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 15 ore
48.622 de skill-uri
- industriekundenKlotzkette/claude-fuer-deutsches-rechtFür Industriekunden — Sonderregelungen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- research-ideationpedrohcgs/claude-code-my-workflowGenerate structured research questions, testable hypotheses, and candidate empirical strategies from a topic, phenomenon, or dataset description. Use when user says "give me research ideas on X", "brainstorm questions about Y", "what could I study with this data?", "I'm looking for a paper idea on...", "generate hypotheses for...". One-shot generation, not multi-turn. For idea-refinement use `/interview-me`.ȘtiințăFără avertismente★ 1,7 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★ 55,6 K↓ —
- stipulatioKlotzkette/claude-fuer-deutsches-rechtFür Stipulatio: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- replication-packagepedrohcgs/claude-code-my-workflowAssemble a submission-ready replication package to the AEA Data and Code Availability Standard (DCAS) / openICPSR / Social Science Reproduction Platform expectations — standard replication README, dataset manifest, computational-requirements capture, a Table/Figure → script:line map, and a confidential-data deposit plan. Use when user says "build the replication package", "prepare the openICPSR deposit", "make the AEA data and code package", "DCAS compliance", "assemble the deposit for the journal", or after a paper is accepted and the journal's data editor needs the package. NOT a numeric verifier — it calls /audit-reproducibility to confirm claims reproduce before packaging.ȘtiințăFără avertismente★ 1,7 K↓ —
- network-administrationcbrock84/headcountDesigns and operates the corporate network — segmentation, remote access, wireless, DNS and addressing, and diagnosing network problems. Use this to segment a network, set up or fix remote access, diagnose intermittent connectivity, plan addressing or DNS, or assess whether the network's trust assumptions still hold.PlanificareFără avertismente★ 2,6 K↓ —
- vulnerability-managementcbrock84/headcountRuns the loop from discovering a weakness to confirming it is fixed — scanning, triage, prioritization by real exploitability, remediation tracking, and patch policy. Use this to stand up or fix a vulnerability program, triage scanner output, decide what to fix first, set patch SLAs, handle a disclosure from an outside researcher, or report posture to leadership.SecuritateFără avertismente★ 2,6 K↓ —
- bonusKlotzkette/claude-fuer-deutsches-rechtFür Bonus und leistungsbezogene Vergütung im Handelsvertretervertrag: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- translatefeiskyer/claude-code-settingsTranslate English or Japanese tech articles into natural, fluent Chinese. Use whenever the user asks for Chinese translation, says "translate to Chinese" or "翻译", or provides English/Japanese content (pasted text or a file) to convert into Chinese. Chinese output only — not for translating into other languages.AlteleFără avertismente★ 1,7 K↓ —
- zhengxi-viewslyra81604/zhengxi-views郑希观点库——基于易方达基金经理郑希 2012–2026 年全部公开观点原文语料，外加从语料蒸馏、有本人原话佐证的郑希投资方法的可溯源 research skill。能做： (1) 溯源问答——他怎么看 AI算力/光通信/新能源/半导体/ROE 等，引用其原话作答； (2) 讲解他的投资方法/框架/选股逻辑；(3) 前瞻应用——用他的方法分析当下任意主题/行业/个股，语料没谈过也能据框架推演； (4) 风格化点评——用他季报/手记的口吻写市场点评、季度展望； (5) 言行对照——用他全部基金真实数据（季度持仓/净值/业绩/规模/任职回报）核对"说的"与"买的"，或答他的业绩/重仓/规模； (6) 全市场查询对比——内置约 2.7 万只基金列表，按需抓任意基金真实数据做查询或与郑希对比； (7) 郑希框架评分——给一只基金按他的方法打分（多像郑希会买的）。 When the user mentions 郑希/易方达郑希/zhengxi, asks his view on a sector/stock/theme, his 投资方法/框架/选股/风格/持仓/业绩/净值/规模, wants to apply his approach, a commentary 用郑希口吻, to check words vs holdings, or to look up/compare/score ANY China mutual fund (任意基金/某基金经理/同类对比/给基金打分)——use this skill, even if they don't say "skill", even if the topic isn't in his corpus (fall back to his method). 引用忠于原文、不杜撰；推演与原话区分。研究学习辅助，非投资建议。ȘtiințăFără avertismente★ 1,8 K↓ —
- it-asset-managementcbrock84/headcountTracks hardware and software assets through their life — procurement, ownership, licensing, refresh, and disposal. Use this to build an asset register, prepare for a software audit, plan a refresh cycle, control license spend, or dispose of equipment safely.PlanificareFără avertismente★ 2,6 K↓ —
- pathmlK-Dense-AI/scientific-agent-skillsSupports local computational pathology research with PathML: slide loading and tiling, preprocessing and QC, h5path storage, multiplex quantification, spatial graphs, and bounded model inference. Use for whole-slide H&E, CODEX, Vectra, Mesmer, HoVer-Net, and HACTNet workflows.DocumenteFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- fundraising-and-investor-relationscbrock84/headcountRaises capital and manages the relationship afterward — deciding how much and why, understanding what dilution and preferences actually cost, running a process with real competitive tension, preparing for diligence before it starts, and reporting to investors and a board in a way that keeps support when results are bad. Use this to plan a raise, evaluate a term sheet beyond the valuation, prepare a data room, or fix reporting that is producing surprises.FinanțeFără avertismente★ 2,6 K↓ —
- parallel-agent-deliverycbrock84/headcountSplits work across multiple agents or sessions running at once, keeping their surfaces disjoint so results merge cleanly. Use this when facing several independent tasks with no shared state, when a plan has parallelizable steps, when a broad search or audit would be faster fanned out, or when deciding whether work can safely be split at all.PlanificareFără avertismente★ 2,6 K↓ —
- detection-and-monitoringcbrock84/headcountBuilds the capability to notice an attack in progress — deciding what to log and retain, centralizing it somewhere tamper-resistant, writing detections that fire on attacker behavior rather than on individual events, tuning out the noise that trains people to ignore alerts, and defining what happens when something fires. Use this to design or assess monitoring coverage, work out why an incident went unnoticed, cut alert volume without losing signal, or decide what a detection capability should cost.DesignFără avertismente★ 2,6 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★ 10,2 K↓ —
- autoskillK-Dense-AI/scientific-agent-skillsAnalyzes user-requested Screenpipe history windows to detect repeated research workflows, match existing scientific skills, and stage new skill drafts or composition recipes for review. Requires a reachable Screenpipe HTTP API, normally on localhost:3030. Detection and embedding inference run locally; the selected LLM receives redacted app/title cluster summaries and matched skill descriptions. Use only when the user explicitly asks to analyze their recent work and propose skills.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- daskK-Dense-AI/scientific-agent-skillsScales pandas, NumPy, and custom Python research workflows beyond memory or across clusters with Dask. Covers DataFrames, Arrays, Bags, Futures, chunking, schedulers, and distributed diagnostics. Use for partitioned file processing, scientific array computation, or parallel tasks whose memory and dependency structure require Dask.DateFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- 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
- disputes-and-legal-holdscbrock84/headcountHandles a dispute from the first sign of it — recognizing when preservation obligations attach, issuing and scoping a legal hold, suspending automatic deletion across every system that holds relevant material, preserving privilege, managing outside counsel and cost, and evaluating settlement against the real cost of continuing. Use this to respond to a claim or demand letter, issue a hold, work out which systems the hold has to reach, or decide whether to fight.JuridicFără avertismente★ 2,6 K↓ —
- molfeatK-Dense-AI/scientific-agent-skillsFeaturizes small molecules with Molfeat for QSAR/QSPR, chemical similarity, virtual screening, and molecular ML. Covers ECFP/MACCS fingerprints, RDKit descriptors, pharmacophores, pretrained embeddings, configuration persistence, and molecule-to-label alignment.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 1 alt depozit
- pydicomK-Dense-AI/scientific-agent-skillsReads, inspects, writes, transforms, and preflights local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.RedactareFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- pysamK-Dense-AI/scientific-agent-skillsProvides Python/HTSlib workflows for genomic files. Used when reading, querying, filtering, or writing SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, or tabix data with pysam, including pileup, coverage, indexing, and CRAM references.ȘtiințăFără avertismente★ 55,6 K↓ —Apare și în 2 alte depozite
- analytical-method-validationK-Dense-AI/scientific-agent-skillsPlans, executes, and documents validation, verification, and transfer of analytical procedures under the governing framework - ICH Q2(R2) and Q14, USP <1220>/<1225>/<1226>, ICH M10 bioanalytical, CLSI EP, or ISO/IEC 17025. Use for HPLC, LC-MS/MS, GC, CE, ICP-MS, dissolution, qNMR, qPCR, NIR, and ligand binding or cell-based assays whenever the question is whether a procedure is fit for its intended purpose. Triggers include "method validation", "analytical method validation", "AMV", "validation protocol", "acceptance criteria", "linearity", "reportable range", "accuracy and precision", "repeatability", "intermediate precision", "recovery", "LOD", "LOQ", "detection limit", "quantitation limit", "specificity", "robustness", "method transfer", "method comparison", "Deming", "Passing-Bablok", "Bland-Altman", "equivalence testing", "OOS investigation", "ICH Q2", "Q2(R2)", "Q14", "USP 1225", "ICH M10", "incurred sample reanalysis", "ISR", "CLSI EP", and any request to show that an assay works.TestareFără avertismente★ 55,6 K↓ —
gke-cluster-autoscaler
google/skills
OficialPlanificareActualizat alaltăieri
De la autor
Trigger 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).
Instalare
npx skills add google/skills --skill gke-cluster-autoscaler -a claude-code
Se instalează în .claude/skills/gke-cluster-autoscaler/ · 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
Rulează scripturile incluseNu am văzut acces la rețeaLicență: APACHE-2.0
Verificări de siguranță pe SKILL.md
- Include scripturi pe care nu le-am verificatScăzut
De ce 89
Securitate85
Proveniență100
Întreținere100
Licență100
Adopție67
Fișiere (10)
- SKILL.md
- assets/capacity-buffer-serving.yaml
- assets/find-scale-down-blockers.sh
- assets/log-autoscaler-events.sh
- references/attribution.md
- references/ca-capacity-buffers.md
- references/ca-consolidation-tuning.md
- references/ca-debug.md
- references/ca-optimization.md
- references/ca-provisioning.md