Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
49,399 skills from 2,375 repositories · updated 12 minutes ago
49,399 skills
- doca-rdmaNVIDIA/skillsRDMA data movement on NVIDIA BlueField/ConnectX NICs (RoCE/InfiniBand) with DOCA RDMA, instead of hand-written libibverbs/rdma_cm. Use when the user moves data between processes or hosts over the NIC, or hits "one-sided read returns permission denied", "completions never arrive after submit", "connection callback never fires", atomic compare-and-swap over RoCE, or DOCA_ERROR_FULL on the send queue under burst, even without naming DOCA RDMA. Covers bringing up an RDMA context on a doca_dev, connection methods (RDMA CM, bridge/OOB, or gRPC exchange of doca_rdma_export()), the eleven task types (Send/Receive/Send-Imm, Read/Write/Write-Imm, Atomic CmpSwap/FetchAdd, Get/Set/Add Remote Sync Event), matching mmap + RDMA permissions, queue and connection sizing, doca_rdma_cap_* queries, and DOCA_ERROR_* from RDMA calls. Raw QP/verbs control belongs to doca-verbs. Refuse and route elsewhere for general RDMA / ibverbs theory (queue pairs, MRs, RoCE vs IB), installing DOCA itself, or non-RDMA DOCA libraries.WritingNo warnings★ 3.8K↓ —
- pydeseq2K-Dense-AI/scientific-agent-skillsPerforms bulk RNA-seq differential expression analysis with PyDESeq2, including count validation, formula designs, explicit contrasts, Wald tests, FDR correction, coefficient-matched LFC shrinkage, and result visualization. Use for PyDESeq2 or Python DESeq2 workflows with biological replicates.TestingNo warnings★ 56K↓ —Also in 1 other repo
- 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.PlanningNo warnings★ 2.4K↓ —
- chief-technology-officercbrock84/headcountOwns architecture, engineering delivery, infrastructure, data platform, and internal systems. Use this for build-versus-buy calls, technology selection, architectural direction, engineering capacity and delivery risk, technical debt tradeoffs, platform and tooling decisions, or when a technical choice has business consequences that need stating in business terms. Also use to judge whether a technical plan is sound before it is committed to.DevOpsNo warnings★ 2.6K↓ —
- statistical-analysisK-Dense-AI/scientific-agent-skillsGuided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting. Use whenever a user wants to compare groups, test a hypothesis, analyze experimental or survey data, check statistical assumptions, compute required sample sizes, or write up results - even if they never name a specific test. Covers t-tests, ANOVA, chi-square, correlation, regression, non-parametric and Bayesian methods. For low-level model APIs, see the statsmodels and pymc skills.TestingNo warnings★ 56K↓ —
- 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.TestingNo warnings★ 56K↓ —
- imagensickn33/agentic-awesome-skillsAI image generation skill powered by Google Gemini, enabling seamless visual content creation for UI placeholders, documentation, and design assets.DesignNo warnings★ 49.1K↓ —
- peer-reviewK-Dense-AI/scientific-agent-skillsPrepares evidence-bounded, constructive peer-review drafts and structured manuscript assessments. Supports authorized review of scientific manuscripts, protocols, preprints, or research proposals; reporting-guideline selection; claim–evidence checks; methods, statistics, reproducibility, ethics, figure/table, and citation critique; or revision-response planning.EngineeringNo warnings★ 56K↓ —
- huashu-proofreadingalchaincyf/huashu-skills三遍审校降低AI检测率，让文章更有人味。当用户提到"AI味太重"、"像AI写的"、"降低AI检测率"、"审校"、"自然一些"时使用。WritingNo warnings★ 2.2K↓ —
- 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.MediaNo warnings★ 56K↓ —
- 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.ScienceNo warnings★ 56K↓ —
- 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.FinanceNo warnings★ 49.1K↓ —
- navigation-3android/skillsLearn how to install and migrate to Jetpack Navigation 3, and how to implement features and patterns such as deep links, multiple backstacks, scenes (dialogs, bottom sheets, list-detail, two-pane, supporting pane), conditional navigation (such as logged-in navigation versus anonymous), returning results from flows, integration with Hilt, ViewModel, Kotlin, and view interoperability.OfficialOtherNo warnings★ 10.3K↓ —
- copilot-usage-metricsgithub/awesome-copilotRetrieve and display GitHub Copilot usage metrics for organizations and enterprises using the GitHub CLI and REST API.EngineeringNo warnings★ 40.8K↓ —
- slideopssickn33/agentic-awesome-skillsTurn a repository into a cited HTML slide deck and detect the day it drifts from the code. Citations record file, lines, and hash; a stdlib check reports CURRENT, MOVED, or CHANGED.DocumentsNo warnings★ 49.1K↓ —
- 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.DataNo warnings★ 1.9K↓ —
- deepspot-mK-Dense-AI/scientific-agent-skillsGenerates transcriptome-wide virtual spatial transcriptomics from H&E histology with DeepSpot-M. Used for predicted log1p-CPM expression from 224x224 tiles at about 20x, querying the released protein-coding gene panel by symbol, and whole-slide prediction after resolution-aware tiling with histolab.DocumentsNo warnings★ 56K↓ —
- aws-penetration-testingzebbern/claude-code-guideThis skill should be used when the user asks to "pentest AWS", "test AWS security", "enumerate IAM", "exploit cloud infrastructure", "AWS privilege escalation", "S3 bucket testing", "metadata SSRF", "Lambda exploitation", or needs guidance on Amazon Web Services security assessment.TestingNo warnings★ 4.7K↓ —
- marketing-campaign-plannercbrock84/headcountDesigns a coordinated multi-channel campaign or product launch around one story — objective, message, channel sequencing, timeline, assets, and the checklist that gets it out the door. Use this to plan a launch or campaign, sequence a go-to-market push, pressure-test a campaign before committing budget, or turn a product change into a coordinated set of activity. For ongoing channel programs rather than a bounded push, use `marketing-planning`.MarketingNo warnings★ 2.6K↓ —
- payroll-operationscbrock84/headcountRuns the pay cycle so it is right, on time, and provable — the calendar and cutoffs, what feeds pay from the HRIS and time systems, gross-to-net and the deductions in it, multi-jurisdiction registration and tax filing, off-cycle payments and corrections, and the reconciliation to the general ledger. Use this to design or audit a payroll process, work out what happens when someone is paid wrong, or understand what changes when you hire in a new state or country.DesignNo warnings★ 2.6K↓ —
- epo-quellenkarteKlotzkette/claude-fuer-deutsches-rechtFür Epo Quellenkarte: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- scenario-meshyscenario-labs/skillsUse when creating or refining 3D assets with Meshy models on Scenario via MCP: image-to-3D from one photo or 1-4 multi-view angles, text-to-3D, retexturing an existing GLB, remeshing to a target polycount, UV unwrapping, auto-rigging a humanoid character, or applying a library animation clip. Keywords: Meshy 7 and Meshy 6, Ultra mode, Smart Topology, PBR maps, texture prompt, triangle or quad topology, game-ready mesh, A-pose, T-pose, GLB pipeline.MediaNo warnings★ 1.9K↓ —
- infographicsK-Dense-AI/scientific-agent-skillsCreates and reviews infographics with Nano Banana 2 via OpenRouter. Use for statistical summaries, timelines, comparisons, processes, and visual explanations with supplied data or optional Sonar research. Supports ten layouts, eight style presets, reference images, and accessible palette starting points.ScienceNo warnings★ 56K↓ —
- seedance-car-vehicleLearnPrompt/awesome-seedanceThe machine has to stay one machine while the camera does all the work. Lock the vehicle part by part, then fill the runtime with a numbered cut list that moves the camera every second. Use when the user wants a Seedance 2.5 / 2.0 video prompt for this kind of clip (Cars and vehicles at speed; 中文触发词: 汽车与载具速度片, 汽车, 赛车, 摩托, 载具), or asks how published cases of this type were prompted. Read references/cases.md before drafting.MediaNo warnings★ 2.4K↓ —
energievertraege
Klotzkette/claude-fuer-deutsches-recht
OtherUpdated yesterday
From the author
Für Energie-Verträge — Strukturierung und Prüfung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
Install
npx skills add Klotzkette/claude-fuer-deutsches-recht --skill energievertraege -a claude-code
Installs to .claude/skills/energievertraege/ · Each command fetches the skill straight from GitHub with the open skills CLI.
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Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
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Instructions onlyNo network use seenLicence: APACHE-2.0
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