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.
49,492 skills from 2,391 repositories · updated 9 hours ago
49,492 skills
- 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.DesignNo warnings★ 2.6K↓ —Also in 2 other repos
- output-waehlenKlotzkette/claude-fuer-deutsches-rechtFür Output wählen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: Insolvenzrecht.OtherNo warnings★ 1.8K↓ —
- neuropixels-analysisK-Dense-AI/scientific-agent-skillsAnalyzes Neuropixels extracellular recordings end-to-end with SpikeInterface. Covers loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift/motion correction, Kilosort4 (and CPU) spike sorting, quality metrics, and unit curation (threshold-based, model-based UnitRefine, and AI-assisted visual review). Use when working with Neuropixels 1.0/2.0 recordings, spike sorting, or extracellular electrophysiology analysis.EngineeringNo warnings★ 56.1K↓ —
- review-paperpedrohcgs/claude-code-my-workflowA ready-to-fork Claude Code template for academics using LaTeX/Beamer + R. Multi-agent review, quality gates, adversarial QA, and replication protocols.ScienceNo warnings★ 1.7K↓ —
- scenario-klingscenario-labs/skillsUse when generating or editing video with Kling models on Scenario via MCP: text-to-video, image-to-video with first and last frames, multi-shot sequences with per-shot prompts, consistent characters via elements and reference images, prompt-based video editing, motion transfer from a driving video (motion control, mocap), lipsync to audio or text, talking avatars, native audio and dialogue, or picking 720p, 1080p, or 4K tiers. Keywords: Kling V3, O1, 2.6, Omni, Kuaishou, T2V, I2V, V2V.MediaNo warnings★ 2.2K↓ —
- umap-learnK-Dense-AI/scientific-agent-skillsApplies UMAP-learn to nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows.OtherNo warnings★ 56.1K↓ —
- stable-baselines3K-Dense-AI/scientific-agent-skillsTrains and evaluates single-agent reinforcement learning with Stable Baselines3 (PPO, SAC, DQN, TD3, DDPG, A2C), Gymnasium custom environments, vectorized rollouts, callbacks, and checkpoint normalization. Applies to reproducible RL experiments, continuous control, discrete actions, and SB3-Contrib recurrent or masked policies.OtherNo warnings★ 56.1K↓ —
- mini-context-graphgithub/awesome-copilotA persistent, compounding knowledge base combining Karpathy's LLM Wiki pattern with a structured knowledge graph. Ingest documents once — the LLM writes wiki pages, extracts entities/relations into the graph, and stores raw content for evidence retrieval. Knowledge accumulates and cross-references; it is never re-derived from scratch.ProductivityNo warnings★ 40.8K↓ —
- alphagenomeK-Dense-AI/scientific-agent-skillsLooks up precomputed AlphaGenome Atlas effects for any GRCh38 single-nucleotide variant (AVI score with Phred and 18 SHAP feature attributions, plus raw and quantile scores for RNA-seq, DNase, ATAC, ChIP-TF, ChIP-histone, CAGE, PRO-cap, splicing, polyadenylation and contact-map tracks), scores variants or scans windows on demand with the AlphaGenome model for human and mouse (variant scoring, in silico mutagenesis, REF-versus-ALT track prediction), and builds Atlas website deep links. Use when the user mentions AlphaGenome, AlphaGenome Atlas, AVI or AlphaGenome Variant Impact, DeepMind variant effect prediction, or wants to prioritise or mechanistically interpret non-coding, regulatory, splicing, enhancer, promoter, or chromatin-accessibility effects of SNVs from a VCF, credible set, or region. Research use only; not a clinical tool.ScienceNo warnings★ 56.1K↓ —
- industriekundenKlotzkette/claude-fuer-deutsches-rechtFür Industriekunden — Sonderregelungen: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.OtherNo warnings★ 1.8K↓ —
- display-glasses-with-jetpack-compose-glimmerUpdatedandroid/skillsProvides guidelines for developing projected Android XR apps for display glasses using the Jetpack Compose Glimmer UI toolkit. Covers Glimmer design principles, workflows, and interaction models for the glasses form factor. Use this skill to build an Android XR Augmented Experience app with Jetpack Compose Glimmer. Don't use for audio-only AI glasses without a display, non-glasses Android XR headsets (spatial panels or 3D volumes with Jetpack Compose for XR), or phone and tablet Material 3 UIs.OfficialDesignNo warnings★ 10.3K↓ —
- md-to-docxgithub/awesome-copilotConvert Markdown files to professionally formatted Word (.docx) documents with embedded PNG images — pure JavaScript, no external tools requiredDocumentsNo warnings★ 40.8K↓ —
- hgb-red-teamKlotzkette/claude-fuer-deutsches-rechtFür HGB Red-Team: prüft Ergebnis, Beweislast und Gegenposition; Ergebnis: Gegenprüfung mit Beweis- und Fristencheck.OtherNo warnings★ 1.8K↓ —
- portaljs-add-geodatopian/portaljsAuto-ingest a geospatial file (GeoJSON, Shapefile, GeoPackage, KML/KMZ, FlatGeobuf, CSV-with-geometry) into a PortalJS portal on the user's own machine, with no server. Normalizes CRS to EPSG:4326, derives a PMTiles render tier and a GeoParquet query tier, pushes all three artifacts to Cloudflare R2 via Git LFS, and appends one dual-tier datasets.json entry the showcase auto-renders. Use when the source is a vector geo format that needs a map or spatial-query view.DevOpsNo warnings★ 2.4K↓ —
- scikit-survivalK-Dense-AI/scientific-agent-skillsBuilds, evaluates, and audits right-censored or competing-risk survival workflows with scikit-survival, including leakage-safe preprocessing, model selection, probability prediction, and censoring-aware metrics.OtherNo warnings★ 56.1K↓ —
- gke-compute-classesgoogle/skillsConfigures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto Provisioning configuration or general GKE cluster creation.OfficialPlanningNo warnings★ 21.9K↓ —
- unpinned-dependencycisco-ai-defense/skill-scannerDemonstrate a package dependency that is not locked to an exact versionOtherNo warnings★ 2.7K↓ —
- 007sickn33/agentic-awesome-skillsSecurity audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.SecurityNo warnings★ 49.1K↓ —
- concealed-actioncisco-ai-defense/skill-scannerConceal an agent action from the user who requested the taskProductivityNo warnings★ 2.7K↓ —
- 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.DataNo warnings★ 1.9K↓ —
- find-hypertable-candidatestimescale/pg-aiguideUse this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. **Trigger when user asks to:** - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy **Keywords:** hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data.DataNo warnings★ 1.9K↓ —
- 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.PlanningNo warnings★ 56.1K↓ —Also in 2 other repos
- cirqK-Dense-AI/scientific-agent-skillsGoogle quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.DesignNo warnings★ 56.1K↓ —Also in 2 other repos
- scvi-toolsK-Dense-AI/scientific-agent-skillsFits probabilistic models for single-cell omics, including scVI batch integration, scANVI annotation, totalVI CITE-seq, MultiVI RNA/ATAC integration, and posterior differential expression. Use for generative modeling, reference mapping, multimodal analysis, or model-based uncertainty; use scanpy for standard preprocessing and exploratory analysis.OtherNo warnings★ 56.1K↓ —
deepchem
K-Dense-AI/scientific-agent-skills
ScienceUpdated 3 days ago
From the author
Builds molecular property prediction and MoleculeNet workflows with DeepChem, including SMILES featurization, scaffold or grouped holdouts, masked labels, graph models and explicit pretrained encoder transfer. Used for ADMET, toxicity, solubility and chemistry ML when DeepChem data/model contracts and scientific validation are needed.
Install
npx skills add K-Dense-AI/scientific-agent-skills --skill deepchem -a claude-code
Installs to .claude/skills/deepchem/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Runs bundled scriptsUses the networkLicence: MIT
Safety checks on SKILL.md
- Ships scripts we have not reviewedLow
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Provenance95
Maintenance100
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Files (10)
- SKILL.md
- references/api_reference.md
- references/core_capabilities.md
- references/review.md
- references/typical_workflows.md
- references/workflows.md
- scripts/_common.py
- scripts/graph_neural_network.py
- scripts/predict_solubility.py
- scripts/transfer_learning.py