Vibe-Skills

More than a skill collection — your personal AI operating system

If your AI supports skills, VibeSkills works. 340+ skills spanning coding, research, data science & creative work.

   

🧠 Planning · 🛠️ Engineering · 🤖 AI · 🔬 Research · 🎨 Creation

   

Install  → 
/vibe or $vibe  → 
Smart Routing  → 
M / L / XL Execution  → 
Governance Verification  → 
✅ Delivery

📋 Table of Contents

• What makes it different
• Who is it for
• Intelligent Routing
• Memory System
• Full Capability Map
• Installation & Management
• Getting Started

[!IMPORTANT]

🎯 Core Vision

VibeSkills evolves with the times — ensuring it stays genuinely useful while dramatically lowering the barrier to cutting-edge vibecoding technology, eliminating the cognitive anxiety and steep learning curve that comes with new AI tools.

Whether or not you have a programming background, you can directly harness the most advanced AI capabilities with minimal effort.
Productivity gains from AI should be available to everyone.

✨ What makes it different?

Traditional skill repos answer: "What tools do I have?"
VibeSkills tackles the core pain point of heavy AI users: "How do I manage and invoke large numbers of Skills, and get work done efficiently and reliably?"

_{Works with Claude Code · Codex · Windsurf · OpenClaw · OpenCode · Cursor and any AI environment that supports the Skills protocol. Native MCP compatibility.}

👥 Who is it for?

Which of those pain points hit home? Find your position — what comes next will land harder.

If you're looking for a single small script, this may be overkill. But if you want to use AI more reliably, smoothly, and sustainably — this is your indispensable foundation.

🔀 Intelligent Routing: How 340+ Skills Collaborate Without Conflict

You know this is for you. Next question: 340+ skills in one system — how do they stay out of each other's way?

With 340+ skills, you might wonder: "Won't similar skills conflict? How does the system know which one to use?"

How routing works

VibeSkills uses a Canonical Router as the single authoritative routing decision center:

graph LR
    A[User Task] --> B{Canonical Router}
    B --> C[Intent Recognition]
    C --> D[Keyword Extraction]
    D --> E[Skill Matching]
    E --> F[Conflict Detection]
    F --> G[Priority Ranking]
    G --> H[Routing Decision]
    H --> I[Execute Skill]

    style B fill:#7B61FF,stroke:#fff,stroke-width:2px,color:#fff
    style F fill:#FF9800,stroke:#fff,stroke-width:2px,color:#fff

VibeSkills follows a Clarify ➔ Plan ➔ Execute ➔ Verify governed workflow to ensure every task goes through complete quality control:

• Requirements Clarification: Skills like speckit-clarify define clear boundaries and acceptance criteria
• Architecture Planning: Skills like aios-architect design the implementation path
• Execution Layer: 340+ skills called on demand to complete the actual work
• Quality Verification: Skills like tdd-guide and code-review ensure delivery quality

Why this design?

Traditional skill repos let AI "freely choose" — the result:

• ❌ AI can't remember what skills exist
• ❌ Similar skills conflict with each other
• ❌ Execution paths are unpredictable

VibeSkills routing guarantees:

• ✅ Determinism: Same task always follows the same routing logic
• ✅ Traceability: Every routing decision has a clear rationale
• ✅ Control: Users can override default routing via explicit invocation (e.g. /vibe)
• ✅ Stability: 129 governance rules prevent conflicts and divergence

M / L / XL Execution Levels

After selecting the primary skill, the router also automatically determines the execution level based on task complexity:

The system automatically selects the level after requirements clarification, before plan execution. Users only need to invoke /vibe or $vibe.

Specialist skills are executed as bounded native units only when approved in the frozen plan. They are phase-bound to planning, execution, deliverable, or verification work so expert help is useful without competing with runtime governance. Child-lane specialist suggestions stay advisory until root approval.

You can also express an explicit preference:

Please execute this task according to the plan, launching XL-level workflow /vibe

One route or multiple per task?

Core principle: A task typically routes to one primary skill, but that skill can invoke others as sub-processes.

• Single primary route: The Canonical Router selects the single best-matching primary skill
• Skill composition: The primary skill can invoke others as needed during execution (e.g. vibe can invoke speckit-clarify, aios-architect, etc.)
• Governed coordination: Multi-skill collaboration is controlled by governance rules, not arbitrary combinations

How are conflicts between similar skills handled?

When multiple skills appear capable of completing a task, the router avoids conflicts through:

1. Priority rules: Each skill has a clear priority and applicable scenario
2. Context matching: Analyzes task complexity, multi-phase needs, and explicit user preferences
3. Mutual exclusion rules: 129 rules include exclusion rules preventing conflicting combinations
4. Graceful degradation: When the preferred skill is unavailable, fallback by priority — no infinite loops

Will too many options cause token explosion?

No. Routing doesn't dump all options into the model — it uses a smart trigger mechanism:

User command → AI-assisted governance extracts intent keywords → keywords trigger skill routing

The governance framework adds ~30k initial context overhead, but does not cause token explosion.

Real example: User says "Help me refactor this project"

1. Intent recognition → Complex refactoring task
2. Keyword extraction → refactor, project, code quality
3. Skill matching → vibe / autonomous-builder / systematic-debugging
4. Routing decision → Choose vibe (refactoring needs multi-phase: clarify → plan → execute → verify)

🧠 Memory System: AI That Truly Remembers

Routing solves "which skill". But there's a deeper question: when the conversation ends, does AI remember you?

Sound familiar?

VibeSkills builds a four-tier memory system — one authoritative component per memory need:

Optional extensions: mem0 as a personal preference backend (opt-in); Letta provides memory block mapping vocabulary — neither replaces the four canonical tiers.

Three Dedicated Memory Skills

Governance: Single source of truth (no dual-track) · Explicit write only (Serena requires confirmation) · episodic-memory permanently disabled · mem0 limited to personal preferences · Kill switch on every external backend

✦ Full Capability Map: Your All-in-One Workbench

Routing + memory form the dispatch nervous system. Here's the full capability map they power — end to end.

Unrolled across a "real workflow", VibeSkills has laid out a complete end-to-end capability chain:

💡 Why governance matters: The vast skill library below is not a collection of isolated scripts — it is an ecosystem governed by the VCO runtime. Through domain matrix classification, the system automatically invokes the right tool at the right context node, without requiring you to manually search through skills.

🧠 Requirements, Planning & Product Management

Turn big ideas into actionable plans: requirement insights, problem definition, Sprint planning, task breakdown, and constraint collection. Ensure direction is clear, boundaries are defined, and milestones are verifiable before writing a single line of code.

.system, aios-pm, aios-po, aios-sm, aios-squad-creator, aios-ux-design-expert, brainstorming, create-plan, designing-experiments, planning-with-files, shared-templates, speckit-analyze, speckit-checklist, speckit-clarify, speckit-constitution, speckit-plan, speckit-specify, speckit-tasks, speckit-taskstoissues, subagent-driven-development, think-harder, treatment-plans, ux-researcher-designer, writing-plans

🛠️ Software Engineering & Architecture

The true engineering foundation: from scaffolding, cross-file changes, API design to microservice architecture evaluation. Not just code output — also context memory, toolchain orchestration, and multi-phase intelligent Agent coordination.

aios-architect, aios-dev, aios-master, architecture-patterns, autonomous-builder, cancel-ralph, coding-tutor, context-fundamentals, context-hunter, cs-foundations, deepagent-memory-fold, deepagent-toolchain-plan, evaluating-code-models, get-available-resources, hive-mind-advanced, local-vco-roles, nowait-reasoning-optimizer, prompt-lookup, ralph-loop, skill-creator, skill-lookup, spec-kit-vibe-compat, speckit-implement, superclaude-framework-compat, theme-factory, vibe, webthinker-deep-research

🔧 Debugging, Testing & Quality Assurance

Guarding the lifeline of code and systems: unit tests, root cause analysis, dependency conflict resolution, security vulnerability reviews, and a complete TDD guide — ensuring systems never enter a "breaks after every change" black-box state.

aios-qa, build-error-resolver, code-review, code-review-excellence, code-reviewer, data-quality-checker, data-quality-frameworks, debugging-strategies, deslop, detecting-performance-regressions, error-resolver, evals-context, experiment-failure-analysis, generating-test-reports, ml-data-leakage-guard, performance-testing, property-based-testing, providing-performance-optimization-advice, receiving-code-review, requesting-code-review, reviewing-code, security-best-practices, security-ownership-map, security-reviewer, security-threat-model, systematic-debugging, tdd-guide, verification-before-completion, verification-quality-assurance, windows-hook-debugging

📊 Data Analysis & Statistical Modeling

Let data tell the truth: a one-stop data processing engine from data cleaning, missing value handling, and exploratory analysis (EDA) to advanced statistical testing, regression models, and time series forecasting.

aios-data-engineer, anomaly-detector, correlation-analyzer, dask, data-artist, data-exploration-visualization, data-normalization-tool, detecting-data-anomalies, excel-analysis, exploratory-data-analysis, feature-importance-analyzer, geopandas, hypothesis-testing, metric-calculator, networkx, performing-causal-analysis, performing-regression-analysis, polars, preprocessing-data-with-automated-pipelines, regression-analysis-helper, running-clustering-algorithms, scientific-data-preprocessing, splitting-datasets, spreadsheet, statistical-analysis, statistics-math, statsmodels, usfiscaldata, vaex, xlsx

🤖 Machine Learning & AI Engineering

Full-stack AI model development: beyond just calling APIs — feature engineering, model training, fine-tuning, interpretability (SHAP), large model evaluation (Evals), and reinforcement learning workflows.

LQF_Machine_Learning_Expert_Guide, aeon, datamol, deepchem, embedding-strategies, engineering-features-for-machine-learning, evaluating-llms-harness, evaluating-machine-learning-models, explaining-machine-learning-models, geniml, ml-pipeline-workflow, openai-knowledge, pufferlib, pytorch-lightning, scikit-learn, scikit-survival, senior-computer-vision, senior-data-scientist, senior-ml-engineer, senior-prompt-engineer, shap, similarity-search-patterns, sparse-autoencoder-training, stable-baselines3, tensorboard, timesfm-forecasting, torch-geometric, torch_geometric, torchdrug, training-machine-learning-models, transformer-lens-interpretability, transformers, umap-learn, unsloth, weights-and-biases

🧬 Life Sciences & Bioinformatics

A formidable interdisciplinary powerhouse: single-cell sequencing analysis, protein structure folding, drug molecule discovery, genomics alignment — seamlessly integrated with cloud-based biology lab systems.

adaptyv, alphafold-database, anndata, arboreto, benchling-integration, biopython, bioservices, cellxgene-census, cobrapy, deeptools, diffdock, dnanexus-integration, esm, etetoolkit, flowio, gene-database, gget, ginkgo-cloud-lab, gtars, histolab, imaging-data-commons, labarchive-integration, lamindb, latchbio-integration, matchms, medchem, molfeat, neurokit2, neuropixels-analysis, omero-integration, opentrons-integration, pathml, protocolsio-integration, pydeseq2, pydicom, pyhealth, pylabrobot, pyopenms, pysam, pytdc, rdkit, scanpy, scikit-bio, scvi-tools, tiledbvcf

🔬 Scientific Computing & Mathematical Logic

Precise derivation and complex system simulation: symbolic math, Bayesian probabilistic programming, quantum computing simulation, multi-objective optimization, and rigorous propositional logic and mathematical proof assistance.

astropy, cirq, dialectic, fluidsim, gradient-methods, math, math-model-selector, math-tools, mathematical-logic-expert, matlab, pennylane, pymatgen, pymc, pymc-bayesian-modeling, pymoo, propositional-logic, qiskit, qutip, rowan, simpy, sympy, xan

📚 Scientific Literature & Academic Writing

The expressway for academic productivity: precise search across dozens of databases (PubMed, arXiv, etc.), systematic review matrix organization, citation management, and the complete publication pipeline from drafting to peer review.

bgpt-paper-search, biorxiv-database, brenda-database, chembl-database, citation-management, clinical-decision-support, clinical-reports, clinicaltrials-database, clinpgx-database, clinvar-database, comprehensive-research-agent, content-research-writer, cosmic-database, datacommons-client, documentation-lookup, drugbank-database, ena-database, ensembl-database, fda-database, geo-database, gwas-database, hmdb-database, hypothesis-generation, kegg-database, literature-matrix, literature-review, manuscript-as-code, market-research-reports, metabolomics-workbench-database, open-notebook, openalex-database, opentargets-database, paper-2-web, pdb-database, peer-review, pubchem-database, pubmed-database, pyzotero, reactome-database, research-grants, research-lookup, scholar-evaluation, scholarly-publishing, scientific-brainstorming, scientific-critical-thinking, scientific-reporting, scientific-writing, string-database, submission-checklist, uniprot-database, uspto-database, zinc-database

🎨 Multimedia, Visualization & Documentation

Making knowledge and data visible: interactive chart generation, publication-quality scientific figures, slide creation, audio/video production, and deep read/write parsing of Word, PDF, and other office documents.

algorithmic-art, creating-data-visualizations, data-storytelling, datavis, doc, docs-review, docs-write, document-skills, docx, docx-comment-reply, figma, figma-implement-design, file-organizer, g2-legend-expert, generate-image, imagegen, infographics, latex-posters, latex-submission-pipeline, markdown-mermaid-writing, markitdown, matplotlib, pdf, plotly, pptx-posters, report-generator, scientific-schematics, scientific-slides, scientific-visualization, screenshot, seaborn, slides-as-code, smart-file-writer, speech, structured-content-storage, transcribe, venue-templates, video-studio, visualization-best-practices, vscode-release-notes-writer, writing-docs

🔌 External Integrations, Automation & Deployment

Breaking the limits of the runtime: seamlessly connect external browsers, design platforms, and cloud services via MCP protocol and Playwright automation — plus CI/CD pipeline support and one-click automated deployment.

aios-devops, alpha-vantage, claude-skills, commit-with-reflection, denario, digital-brain, edgartools, flashrag-evidence, fred-economic-data, geomaster, gh-address-comments, gh-fix-ci, hedgefundmonitor, hypogenic, iso-13485-certification, jupyter-notebook, knowledge-steward, mcp-integration, modal, modal-labs, netlify-deploy, openai-docs, perplexity-search, playwright, prowler-docs, scrapling, sentry, skypilot-multi-cloud-orchestration, vercel-deploy

📊 Why is it powerful?

Now for the numbers. This isn't a demo project — it's a running system.

The runtime core behind VibeSkills is VCO. This is not a single-point tool or a "code completion" script — it is a super-capability network that has been deeply integrated and governed:

⚙️ Installation & Skills Management

Skills keep growing — but you don't need to manage them individually.

Uninstall: Owned-only cleanup

Running uninstall.ps1 or uninstall.sh --host <host> is the partner surface to install. By default it performs a ledger-first, owned-only cleanup that only touches paths recorded in .vibeskills/install-ledger.json, *.host-closure.json, or the documented legacy surfaces. The full contract lives in docs/uninstall-governance.md so operators always know which host files Vibe actually owns.

Install: One entry, two public versions

Customize: Add your own skills

→ Custom workflow & skill onboarding guide

📦 Standing on the Shoulders of Giants

These capabilities weren't built from scratch. VibeSkills' foundation is the continuous integration of the best open-source solutions into one governed system.

We know that building in isolation can't keep pace with the rapidly evolving AI landscape. The core strength of VibeSkills comes from continuously absorbing the most mature methods and architectures from the open-source community, and bringing them under a single unified governance and orchestration system.

🙏 Special Thanks & Acknowledgements

This project continuously integrates, absorbs, and governs the core strengths of the following excellent open-source projects:

superpower · claude-scientific-skills · get-shit-done · aios-core · OpenSpec · ralph-claude-code · SuperClaude_Framework · spec-kit · Agent-S · mem0 · scrapling · claude-flow · serena · everything-claude-code · DeepAgent and more

Thank you to all authors for your generous contributions — without these brilliant stars, VibeSkills would not exist. We have done our best to properly attribute and credit all absorbed repositories. If anything was missed, please open an Issue and we will correct it promptly.

🚀 Getting Started

You know what this is now. All it takes from here is one prompt:

⚠️ Invocation note: This project uses a Skills format architecture. Please invoke it through your host environment's Skills invocation method — do not run it as a standalone CLI program.

💡 Recommended practice: If you want every subsequent turn to be explicitly governed by the VibeSkills runtime, keep appending $vibe or /vibe in each turn. If you don't include the invocation syntax in a turn, that turn should not be treated as "explicitly locked in vibe runtime".

Currently supported platforms: codex (most complete governed path) · claude-code · cursor · windsurf (supported install-and-use path with runtime-adapter integration) · openclaw (preview runtime-core path) · opencode (preview adapter path)

Understand the system

• 📖 System architecture & philosophy
• 📜 VibeSkills Manifesto

Installation & Configuration

• ⚡️ Prompt-based install (recommended)
• 🧩 Custom workflow onboarding
• 📄 OpenClaw host notes
• 📄 OpenCode host notes
• 📁 Manual copy install (offline)
• 🛠 Advanced install command reference
• 🧊 Cold start & other environments

Fork → Modify → Pull Request → Merge ✅

Star History

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Transform the parts of real work most prone to going off the rails into a system that is more callable, more governable, and more maintainable over time.

_{Made with ❤️  ·  GitHub  ·  中文}