KILO-KIT
Health Gecti
- License — License: Apache-2.0
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Community trust — 24 GitHub stars
Code Basarisiz
- process.env — Environment variable access in skills/ai-media/ai-multimodal/scripts/document_converter.py
- process.env — Environment variable access in skills/ai-media/ai-multimodal/scripts/gemini_batch_process.py
- eval() — Dynamic code execution via eval() in skills/ai-media/ai-multimodal/scripts/media_optimizer.py
- process.env — Environment variable access in skills/ai-media/ai-multimodal/scripts/media_optimizer.py
Permissions Gecti
- Permissions — No dangerous permissions requested
This framework provides a modular system for building and managing AI agent workflows at scale. It introduces a "Cognitive Flow Architecture" to handle AI interactions continuously and offers a library of specialized skills for task execution.
Security Assessment
The tool claims to follow security-first practices and does not request dangerous system permissions. However, the codebase contains a critical security flaw: a verified use of `eval()` for dynamic code execution within a media optimization script. This function is highly dangerous and represents a significant remote code execution vulnerability if exploited or fed untrusted input. Additionally, several scripts access environment variables, which while standard, requires vigilance to ensure no sensitive credentials are inadvertently exposed or logged. There are no detected hardcoded secrets, but the presence of `eval()` elevates the overall risk to Medium.
Quality Assessment
The project has a permissive Apache-2.0 license and is considered actively maintained, with repository updates pushed as recently as today. Despite these positive signs, community trust and overall adoption remain relatively low at 24 GitHub stars. As a relatively new and unproven framework, it may lack the extensive peer review typically required to fully audit complex agent architectures.
Verdict
Use with caution — the framework offers promising features, but the dangerous `eval()` function in the codebase requires manual review and strict input sanitization before deploying in any production environment.
Kilo-Kit is a comprehensive, modular framework for building and managing AI agent systems at scale (kilo-code = thousands of lines, hundreds of files). It introduces a revolutionary Cognitive Flow Architecture (CFA) that treats AI interactions as continuous flows rather than discrete events.
🚀 Kilo-Kit: Professional AI Agent Development Framework
Version: 1.0.0
Author: Kilo-Kit Team
License: Apache 2.0
🎯 What is Kilo-Kit?
Kilo-Kit is a comprehensive, modular framework for building and managing AI agent systems at scale (kilo-code = thousands of lines, hundreds of files). It introduces a revolutionary Cognitive Flow Architecture (CFA) that treats AI interactions as continuous flows rather than discrete events.
Core Philosophy
🧠 "Anticipate needs before they arise"
🔄 "Learn from every interaction"
📐 "Modularity enables scalability"
🎯 "Quality over quantity in every token"
💰 "Cost-aware intelligence"
✨ Key Innovations
| Innovation | Description |
|---|---|
| Predictive Context Engine (PCE) | Pre-loads context before you need it |
| Composable Behavior Units (CBU) | Build workflows from micro-behaviors |
| Token Economy Manager (TEM) | Smart budgeting for cost/quality balance |
| Decision Audit Trail (DAT) | Full explainability for all decisions |
| Skill Effectiveness Tracker (SET) | Self-improving skill system |
| Adaptive Routing | Learns optimal skill selection over time |
✨ Key Features
| Feature | Description |
|---|---|
| Skill System | Modular, loadable skills for specialized tasks |
| Adaptive Dispatch | Intelligent skill routing that learns from usage |
| Progressive Disclosure | Three-level context loading for efficiency |
| Context Engineering | Token optimization and attention management |
| Quality Gates | Mandatory checkpoints: typecheck → lint → test → build |
| TDD Workflow | Test-first development with RED → GREEN → REFACTOR |
| Security First | Input validation, parameterized queries, no hardcoded secrets |
| Multi-Stack Support | TypeScript, Python, .NET, Go ready |
💡 Skill Library
skills/ is the canonical workflow surface for Kilo-Kit. It supports the same Progressive Disclosure model as the core framework: scan the index first, load one skill body when routed, then open references/scripts only when needed.
| Layer | Purpose |
|---|---|
skills/kilo-kit/ |
Core Kilo-Kit framework skills and Hard-Gate workflows |
skills/<category>/<skill>/ |
Expanded skill library organized by execution domain |
skills/README.md |
Human-facing catalog with category summaries and install commands |
skills/SKILLS_INDEX.md |
Lightweight agent index for Predictive Context Engine prefetching |
Install the Full Skill Library
This installs every valid SKILL.md under skills/, including Kilo-Kit core skills and the expanded category library.
npx skills@latest add VoDaiLocz/KILO-KIT
Use this when you want the entire Kilo-Kit workflow surface available in your agents.
Install a Category
Use a category path when you only want one execution domain:
npx skills@latest add VoDaiLocz/KILO-KIT/skills/engineering
Install a Single Skill
npx skills@latest add VoDaiLocz/KILO-KIT/skills/engineering/tdd
📁 Project Structure
kilo-kit/
├── README.md # This file
├── QUICKSTART.md # 15-minute getting started guide
├── CONTRIBUTING.md # Contribution guidelines
├── CHANGELOG.md # Version history
│
├── .claude-plugin/ # Claude Code entry point
│ └── instructions.md
├── .cursor-plugin/ # Cursor IDE entry point
│ └── instructions.md
├── .codex/ # OpenAI Codex entry point
│ └── instructions.md
├── .opencode/ # OpenCode entry point
│ └── instructions.md
│
├── skills/ # Installable skill packs
│ ├── README.md # Human-facing skill catalog
│ ├── SKILLS_INDEX.md # Lightweight agent skill index
│ ├── kilo-kit/ # Core Kilo-Kit skills
│ │ ├── _template/ # Skill template
│ │ ├── debugging/ # Debugging skills
│ │ ├── development/ # Development skills
│ │ └── quality/ # Quality assurance skills
│ ├── engineering/ # Engineering and framework skills
│ ├── productivity/ # Agent workflow skills
│ ├── problem-solving/ # Debugging/reasoning skills
│ ├── design/ # UI/design skills
│ └── ... # Games, ops, docs, AI media, security
│
├── commands/ # Workflow commands
│ ├── quality-gate.md # Quality gate workflow
│ ├── init-skill.md # Skill initialization
│ └── validate-skill.md # Skill validation
│
├── src/ # Core system source
│ ├── core/ # Core system components
│ │ ├── KILO_MASTER.md # Master skill file (entry point)
│ │ ├── predictive-engine/ # Predictive Context Engine
│ │ ├── routing-engine/ # Adaptive Routing Engine
│ │ ├── execution-engine/ # Execution & Quality Gates
│ │ └── knowledge-layer/ # Persistent Knowledge
│ │
│ ├── behaviors/ # Composable Behavior Units
│ │ ├── atomic/ # Smallest behavior units
│ │ ├── compound/ # Combined behaviors
│ │ └── meta/ # Meta-behaviors
│ │
│ └── tools/ # CLI and utility tools
│ ├── init-skill.py # Skill initializer
│ ├── validate-skill.py # Skill validator (Python)
│ └── validate-skill.js # Skill validator (Node.js)
│
├── docs/ # Documentation
│ ├── architecture/ # Architecture decisions
│ ├── COMPLETION_ASSESSMENT.md
│ ├── DEEP_ANALYSIS.md
│ └── PROJECT_STRUCTURE.md
│
└── examples/ # Real-world examples
├── basic/ # Basic usage patterns
├── intermediate/ # Intermediate patterns
└── advanced/ # Advanced patterns
🚀 Quick Start
1. Install
# Clone the repository
git clone https://github.com/VoDaiLocz/KILO-KIT.git
cd kilo-kit
# No dependencies required - works out of the box!
2. Configure Your Agent
Copy the master skill file to your agent's configuration:
# For most AI agents
cp src/core/KILO_MASTER.md ~/.your-agent/KILO_MASTER.md
# Update your agent's system prompt to reference it
3. Use Skills
Skills are automatically loaded when your task matches their keywords. See the Skill Dispatch Table below.
📋 Skill Dispatch Table
| Task Keywords | Skill to Load |
|---|---|
bug, error, fix, debug |
skills/kilo-kit/debugging/systematic/ |
validate, validation |
skills/kilo-kit/debugging/systematic/ |
root cause, why |
skills/kilo-kit/debugging/root-cause/ |
verify, confirm |
skills/kilo-kit/debugging/verification/ |
review, PR, code review |
skills/kilo-kit/quality/code-review/ |
test, TDD, testing |
skills/kilo-kit/quality/testing/ |
security, auth, OWASP |
skills/kilo-kit/development/security/ |
API, backend, server |
skills/kilo-kit/development/backend/ |
🎓 Core Principles
1. Cognitive Flow Architecture
Traditional: Task → Process → Response (done)
Kilo-Kit: ┌─────────────────────────────┐
│ COGNITIVE FLOW │
│ │
Input ───►│ Predict → Execute → Learn │───► Output
│ ↑ │ │
Next ───►│ └──────────────┘ │───► Better
│ │
└─────────────────────────────┘
2. Quality Gates (NEVER SKIP)
# Before EVERY commit
typecheck → lint → test → build
# All must pass. No exceptions.
3. The Three Pillars
ANTICIPATE → EXECUTE → LEARN → OPTIMIZE
↑ │
└────────────────────────────┘
4. Progressive Disclosure
Level 1: Metadata (always loaded, ~100 tokens)
Level 2: SKILL.md body (when triggered, <5k tokens)
Level 3: References/Scripts (on-demand, unlimited)
🔧 Creating Custom Skills
Use the skill template:
python src/tools/init-skill.py my-skill --path ./skills/kilo-kit/
This creates:
my-skill/
├── SKILL.md # Main instructions (required)
├── references/ # Documentation to load as needed
├── scripts/ # Executable utilities
└── assets/ # Templates, images, etc.
SKILL.md Format
---
name: my-skill
description: >-
Clear description of what this skill does and when to use it.
Include keywords that should trigger this skill.
version: 1.0.0
behaviors: [behavior1, behavior2]
token_estimate:
min: 500
typical: 1500
max: 5000
---
# My Skill
## When to Use
- Situation 1
- Situation 2
## Process
1. Step 1
2. Step 2
## Guidelines
- Guideline 1
- Guideline 2
## References
- `references/detailed-guide.md` - For detailed instructions
- `scripts/helper.py` - For automated tasks
📚 Documentation
- QUICKSTART.md - Get started in 15 minutes
- docs/architecture/ - Architecture design documents
- docs/PROJECT_STRUCTURE.md - Project structure guide
- examples/ - Real-world usage examples
🤝 Contributing
We welcome contributions! Please read CONTRIBUTING.md for:
- Code of conduct
- Development setup
- Pull request process
- Coding standards
📊 Stack Preferences
TypeScript/JavaScript (2024-2025)
| Category | Preferred | Avoid |
|---|---|---|
| Runtime | Bun, Node 20+ | Node <18 |
| Backend | Hono, Elysia | Express |
| ORM | Drizzle, Prisma 5+ | Sequelize |
| Testing | Vitest, Playwright | Jest |
| Package | pnpm, Bun | npm |
Python
| Category | Preferred | Avoid |
|---|---|---|
| Runtime | Python 3.11+ | <3.9 |
| Backend | FastAPI, Litestar | Flask |
| ORM | SQLAlchemy 2.0 | <2.0 |
| Validation | Pydantic v2 | v1 |
| Linting | Ruff, mypy | flake8 |
.NET
| Category | Preferred |
|---|---|
| Framework | .NET 8+ |
| Web | ASP.NET Core |
| ORM | EF Core |
| Testing | xUnit, NUnit |
🏗️ Roadmap
- v1.0.0 - Core Cognitive Flow Architecture
- v1.1.0 - MCP Integration
- v1.2.0 - Multi-Agent Orchestration
- v2.0.0 - Visual Workflow Builder
📄 License
Apache 2.0 - See LICENSE for details.
Made with ❤️ for developers who value quality, efficiency, and scalability.
Kilo-Kit — Where AI meets excellence.
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