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.
49.492 de skill-uri din 2.391 de depozite · actualizat acum 9 ore
49.490 de skill-uri
- 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↓ —
- influence-psychologywondelai/skillsApply the seven principles of ethical persuasion (reciprocity, commitment, social proof, authority, liking, scarcity, unity) to product design, copy, and sales. Use when the user mentions "social proof", "persuasive copy", "why users dont convert", "ethical persuasion", "reciprocity", "scarcity tactics", "commitment and consistency", "shared identity", "in-group", "make my copy more persuasive", "increase trust", or "get more people to say yes". Also trigger when designing testimonial sections, crafting urgency messaging, or improving trust signals on landing pages. Covers the principles, when each applies, and ethical limits. For deal negotiation tactics, see negotiation. For viral word-of-mouth, see contagious.DesignFără avertismente★ 2,6 K↓ —Apare și în 2 alte depozite
- promoteNouLeoYeAI/agent-master-skillsGraduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement. Use when the user runs /si:promote or asks to make a learned behavior permanent.ProductivitateFără avertismente★ 2,2 K↓ —
- experimental-designK-Dense-AI/scientific-agent-skillsDesigns experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use statistical-analysis.DesignFără avertismente★ 56,1 K↓ —
- literature-reviewK-Dense-AI/scientific-agent-skillsConducts systematic, scoping, and narrative literature reviews using PubMed, arXiv, bioRxiv, Semantic Scholar, and other appropriate sources. Use for research synthesis, reproducible literature searches, screening, citation checking, or preparing Markdown and PDF reviews. Tracks search coverage, records versus studies, and evidence limitations; supports meta-analysis planning but does not supply a meta-analysis engine.InginerieFără avertismente★ 56,1 K↓ —
- opcodeLeoYeAI/agent-master-skillsZero-token execution layer for AI agents. Define workflows once, run them free forever — persistent, scheduled, deterministic. 6 MCP tools over SSE. Supports DAG-based execution, 6 step types (action, condition, loop, parallel, wait, reasoning), 26 built-in actions, ${{}} interpolation, reasoning nodes for human-in-the-loop decisions, and secret vault. Use when defining workflows, running templates, checking status, sending signals, querying workflow history, or visualizing DAGs.ProductivitateFără avertismente★ 2,2 K↓ —
- networkxK-Dense-AI/scientific-agent-skillsCreates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.ȘtiințăFără avertismente★ 56,1 K↓ —Apare și în 1 alt depozit
- spotLeoYeAI/agent-master-skillsBinance Spot request using the Binance API. Authentication requires API key and secret key. Supports testnet and mainnet.InginerieFără avertismente★ 2,2 K↓ —
- 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.TestareFără avertismente★ 56,1 K↓ —Apare și în 1 alt depozit
- cypress-flake-fixergithub/awesome-copilotFind and fix flake-prone anti-patterns in an existing Cypress suite, and APIs removed in Cypress 12 to 16. Bundles a zero-dependency scanner for fixed cy.wait() delays, assigned command return values, async/await, force: true, chaining after actions, one-shot expect() inside .then(), conditional testing, and removed APIs such as Cypress.env(), cy.exec(), cy.server()/cy.route(). Use when asked to fix flaky Cypress tests, remove cy.wait, stabilize or harden a Cypress suite, audit Cypress specs, debug "detached from the DOM" errors, or prepare an upgrade to Cypress 15 or 16.TestareFără avertismente★ 40,8 K↓ —
- idw-ivKlotzkette/claude-fuer-deutsches-rechtFür Sanierungsfähigkeit-Gate für Insolvenzverwaltung: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
- labarchive-integrationK-Dense-AI/scientific-agent-skillsIntegrates with the official LabArchives ELN REST-like API and Inventory API v1. Supports regional endpoint selection, signed-request construction, user authorization and UID flows, local LA container validation, and verified LabArchives integration workflows.InginerieFără avertismente★ 56,1 K↓ —
- ressort-bmdsKlotzkette/claude-fuer-deutsches-rechtFür Ressort-Heranführung BMDS: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Legistik-Werkstatt. Route: ressort-bmds.AlteleFără avertismente★ 1,8 K↓ —
- uncertainty-and-unitsK-Dense-AI/scientific-agent-skillsTracks physical units and propagates measurement uncertainty in scientific calculations using pint and uncertainties. Use for unit conversion and dimensional checking, GUM uncertainty budgets, Type A and Type B evaluation, coverage factors and expanded uncertainty, Monte Carlo propagation, significant-figure and plus-minus reporting, error propagation through curve fits, CODATA constants, auditing Python code for stripped units or broken uncertainty propagation, and order-of-magnitude plausibility checks using dimensionless groups (Reynolds, Peclet, Damkohler, Knudsen, Biot, Womersley), characteristic scales such as diffusion time or Debye length, and observed magnitude ranges. Trigger on "is this number physically reasonable", "sanity check these units", "what regime is this flow in", or a result that looks off by orders of magnitude.ȘtiințăFără avertismente★ 56,1 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★ 56,1 K↓ —Apare și în 2 alte depozite
- hypothesis-generationK-Dense-AI/scientific-agent-skillsFormulates evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Used when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.ȘtiințăFără avertismente★ 56,1 K↓ —
- scenario-soniloscenario-labs/skillsUse when adding sound to a video or generating standalone audio with Sonilo models on Scenario via MCP: text-to-sound-effects, text-to-music, video-to-sound-effects or video-to-music from a clip, scoring silent AI video, foley, ambience, muxed video-to-video variants returning the clip with the new track mixed in, keeping speech while replacing music, or per-segment sound control. Keywords: Sonilo V1.1, SFX, soundtrack, score, keepSpeechVocal, segments, royalty-free.MediaFără avertismente★ 2,2 K↓ —
- dnanexus-integrationK-Dense-AI/scientific-agent-skillsBuilds and operates reproducible genomics workloads on DNAnexus with the dx CLI, dxpy, apps/applets, native workflows, dxCompiler, and Nextflow. Supports DNAnexus data transfers, dxapp.json development, execution monitoring, workflow import, and project automation.ȘtiințăFără avertismente★ 56,1 K↓ —
- scenario-3dscenario-labs/skillsUse when generating or handling 3D assets through the Scenario MCP server, including text-to-3D or image-to-3D meshes, GPT-6 Astra 3D or Claude Opus 5.5 3D, GLB, FBX, OBJ, STL, or VOX files, PBR-textured or game-ready models, voxel models, multi-view reconstruction, editing a mesh by prompt, retexture, remesh, UV unwrap, auto-rigging a biped or quadruped, or retargeting an animation, previewing a mesh in the 3D viewer, or downloading a model for import into Unity, Unreal, Godot, or Blender.MediaFără avertismente★ 2,2 K↓ —
- scenario-reportscenario-labs/skillsUse when a Scenario user wants to report a bug or request a change, on the public tracker at github.com/scenario-labs/skills or by email to [email protected]: turning a failed generation, MCP tool error, or unclear skill into a reproducible report, collecting trace ids with diagnostics_run, stripping keys, signed asset URLs, and personal data, asking before sharing a team or project id, or building a prefilled issue URL. Keywords: file an issue, feature request, feedback.ProductivitateFără avertismente★ 2,2 K↓ —
- scenarioscenario-labs/skillsUse when connecting an AI agent to Scenario (scenario.com) through MCP, or when a task involves generating images, video, 3D, audio, sprites, textures, or game assets. Also when picking a Scenario model, running a LoRA, refining a generation prompt, uploading reference images, waiting on generation jobs, checking credits or quota, hitting Scenario auth, scope, or Forbidden errors, or setting up mcp.scenario.com in Claude Code, Cursor, VSCode, or another agent.MediaFără avertismente★ 2,2 K↓ —
- glanceLeoYeAI/agent-master-skillsCreate, update, and manage Glance dashboard widgets. Use when user wants to: add something to their dashboard, create a widget, track data visually, show metrics/stats, display API data, or monitor usage.InginerieFără avertismente★ 2,2 K↓ —
- seedance-sports-extremeLearnPrompt/awesome-seedanceThe clip lives or dies on the action loop. Write every link from run-up to landing in order, name the physics you want by part, and spend the negative list on flying, hovering and teleporting. Use when the user wants a Seedance 2.5 / 2.0 video prompt for this kind of clip (Sports and extreme stunts; 中文触发词: 体育与极限运动, 体育, 极限运动, 跑酷, 滑板), or asks how published cases of this type were prompted. Read references/cases.md before drafting.MediaFără avertismente★ 2,4 K↓ —
- dsfa-fuer-robotikKlotzkette/claude-fuer-deutsches-rechtFür DSFA für Robotik: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.AlteleFără avertismente★ 1,8 K↓ —
auto-empirical-research-skills
brycewang-stanford/Auto-Empirical-Research-Skills
ȘtiințăActualizat acum 3 zile
De la autor
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows, or an end-to-end run from raw data all the way to a finished Word (.docx) manuscript, without reading the entire repository at once.
Instalare
npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill auto-empirical-research-skills -a claude-code
Se instalează în .claude/skills/auto-empirical-research-skills/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Fără descărcare: licența acestui skill (CC-BY-SA-4.0) nu ne permite să-i redistribuim fișierele. Comenzile de instalare le iau direct de pe GitHub.
La ce are acces
Doar instrucțiuniNu am văzut acces la rețeaLicență: CC-BY-SA-4.0
Verificări de siguranță pe SKILL.md
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Fișiere (23)
- .gitignore
- .gitmodules
- .nojekyll
- .pre-commit-config.yaml
- CHANGELOG.md
- CITATION.cff
- CODE_OF_CONDUCT.md
- CONTRIBUTING.md
- INSTALL.md
- LICENSE
- Makefile
- README-en.md
- încă 11