health. Trigger with "monitor Ramp integration" or "Ramp observability".DevOpsFără avertismente★ 2,9 K↓ —
- ctf-cryptoljagiello/ctf-skillsProvides cryptography attack techniques for CTF challenges. Use when attacking encryption, hashing, signatures, ZKP, PRNG, or mathematical crypto problems involving RSA, AES, ECC, lattices, LWE, CVP, number theory, Coppersmith, Pollard, Wiener, padding oracle, GCM, key derivation, or stream/block cipher weaknesses.FinanțeFără avertismente★ 3,5 K↓ —
- figma-implement-designforyourhealth111-pixel/Vibe-SkillsTranslate Figma nodes into production-ready code with 1:1 visual fidelity using the Figma MCP workflow (design context, screenshots, assets, and project-convention translation). Trigger when the user provides Figma URLs or node IDs, or asks to implement designs or components that must match Figma specs. Requires a working Figma MCP server connection.DesignFără avertismente★ 3,8 K↓ —
- requesting-code-reviewforyourhealth111-pixel/Vibe-SkillsPrepare and request a code review after implementation or before merge by assembling scope, requirements, git range, and reviewer instructions.InginerieFără avertismente★ 3,8 K↓ —
- property-based-testingforyourhealth111-pixel/Vibe-SkillsProperty-based testing with fast-check (TypeScript/JavaScript) and Hypothesis (Python). Generate test cases automatically, find edge cases, and test mathematical properties. Use when user mentions property-based testing, fast-check, Hypothesis, generating test data, QuickCheck-style testing, or finding edge cases automatically.TestareFără avertismente★ 3,8 K↓ —
- kiro-spec-requirementsgotalab/cc-sddGenerate comprehensive requirements for a specificationPlanificareFără avertismente★ 3,7 K↓ —
- designing-experimentsforyourhealth111-pixel/Vibe-SkillsDesign experiments and quasi-experiments before analysis. Use when choosing study design, treatment/control structure, outcomes, assumptions, validation plans after scientific experiment failure, or which of DiD, ITS, synthetic control, or regression discontinuity fits the research question. For fitting models or estimating effects on existing data, use performing-causal-analysis instead.DesignFără avertismente★ 3,8 K↓ —
- documentation-lookupforyourhealth111-pixel/Vibe-SkillsUse when the user needs current library, framework, or API documentation and version-specific code examples.PlanificareFără avertismente★ 3,8 K↓ —
- kiro-spec-designgotalab/cc-sddCreate comprehensive technical design for a specificationDesignFără avertismente★ 3,7 K↓ —
- ops-projectsdavepoon/buildwithclaudePortfolio dashboard for all GSD-tracked projects. Scans ~/Projects and ~/gsd-workspaces for .planning/ directories, shows phase status, git state, blockers, and next actions for every project. Run /ops projects to see the full portfolio.PlanificareFără avertismente★ 3,7 K↓ —
- ulw-researchcode-yeongyu/oh-my-openagentRuns maximum-saturation research with a cooperating team, claim-graph gating, and a cited, QA'd deliverable. Use when the user explicitly asks for research or a deep investigation, including any 'ulw' research wording.ȘtiințăFără avertismente★ 70,4 K↓ —
- stop-that-shitlennney/stop-that-shitComplete requested work while preventing speculative defenses and scope creep. Use when considering extra hardening, reviewing possible overengineering, resolving repeated verification loops, following explicit task boundaries, or when the user invokes Stop That Shit. Ordinary use of validation, retries, or dependencies alone is not a trigger.PlanificareFără avertismente★ 3,2 K↓ —
- kiro-spec-batchgotalab/cc-sddCreate complete specs (requirements, design, tasks) for all features in roadmap.md using parallel sub-agent dispatch by dependency wave.PlanificareFără avertismente★ 3,7 K↓ —
- kiro-spec-batchgotalab/cc-sddCreate complete specs for roadmap features by dependency wave using Devin subagents when available, with permission-aware sequential and inline fallbacks.PlanificareFără avertismente★ 3,7 K↓ —
- doca-gpunetioNVIDIA/skillsUse this skill when the user is doing hands-on DOCA GPUNetIO programming — wiring a CUDA kernel on an NVIDIA GPU to a doca-eth queue via doca_gpu_eth_rxq / doca_gpu_eth_txq, standing up the per-CUDA-device doca_gpu context, designing the persistent CUDA kernel that drains the GPU-visible queue, running the dual capability check (DOCA cap-query plus cudaGetDeviceProperties), registering cudaMalloc pools via doca_buf_arr_create_*, or debugging DOCA_ERROR_* returns from the GPUNetIO API. Trigger even when the user does not explicitly mention "DOCA GPUNetIO" or "persistent kernel" — typical implicit phrasings include "CUDA kernel reading packets directly from the NIC", "GPU-initiated networking on BlueField", "DOCA_ERROR_DRIVER on doca_gpu_create", "nvidia_peermem not loaded", "kernel-per-packet is too slow", or "which GPU supports GPU-side packet I/O". Refuse and route elsewhere for general CUDA programming, DOCA Ethernet queue bring-up, DOCA DPA, or DOCA install — those belong to other skills.InginerieFără avertismente★ 3,8 K↓ —
- doca-compressNVIDIA/skillsHardware compression offload with DOCA Compress on a BlueField DPU, ConnectX NIC, or host: DEFLATE compress and decompress, plus LZ4 decompress (stream and block; LZ4 encode is NOT supported), instead of CPU zlib / zstd. Trigger on "offload this gzip", "decompress incoming network data on the NIC", "compress task returns INVALID_VALUE on alloc_init", "submitted a task but no completion arrives", or "decompress LZ4 on the BlueField", even without naming DOCA Compress. Covers enabling compress-deflate, decompress-deflate, decompress-lz4-stream and decompress-lz4-block tasks on a doca_compress context, sizing source / destination doca_buf against the per-task cap query, mmap permissions, offload vs CPU decisions, a round-trip smoke, and DOCA_ERROR_* from Compress calls. Refuse and route elsewhere for zstd / Snappy / brotli, LZ4 encode (a CPU LZ4 library), pure mmap-to-mmap copies (doca-dma), or DOCA Core lifecycle internals.ProductivitateFără avertismente★ 3,8 K↓ —
- narrative-baseline-mapperaaron-he-zhu/aaron-marketing-skillsUse when the user asks to "map what our surfaces say today", "inventory our current messaging", or "find the gap between what we say and what we mean"; produces the narrative baseline — a surface-by-surface inventory of what every owned touchpoint (homepage, pricing, docs, decks, social bios, email footers) claims RIGHT NOW, each line labeled Measured / User-provided / Estimated, plus a per-surface gap read vs the intended message and the drift-baseline snapshot the Evaluate phase measures future drift against. Not for authoring the canon — use message-system-architect; not for scoring the surfaces or running the vetoes — use narrative-quality-auditor. 现状叙事盘点/各触点口径/意图差距/漂移基线PlanificareFără avertismente★ 3 K↓ —
- tao-train-pointpillarsNVIDIA/skillsPointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, exporting, pruning, retraining, or running inference for a TAO PointPillars model. Trigger phrases include "train PointPillars", "LiDAR 3D detection", "point-cloud object detection", "pillar-based 3D detector".MediaFără avertismente★ 3,8 K↓ —
- doca-flow-perfNVIDIA/skillsUse this skill when the user measures control-plane insertion throughput of DOCA Flow with the doca_flow_perf binary on x86 host or Arm cores — selecting a configs/ JSON policy, weighing the DPDK-versus-DOCA backend, running the smoke iteration then the eval loop, interpreting CPU cycles plus num_pushed / num_failed, or capturing the four-tuple (DOCA release, firmware, JSON policy, worker config) that makes an insertion figure defensible. Also load it for implied asks like "5-tuple hairpin insert figure", "flow-perf result mismatches release notes", "DPDK-vs-DOCA comparison", or "install variance too high". Refuse and route to the proper owner for live-app optimization (doca-flow-tune), wire throughput or latency, or library-internal pipe semantics.PlanificareFără avertismente★ 3,8 K↓ —
- finta-hello-worldjeremylongshore/tons-of-skills-marketplaceSet up your first fundraise pipeline in Finta with investors and deal stages. Use when starting a new fundraise, importing investor lists, or learning Finta's pipeline management features. Trigger with phrases like "finta hello world", "finta first pipeline", "start fundraise in finta", "finta quick start".FinanțeFără avertismente★ 2,9 K↓ —
- gsd:importdavepoon/buildwithclaudeIngest external plans with conflict detection against project decisions before writing anything.RedactareFără avertismente★ 3,7 K↓ —
- excel-lbo-modelerjeremylongshore/tons-of-skills-marketplaceBuild leveraged buyout (LBO) models in Excel with debt schedules and IRR analysis. Use when structuring LBO transactions or analyzing PE returns. Trigger with phrases like 'excel lbo', 'build lbo model', 'calculate pe returns'.DocumenteFără avertismente★ 2,9 K↓ —
- document-skillsforyourhealth111-pixel/Vibe-SkillsUmbrella skill for document workflows (PDF/DOCX/XLSX/PPTX). Dispatches to the most specific document skill to reduce noise and improve routing precision.DocumenteFără avertismente★ 3,8 K↓ —
pyhealth
foryourhealth111-pixel/Vibe-Skills
TestareActualizat alaltăieri
De la autor
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).
Instalare
npx skills add foryourhealth111-pixel/Vibe-Skills --skill pyhealth -a claude-code
Se instalează în .claude/skills/pyhealth/ · 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 90
Securitate100
Proveniență83
Întreținere100
Licență100
Adopție57
Fișiere (7)
- SKILL.md
- references/datasets.md
- references/medical_coding.md
- references/models.md
- references/preprocessing.md
- references/tasks.md
- references/training_evaluation.md