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multi-model-validation
This skill orchestrates parallel execution of multiple AI models (Grok, Gemini, GPT-5, etc.) for code validation and review. It provides 3-5x speedup through concurrent processing, enforces performance statistics collection, and includes dynamic model discovery. Version 3.1.0 adds mandatory checklist enforcement and session-based workspaces.
neurokit2
This skill provides Python-based processing for physiological signals like ECG, EEG, and EDA. It handles cleaning, feature extraction, and analysis for heart rate variability, brain activity patterns, and autonomic responses. The toolkit includes event-related analysis, multi-modal integration, and complexity metrics for research applications.
etetoolkit
This skill provides Python-based tools for phylogenetic tree analysis using the ETE library. It handles tree file formats (Newick/NHX), detects evolutionary events like duplications and speciations, integrates with NCBI taxonomy, and generates publication-quality visualizations in PDF/SVG formats. Includes both Python API examples and command-line scripts.
chembl-database
This skill provides programmatic access to the ChEMBL database for medicinal chemistry research. It enables searching bioactive molecules, retrieving bioactivity data (IC50, Ki), finding inhibitors, and performing SAR studies through Python client integration with clear query examples.
project-workflow
Nine integrated slash commands for complete project lifecycle: /explore-idea, /plan-project, /plan-feature, /wrap-session, /continue-session, /workflow, /release, /brief, /reflect. Use when starting projects, managing sessions across context windows, capturing learnings, or preparing releases. Saves 35-55 minutes per lifecycle.
protocolsio-integration
This skill provides detailed guidance for interacting with the protocols.io API v3. It covers authentication, protocol lifecycle management, file handling, and workspace organization. The documentation includes specific endpoint examples, parameter details, and common integration patterns for scientific protocol management.
specification-management
A well-structured specification management system that automates document workflow tracking with auto-incrementing IDs, decision logging, and phase transitions for PRD→SDD→PLAN processes.
hypothesis-generation
This skill provides a structured template for generating and testing scientific hypotheses. It guides users through literature review, hypothesis formulation, experimental design, and prediction making. The output follows a standardized format suitable for research proposals or study planning.
scene-structure-techniques
A structured prompt for fiction writers to plan individual scenes using the scene-sequel framework. It guides users through defining character goals, conflicts, and resolutions, then generates a detailed scene outline with beats, tension management, and integration notes for writing tools.
content-research-writer
Acts as a writing partner that helps structure outlines, research topics with citations, improve hooks, and provide section-by-section feedback. Guides users through complete writing workflows for articles, tutorials, and newsletters while preserving their unique voice.
competitive-intelligence
A comprehensive competitive intelligence framework with clear processes for landscape mapping, feature comparison, win/loss analysis, battlecard creation, and ongoing tracking.
qutip
This skill wraps the QuTiP library for simulating quantum systems, focusing on open quantum systems with master equations and Lindblad dynamics. It provides specific examples for quantum optics, cavity QED, and decoherence studies, with clear boundaries on when to use it versus circuit-based quantum computing libraries.
cellxgene-census
This skill provides programmatic access to the CELLxGENE Census, a large single-cell genomics database with 61M+ cells. It enables querying expression data by cell type, tissue, or disease, integrates with PyTorch and scanpy, and supports both in-memory and out-of-core processing for different query sizes.
medchem
A Python library for applying medicinal chemistry rules and structural alerts to filter compound libraries. It implements established rules like Lipinski's Rule of Five, PAINS filters, and Lilly demerits, with batch processing and command-line interface support for drug discovery workflows.
fda-database
This skill provides Python-based access to the FDA's openFDA API, enabling queries for drug adverse events, medical device clearances, food recalls, and substance identification. It includes specific methods for different FDA data categories and demonstrates practical use cases for regulatory analysis and safety research.
deepchem
Provides DeepChem integration for molecular property prediction, drug discovery, and materials science. Includes data loaders for SMILES/SDF files, multiple featurization methods (fingerprints, graphs, descriptors), and pre-built models for ADMET/toxicity prediction. Offers workflow examples for GNNs, transfer learning, and molecule generation.
new-track
This skill guides users through creating structured development tracks with specifications and hierarchical plans. It enforces a spec-before-plan workflow, reads project context files, and integrates with a TodoWrite system for progress tracking. The interactive Q&A approach ensures requirements are captured before planning begins.
tester-detective
This skill uses AST callers analysis via claudemem to identify test coverage gaps, find which tests call specific functions, and detect untested code. It provides concrete commands for test discovery and prioritizes high-PageRank untested functions as critical issues.
implementation-planning
A skill that generates structured implementation plans following TDD principles. It breaks down features into phases with Prime, Test, Implement, Validate cycles, links tasks to PRD/SDD specifications, and identifies parallel work opportunities. Focuses on activities and dependencies without time estimates.
hmdb-database
Provides access to the Human Metabolome Database with 220K+ metabolite entries. Enables searching by name, ID, or structure to retrieve chemical properties, biomarker data, NMR/MS spectra, and pathway information for metabolomics research and metabolite identification tasks.
biorxiv-database
This skill provides Python tools to search and retrieve preprints from the bioRxiv database. It supports keyword, author, and date-range searches, returns structured JSON metadata, and enables PDF downloads. It's useful for literature reviews and tracking recent publications in life sciences.
project-planning
Generate structured planning docs for web projects with context-safe phases, verification criteria, and exit conditions. Creates IMPLEMENTATION_PHASES.md plus conditional docs. Use when: starting new projects, adding major features, or breaking large work into manageable phases.
gene-database
This skill provides Python scripts to query NCBI's Gene database via E-utilities and Datasets APIs. It enables searching by symbol/ID, retrieving gene metadata (RefSeqs, GO terms, locations), batch processing, and linking to related databases like ClinVar and PubMed. It handles rate limits and includes practical examples for common bioinformatics workflows.
research-executor
Automates academic research using a 7-phase methodology with parallel agents for web, academic, and verification tasks. Enforces strict citation formats and produces structured reports with source validation. Useful for systematic literature reviews and evidence-based analysis.