Albertchamberlain/Awesome-OKF
OKF (Open Knowledge Format) — curated catalog of tools, plugins, skills, proposals, and docs for agent-friendly knowledge. YAML-driven, agent-searchable, MCP-ready.
Star History
Momentum
+10
STARS · LAST 30 DAYS
1
PER DAY
#824
MOST-STARRED Python
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +7 | +10 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +1 | +3 | +10 |
Awesome-OKF gained 10 stars in the last 30 days, about 1 a day, and now has 97. It is about 1 year old and has averaged roughly 97 stars a year. It ranks #824 among Python repositories and #6,783 across all languages on GitHubRepo.
Trending Record
5
DAYS ON TRENDING
#2513
BEST RANK
Sep 24, 2026
FIRST APPEARANCE
Active
STATUS TODAY
Awesome-OKF has maintained a continuous presence across global trending indexes, peaking at #2513. Below is the 30-day activity profile:
💡 Overview
Awesome-OKF is an open-source project written in Python: OKF (Open Knowledge Format) — curated catalog of tools, plugins, skills, proposals, and docs for agent-friendly knowledge. YAML-driven, agent-searchable, MCP-ready.
Engineered for speed, consistency, and developer ease, it solves common hurdles in agent-memory, agent-skills, ai-agents. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
⚡ Key Features
Optimized execution pipeline written in Python for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
📥 Installation
$ pip install Awesome-OKF⚙ System Requirements
Platforms
- • macOS
- • Linux
- • Windows
Runtime & Dependencies
Python >= 3.9, pip, virtualenv
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
🧠 How It Works
Awesome-OKF coordinates its core functionality through a modular Python pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
🎯 Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with Awesome-OKF.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
🚀 Getting Started
Install Awesome-OKF using your package manager: `pip install Awesome-OKF`
Initialize your project workspace or configuration file for Awesome-OKF.
Import Awesome-OKF into your codebase or invoke it directly from your terminal.
Execute your test suite or run `Awesome-OKF --help` to verify successful setup.
👍 Strengths
⚠️ Considerations
⇄ Alternatives & Direct Competitors
👥 Who Should Use This
Developers and engineering teams building with Python, seeking reliable, tested, and actively maintained tooling for production workloads.
🏆 Nearby in the Rankings
Albertchamberlain/Awesome-OKF is currently ranked #6,783 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #6,774 | Mobaia/PhySpec | Python | ★ 98 | Compare ↗ |
| #6,774 | docker/sandbox-kit-spec | Go | ★ 98 | Compare ↗ |
| #6,774 | ThinkFlowLab/system1-agents | Python | ★ 98 | Compare ↗ |
| #6,774 | tihanyin/REx-skill | Python | ★ 98 | Compare ↗ |
| #6,774 | Simreal-AI/MathmoBench | Python | ★ 98 | Compare ↗ |
| #6,783 | Albertchamberlain/Awesome-OKF This Project | Python | ★ 97 | |
| #6,783 | masumedb/masume | Go | ★ 97 | Compare ↗ |
| #6,783 | lonecoding/QuantumultX-Rules | Python | ★ 97 | Compare ↗ |
| #6,783 | Erutaner/CLADE | Python | ★ 97 | Compare ↗ |
| #6,783 | erfnzdeh/my.edu.sharif.edu-sniper | Go | ★ 97 | Compare ↗ |
| #6,783 | KINGCLCL/SoftMotion | Python | ★ 97 | Compare ↗ |
Frequently Asked Questions
What does Awesome-OKF do? +
OKF (Open Knowledge Format) — curated catalog of tools, plugins, skills, proposals, and docs for agent-friendly knowledge. YAML-driven, agent-searchable, MCP-ready.
What language is Awesome-OKF written in? +
The primary language is Python. Topics include: agent-memory, agent-skills, ai-agents, ai-memory, awesome.
Is Awesome-OKF actively maintained? +
Yes, the last recorded push was on Sep 15, 2026 with 9 open issues being tracked.
How many stars does Awesome-OKF have? +
Awesome-OKF has 97 stars and 3 forks on GitHub.
How does Awesome-OKF rank among GitHub repositories? +
With 97 stars, Albertchamberlain/Awesome-OKF is ranked #6,783 globally across all repositories tracked on GitHubRepo and #824 among Python projects.
What license is Awesome-OKF distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
