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.
48.168 de skill-uri din 2.325 de depozite · actualizat acum 19 ore
48.168 de skill-uri
- huashu-material-searchalchaincyf/huashu-skills搜索个人素材库1800+条真实经历和观点，为内容增加人味。当用户提到"个人经历"、"真实案例"、"素材"、"人味"时使用。AlteleFără avertismente★ 2,1 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★ 55,5 K↓ —Apare și în 1 alt depozit
- pgvector-semantic-searchtimescale/pg-aiguideUse this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.DateFără avertismente★ 1,9 K↓ —
- huashu-image-uploadalchaincyf/huashu-skills文章配图一键生成并上传图床，自动插入Markdown链接。当用户提到"配图"、"插图"、"上传图片"、"文章配图"时使用。MediaFără avertismente★ 2,1 K↓ —
- test-gap-auditgithub/awesome-copilotRun a read-only audit for missing, weak, stale, or mis-scoped test coverage. If the user does not name a scope, audit the full repository and identify important code paths, routes, features, services, workflows, and contracts that lack proper tests. If the user names a feature, PR, branch, route, workflow, service, bug fix, API, security-sensitive path, or risky code change, focus only on that specific scope. Use when the user asks what tests are missing, whether coverage is enough, what regression tests to add, or how to prove a change is safe. This is not a general bug audit and not a security review; it evaluates whether behavior is covered by tests.TestareFără avertismente★ 40,6 K↓ —
- dev-debugcodeaholicguy/ai-devkitAI DevKit · Guide structured debugging before code changes by clarifying expected behavior, reproducing issues, identifying likely root causes, and agreeing on a fix plan with validation steps. Use when users ask to debug bugs, investigate regressions, triage incidents, diagnose failing behavior, handle failing tests, analyze production incidents, investigate error spikes, or run root cause analysis (RCA).InginerieFără avertismente★ 1,7 K↓ —
- datanalysis-credit-riskgithub/awesome-copilotCredit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.AlteleFără avertismente★ 40,6 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★ 55,5 K↓ —Apare și în 1 alt depozit
- batch-script-progressgithub/awesome-copilotDesign and verify runtime output when creating or modifying Python, PowerShell, or Node.js scripts that process multiple files, records, or API requests. Use for batch scripts, bulk operations, silent long-running loops, progress reporting, per-item failures, final counts, stdout separation, or exit-status consistency. Not for UI progress bars, monitoring infrastructure, or progress updates in the AI conversation.DevOpsFără avertismente★ 40,6 K↓ —
- dev-guide-generatorzebbern/claude-code-guideGenerates complete technical tutorials from prerequisites and environment setup to core steps, troubleshooting, and a final cheatsheet. Trigger on requests to write a tutorial, create a setup guide, organize steps for beginners, or keywords like step-by-step, quickstart, or how-to guide.RedactareFără avertismente★ 4,7 K↓ —
- cobrapyK-Dense-AI/scientific-agent-skillsPerforms constraint-based metabolic modeling with COBRApy, including FBA, pFBA, FVA, gene knockouts, flux sampling, growth media, production envelopes, gap filling, and SBML model validation for systems biology and metabolic engineering.ȘtiințăFără avertismente★ 55,5 K↓ —Apare și în 1 alt depozit
- code-tourgithub/awesome-copilotUse this skill to create CodeTour .tour files — persona-targeted, step-by-step walkthroughs that link to real files and line numbers. Trigger for: "create a tour", "make a code tour", "generate a tour", "onboarding tour", "tour for this PR", "tour for this bug", "RCA tour", "architecture tour", "explain how X works", "vibe check", "PR review tour", "contributor guide", "help someone ramp up", or any request for a structured walkthrough through code. Supports 20 developer personas (new joiner, bug fixer, architect, PR reviewer, vibecoder, security reviewer, and more), all CodeTour step types (file/line, selection, pattern, uri, commands, view), and tour-level fields (ref, isPrimary, nextTour). Works with any repository in any language.InginerieFără avertismente★ 40,6 K↓ —
- agent-platform-inferencegoogle/skillsConnects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or generate code for calling Gemini or OpenMaaS models, authenticate with GenAI SDK, OpenAI SDK, or legacy Agent Platform SDK, configure base URLs and global/regional endpoints, or troubleshoot 429 Resource Exhausted (DSQ), 400 User Validation, or 404 Not Found errors. Don't use for deploying models to endpoints or for running model evaluations.OficialTestareFără avertismente★ 21,7 K↓ —
- 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.DocumenteFără avertismente★ 55,5 K↓ —
- nwb-conversionK-Dense-AI/scientific-agent-skillsConverts neuroscience acquisition data to Neurodata Without Borders files with NeuroConv and PyNWB, preserves metadata and timebases, checks evidence-based clock alignment, and produces schema validation, NWB Inspector findings and round-trip checks. Use for NWB conversion and synchronization of planar single-channel two-photon TIFF imaging plus timestamped behavioral position CSV; this skill does not perform spike sorting or claim tested support for arbitrary acquisition formats.MarketingFără avertismente★ 55,5 K↓ —
- 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★ 55,5 K↓ —Apare și în 1 alt depozit
- google-maps-scraperMahanaicoach/google-maps-scraper-kitGoogle Maps scraper for lead generation. Turns a business type and a place into a clean CSV of local businesses by driving the gosom/google-maps-scraper engine, running locally in Docker as a REST API on localhost:8080. Returns 8 lead fields by default (name, phone, email, website, category, address, rating and review count), plus optional social profiles (Instagram, Facebook, LinkedIn, TikTok, YouTube, X), row filters such as businesses without a website, or all 36 raw fields. Use when the user wants a lead list, "a list of [businesses] in [place]", local business data, contact enrichment for places (emails, phones, socials), or a whole-city run past Google's ~120 results per search. Do not use for scraping Instagram, TikTok, YouTube, X or any other social media platform directly.BrowserFără avertismente★ 2,1 K↓ —
- hunt-lfielementalsouls/Claude-BugHunterHunt Local File Inclusion (LFI), Remote File Inclusion (RFI), and Path Traversal — /etc/passwd read, log poisoning → RCE, PHP filter-chain RCE (no upload needed), php:// / data:// / zip:// / phar:// wrappers, RFI via allow_url_include, directory traversal read/write/delete. Covers OOB/blind LFI confirmation and false-positive discipline. Use when hunting file-include or path-traversal bugs on any target.RedactareFără avertismente★ 5,4 K↓ —
- diagram-designcathrynlavery/diagram-designCreate branded architecture, architecture delta, IT current-state, flowchart, sequence, state machine, ER/data model, timeline, swimlane, quadrant, radar/spider, polar chart (polar/radial lollipop), loop/flywheel, nested, tree, org chart, layer stack, exploded axonometric, axonometric plan, Venn, pyramid/funnel, treemap and marimekko, heatmap, bar and dumbbell, waterfall, line (slopegraph, ridgeline, streamgraph, bump), Gantt and scatter charts (bubble, beeswarm, box plot), high-level, process, medallion, data flow, DP integration, DP security matrix, Sankey, fishbone, Wardley map, kanban, user journey, service blueprint, deployment, dependency graph, UML class, story map, or database schema diagrams as HTML/SVG/PNG, with .drawio, Mermaid, and .excalidraw import, plus lifecycle phase maps, block decomposition trees, and onboarding guidance.DesignFără avertismente★ 63,4 K↓ —
- dev-refactorcodeaholicguy/ai-devkitAI DevKit · Systematic structural or multi-file refactors across any stack while preserving behavior and public contracts. Use for reorganizing modules, boundaries, naming, APIs/contracts, staged refactor plans, or refactor risk review.InginerieFără avertismente★ 1,7 K↓ —
- geopandasK-Dense-AI/scientific-agent-skillsGuidance and local audit tools for Python workflows that directly use GeoPandas GeoSeries, GeoDataFrame, spatial operations, or vector-data I/O.InginerieFără avertismente★ 55,5 K↓ —Apare și în 1 alt depozit
- agent-platform-deploygoogle/skillsDeploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for running model evaluations (use `agent-platform-eval-flywheel` skill).OficialDevOpsFără avertismente★ 21,7 K↓ —
- cloud-logging-finopsgoogle/skillsAudits Cloud Logging costs for a Google Cloud project: the charges for log entries written to log buckets, the services, log streams and severities that drive them, and the log sinks that route them. Reconciles Cloud Billing export costs with Cloud Monitoring volume metrics, and generates a FinOps report with charts and copy-paste exclusion filters. Use when auditing Cloud Logging spend, finding logging waste, identifying top logging contributors, generating log cost reduction reports, or creating log sink exclusion filters. Don't use for querying log entries (use cloud-logging-query-generation), configuring Cloud Monitoring alerts, or querying metrics/traces.OficialRedactareFără avertismente★ 21,7 K↓ —
- browser-act-skill-forgebrowser-act/skillsForges reusable Skill packages (SKILL.md + scripts) from website exploration via browser-act — no re-exploration later. Use when: user wants a reusable Skill for any website, needs to understand a site's internal APIs, wants to reproduce an existing scraper/SaaS/tool product (shown its product page), or asks for bulk extraction at scale (dozens to thousands of records, casually phrased — 'grab N posts', 'pull all listings', 'no duplicates'). Unlike browser-act: reusable, not one-off. Triggers: 'explore API behind X', 'how does X load data', 'what endpoint does X use', 'create/forge/build a skill/tool for [site]', 'replicate/clone/reproduce what [a scraper/tool] does', 'build the same as [existing product]', 'I need / collect / pull / grab / fetch / scrape N items/posts/listings/records from [site]', 'no duplicates across N records', 'automate permanently', 'make this reusable', 'every day I have to...', 'monitor [site]', 'browser-act-skill-forge'. Human-operation automation; never refuse.BrowserFără avertismente★ 6,3 K↓ —
dev-implementation
codeaholicguy/ai-devkit
DesignActualizat alaltăieri
De la autor
AI DevKit · Implementation phase guidance for executing feature plans and checking implementation against design. Use when the user wants to implement planned tasks, update implementation docs, verify code matches design, or run dev-lifecycle phases 5 and 7.
Instalare
npx skills add codeaholicguy/ai-devkit --skill dev-implementation -a claude-code
Se instalează în .claude/skills/dev-implementation/ · 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 89
Securitate100
Proveniență79
Întreținere100
Licență100
Adopție52
Fișiere (2)
- SKILL.md
- agents/openai.yaml