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openmodelsrun/skills

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OpenModels Skills Registry

A community-maintained catalog of AI agent skills — structured, searchable, and integrated with the OpenModels ecosystem.

What are Skills?

Skills are structured definitions of tasks that AI agents excel at. Each skill includes:

  • Description — what the skill does and when to use it
  • Recommended models — which LLMs work best (linked to OpenModels registry)
  • Example prompts — ready-to-use templates
  • Metadata — category, complexity, modalities, compatible tools

Skills help developers discover what AI agents can do and choose the right model for each task.

Quick Start

Browse skills on openmodels.run/skills or explore the YAML files directly:

skills/
├── code-review.yaml
├── unit-test-generation.yaml
├── refactoring-assistant.yaml
├── debugging-assistant.yaml
├── api-design.yaml
├── sql-generation.yaml
├── schema-design.yaml
├── documentation-generator.yaml
├── security-audit.yaml
├── accessibility-review.yaml
├── performance-optimization.yaml
├── ci-cd-pipeline.yaml
├── commit-message-writer.yaml
├── prompt-engineering.yaml
├── code-translation.yaml
├── regex-builder.yaml
├── ...
└── 75 skills total (see full list in skills/ directory)

New in v0.1.7

  • infrastructure-as-code — Terraform/CDK/Pulumi IaC configuration generation
  • threat-modeling — STRIDE analysis and security threat assessment
  • video-analysis — video content analysis with scene detection and annotation
  • api-load-testing — k6/Locust load testing script generation
  • audio-transcription — audio transcription with speaker diarization
  • contract-analysis — legal contract review and risk assessment
  • incident-response — SRE runbooks and postmortem generation
  • mobile-app-prototyping — SwiftUI/Compose/React Native prototyping
  • design-system-generator — design tokens and component specifications
  • data-pipeline-builder — Airflow/dbt/Spark ETL pipeline generation

ASO Skills (new in v0.1.5)

  • aso-audit — full App Store health check with 10-dimension scored report card (0–100)
  • aso-competitor-analysis — keyword gaps, creative strategy, ratings, and monetization benchmarking
  • aso-keyword-research — keyword discovery, opportunity scoring, and strategy bucketing
  • aso-metadata-optimization — title, subtitle, keyword field, and description writing for iOS and Android

Scientific & Data Skills (new in v0.1.4)

  • literature-review — systematic reviews across PubMed, arXiv, bioRxiv
  • hypothesis-generation — scientific hypothesis formulation and experimental design
  • bioinformatics-pipeline — scRNA-seq, Scanpy, pathway analysis, variant calling
  • molecular-analysis — cheminformatics, RDKit, drug-likeness, ADMET
  • scientific-visualization — publication-quality figures for journals
  • network-graph-analysis — NetworkX, community detection, GNN
  • time-series-forecasting — ARIMA, Prophet, LSTM, anomaly detection
  • ml-experiment-tracker — MLflow, W&B, Optuna, hyperparameter tuning
  • scientific-writing — manuscripts, grants, IMRaD, peer review
  • geospatial-analysis — GeoPandas, GIS, remote sensing, spatial stats

Skill Format

Each skill is a YAML file validated against a JSON Schema:

id: code-review
name: Code Review
description: >
 Automated code review with actionable feedback...
category: development
tags:
 - code-quality
 - automation
author:
 name: OpenModels Community
 github: openmodelsrun
recommended_models:
 - claude-opus-4-6
 - gpt-5
 - gemini-2-5-pro
min_context_window: 32000
modalities:
 input: [code, text]
 output: [text, code]
complexity: intermediate
use_cases:
 - Pull request review automation
 - Code quality gates in CI
example_prompt: |
 Review the following code for bugs, performance, and style...
related_skills:
 - unit-test-generation
 - security-audit
compatible_tools:
 - claude-code
 - cursor
 - kiro
 - any
created_at: "2026年05月24日T10:00:00.000Z"
updated_at: "2026年05月24日T10:00:00.000Z"

Categories

Category Description
💻 development Writing, reviewing, and improving code
✍️ writing Generating and transforming written content
📊 data Analyzing, transforming, and visualizing data
🔍 research Gathering and synthesizing information
🎨 creative Brainstorming and creative problem-solving
⚙️ ops Deployment, CI/CD, and infrastructure
🧪 testing Test generation and quality assurance
🔒 security Vulnerability detection and hardening
🚀 productivity Workflow automation and efficiency

Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

Quick steps:

  1. Fork this repository
  2. Create a new YAML file in skills/ following the schema
  3. Run validation: python validate.py
  4. Submit a pull request

Validation

All skills are validated against JSON Schema on every PR:

pip install -r requirements.txt
python validate.py

Validation checks:

  • YAML syntax
  • Schema conformance (required fields, types, enums, patterns)
  • No duplicate IDs
  • Filename matches the id field
  • Related skills reference existing IDs

Integration with OpenModels

Skills are ingested into the OpenModels platform and available via:

  • Web UI — browse, filter, and search at openmodels.run/skills
  • API — query programmatically via /api/v1/skills
  • Cross-references — skills link to models, models link to skills

License

MIT

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Community-maintained catalog of AI agent skills — structured, searchable and integrated with the OpenModels ecosystem.

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