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 35 de minute
48.622 de skill-uri
- 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
- marine-carbonate-chemistryK-Dense-AI/scientific-agent-skillsSolves seawater carbonate chemistry with PyCO2SYS for chemical oceanography, ocean acidification, and marine carbon-cycle research. Use for paired total alkalinity, dissolved inorganic carbon, pH, or seawater pCO2/fCO2 measurements; carbonate speciation; aragonite and calcite saturation; Revelle factors; lab-to-in-situ temperature and pressure corrections; and measurement uncertainty propagation. Applies to carbonate-system calculations, not general aqueous speciation or air-sea gas-flux estimation.ȘtiințăFără avertismente★ 55,6 K↓ —
- nebenberufKlotzkette/claude-fuer-deutsches-rechtFür Nebenberuf: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Berufsrecht Notare.AlteleFără avertismente★ 1,8 K↓ —
- red-teamKlotzkette/claude-fuer-deutsches-rechtFür Red-Team-Review für Insiderrecht-Compliance: prüft Ergebnis, Beweislast und Gegenposition; Ergebnis: Gegenprüfung mit Beweis- und Fristencheck.JuridicFără avertismente★ 1,8 K↓ —
- 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
- 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
- memorycodeaholicguy/ai-devkitAI DevKit · Use the memory CLI as a durable knowledge layer. Search before non-trivial work, store verified reusable knowledge, update stale entries, and avoid saving transcripts, secrets, or one-off task progress.ProductivitateFără avertismente★ 1,7 K↓ —
- get-available-resourcesK-Dense-AI/scientific-agent-skillsDetects host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a clearly resource-sensitive local workload. Produces a redacted JSON snapshot and conservative planning helpers without stress tests or assuming visible host hardware is usable.TestareFără avertismente★ 55,6 K↓ —
- relsa-severity-assessmentK-Dense-AI/scientific-agent-skillsSupports multivariate severity assessment and exploratory endpoint-time score forecasting for laboratory animal studies using the RELSA (RELative Severity Assessment) score and ARIMA-based foRcast forecasting. Use when combining welfare readouts — body weight or weight loss, body temperature, clinical or nesting scores, biomarkers, activity, heart rate, burrowing, wheel running — into one severity score per animal per day, when asking which animals are at risk of reaching a humane endpoint at a specified future observation time, when defining attention/danger zones or thresholds on a severity scale by kernel density estimation, or when reporting severity for a 3Rs, refinement, animal-welfare, or EU Directive 2010/63/EU severity-assessment context. Covers directionality ("turned" variables), baseline normalization, reference sets, RELSA weights, ARIMA prediction intervals, and RMSE/PICP/MPIW evaluation.ȘtiințăFără avertismente★ 55,6 K↓ —
- transformersK-Dense-AI/scientific-agent-skillsHugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks. Applies when working with AutoModel, pipelines, tokenizers, generation configs, or TrainingArguments within Transformers.MediaFără avertismente★ 55,6 K↓ —
- convert-word-to-mdgithub/awesome-copilotConverts Word (.docx) documents into Markdown so their contents can be accurately analyzed, summarized, searched, or extracted from. Use this skill whenever the user shares, references, or asks about a .docx file — even if they don't say "convert" or "markdown" explicitly. This includes requests to "read", "summarize", "review", "extract data from", "compare", or "analyze" a Word document, resume, report, contract, or proposal. Always run the bundled conversion script to produce Markdown first; do not attempt to parse .docx content directly or write ad-hoc conversion code. Also use this skill for batch requests involving a whole folder of Word documents. IMPORTANT: When the user references a folder or set of documents containing multiple file types (.pdf, .docx, .xlsx), invoke ALL three sibling skills — convert-pdf-to-md, convert-word-to-md, and convert-excel-to-md — so no file type is silently skipped.DocumenteFără avertismente★ 40,7 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
- portaljs-add-dcatdatopian/portaljsMake a PortalJS portal harvestable by national/EU/US open-data portals — emit standards-compliant DCAT catalog feeds (DCAT 2/3, DCAT-AP, DCAT-US, national profiles) in JSON-LD, Turtle, and RDF/XML at build, with autodiscovery and per-profile conformance checking. Use when a portal needs to be harvested by data.europa.eu, data.gov, or a national open-data catalog.JuridicFără avertismente★ 2,4 K↓ —
- sharksickn33/agentic-awesome-skillsPitch a business idea to a Shark Tank-style panel of Claude sub-agent investors who grill it, hear a founder agent answer, and each go IN or OUT with a practice offer.FinanțeFără avertismente★ 49 K↓ —
- atelier-agent-integrationLeoYeAI/agent-master-skillsRegister as an autonomous agent on Atelier (atelierai.xyz), create content services, poll for paid orders, generate and deliver results, and earn USDC on Solana — fully autonomous. Use when asked to join Atelier, sell content, list services, check orders, deliver work, launch a token, or earn crypto as a creative agent.FinanțeFără avertismente★ 2,2 K↓ —
- einstieg-routingKlotzkette/claude-fuer-deutsches-rechtFür Einstieg und Routing: routet Rolle, Frist, Unterlagen und Fachschritt; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Energierecht.AlteleFără avertismente★ 1,8 K↓ —
- keyword-stuffingcisco-ai-defense/skill-scannerInflate skill discovery through repeated activation keywordsAlteleFără avertismente★ 2,7 K↓ —
- homeofficeKlotzkette/claude-fuer-deutsches-rechtFür Homeoffice: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Berufsrecht Notare.AlteleFără avertismente★ 1,8 K↓ —
- setup-timescaledb-hypertablestimescale/pg-aiguideUse this skill when creating database schemas or tables for Timescale, TimescaleDB, TigerData, or Tiger Cloud, especially for time-series, IoT, metrics, events, or log data. Use this to improve the performance of any insert-heavy table. **Trigger when user asks to:** - Create or design SQL schemas/tables AND Timescale/TimescaleDB/TigerData/Tiger Cloud is available - Set up hypertables, compression, retention policies, or continuous aggregates - Configure partition columns, segment_by, order_by, or chunk intervals - Optimize time-series database performance or storage - Create tables for sensors, metrics, telemetry, events, or transaction logs **Keywords:** CREATE TABLE, hypertable, Timescale, TimescaleDB, time-series, IoT, metrics, sensor data, compression policy, continuous aggregates, columnstore, retention policy, chunk interval, segment_by, order_by Step-by-step instructions for hypertable creation, column selection, compression policies, retention, continuous aggregates, and indexes.DateFără avertismente★ 1,9 K↓ —
- pathway-enrichmentK-Dense-AI/scientific-agent-skillsPerforms pathway and gene-set enrichment analysis on gene lists or ranked gene data and interprets the results. Used when the user has a set of genes (differentially expressed genes from PyDESeq2/Scanpy, CRISPR-screen hits, cluster marker genes, proteomics hits) and wants to know which biological pathways, GO terms, or gene sets are over-represented or enriched. Covers over-representation analysis (ORA / Enrichr / Fisher / hypergeometric), ranked Gene Set Enrichment Analysis (GSEA / preranked), single-sample scoring (ssGSEA/GSVA), and functional profiling via gseapy, g:Profiler, Enrichr libraries, MSigDB, GO, KEGG, Reactome, and WikiPathways — plus gene-ID mapping, choosing the right background universe, multiple-testing correction, redundancy reduction, dotplots/enrichment maps, and publication-ready tables. Use this for "pathway analysis", "enrichment analysis", "GO enrichment", "KEGG/Reactome pathways", "GSEA", "over-representation", "functional annotation", or "what pathways are my genes in".TestareFără avertismente★ 55,6 K↓ —
- gke-ai-troubleshooting-jobset-interruptiongoogle/skillsDiagnoses GKE JobSet interruptions, restarts, and preemptions for AI/ML training workloads autonomously. Use when troubleshooting JobSet restart loops, spot VM preemptions, node readiness failures, host VM issues, or coordinator worker crashes. Don't use for general GKE cluster creation, basic workload deployment, or non-JobSet application issues.OficialDevOpsFără avertismente★ 21,8 K↓ —
- gke-ai-troubleshooting-tpu-dynamic-slices-monitoringgoogle/skillsMonitors, troubleshoots, and manages GKE TPU Dynamic Slices custom resources. Use when checking TPU slice lifecycle states, troubleshooting slice provisioning failures, validating single-slice or multi-slice (JobSet) workload manifests, or safely patching stuck finalizers and disabling the slice controller. Don't use for generic GKE cluster node pool creation or standard non-TPU workload management (use gke-basics or gke-cluster-creation instead).OficialAlteleFără avertismente★ 21,8 K↓ —
- 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
- gke-ai-troubleshooting-tpu-vbar-oomgoogle/skillsDiagnoses and prevents vbar_control_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar_control_agent crashes, memory cgroup OOMs in serial console logs, tpu-device-plugin metrics checksum corruption errors, or custom TPU metrics collection conflicts on GKE TPU v6e nodes. Don't use for general non-TPU container OOM troubleshooting or standard GKE node lifecycle operations.OficialProductivitateFără avertismente★ 21,8 K↓ —
contract-review
cbrock84/headcount
JuridicActualizat 18 oct. 2026
De la autor
Reviews and negotiates commercial agreements — MSAs, SOWs, order forms, NDAs, vendor and data-processing agreements — identifying material risk, proposing positions, and recommending a path rather than listing issues. Use this to review a contract before signature, prepare a negotiation position, build fallback positions and approval thresholds, or assess exposure in terms already agreed.
Instalare
npx skills add cbrock84/headcount --skill contract-review -a claude-code
Se instalează în .claude/skills/contract-review/ · 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