Privacy and advertising choices
Git-Stars uses essential storage for site operation. Optional analytics and ad-measurement scripts stay disabled unless you accept them; partners such as Google may then use cookies or similar identifiers where required. Privacy Policy
把书、长视频、播客等高价值内容蒸馏成可执行的 Agent Skills
This repository page is useful for visitors, but Git-Stars keeps it out of search indexing until more original evidence and comparison context are available.
75
review score
Problem solved
It solves the problem of converting unstructured, lengthy content into structured, actionable skills for AI agents, bypassing the need for manual prompt engineering or fine-tuning.
Deployment reality
The available setup signal starts with: Clone the repo and run `pip install -r requirements.txt`.. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.
Commercial use
The recorded license is AGPL-3.0. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.
Capability ceiling
Developers can build agents that automatically extract key insights from books or videos and execute tasks like summarization, Q&A, or decision-making based on that knowledge. Real-world use cases include creating study assistants, content curation bots, or domain-specific expert agents. The ceiling is limited only by the quality of source content and the agent's underlying model.
Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.
kangarooking/cangjie-skill is tracked as a Python project in the Automation, AI Agent, LLM Tool area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.
Momentum check: the repository has 8.0k total stars, with +0 today, +0 this week, and +4.9k this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.
Maintenance check: current activity is Moderate; the latest push was 66 days ago, and the open issue queue is 13, about 0.16% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.
Adoption check: 961 forks and 8.0k watchers suggest how often the project is reused or followed. License signal: AGPL-3.0. Always verify license compatibility before commercial or internal use.
Practical fit: this project is most relevant when you need Python teams evaluating ecosystem-native tooling. Be cautious when you need a legal review, security audit, or production SLA.
Source check: Git-Stars currently has 1 explicit source reference(s) for this report and a recent growth signal of 4.9k. Follow the original GitHub repository for final install, security, and release information.
Analysis
ReadyOriginal problem, capability, and verdict guidance are available.
Sources
LimitedNeeds clearer source references.
License
ReadyAGPL-3.0 is recorded for review.
Maintenance
ReadyRecent activity is visible in repository metadata.
Alternatives
ReadyEnough nearby projects exist for comparison.
Momentum
8.0k Stars
Reuse
961 Forks
Attention
8.0k Watchers
Maintenance
moderate
License
AGPL-3.0
Open issues
13
Cangjie Skill is an AI agent framework that distills high-value content like books, long videos, and podcasts into executable agent skills, enabling agents to perform complex tasks based on curated knowledge.
Automation
Workflow automation, integration glue, and orchestration
AI Agent
Agent frameworks, autonomous workflows, and tool-use systems
LLM Tool
Libraries and tools for LLM apps, RAG, prompts, and evals
Clone the repo and run `pip install -r requirements.txt`.63
Health Score
Moderate
Commit Activity
Apr 16, 2026
Created
Aug 9, 2026
Last push
Star history will appear after daily syncs accumulate data.
Forks
Open
Watchers
kangarooking
GitHub profileobra/superpowers
An agentic skills framework & software development methodology that works.
affaan-m/ECC
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
NousResearch/hermes-agent
The agent that grows with you
mattpocock/skills
Skills for Real Engineers. Straight from my .agents directory.
multica-ai/andrej-karpathy-skills
A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls.
✓
License
✓
Forked
~ Moderate
Maintained
Problem Solved
It solves the problem of converting unstructured, lengthy content into structured, actionable skills for AI agents, bypassing the need for manual prompt engineering or fine-tuning.
Capabilities
Developers can build agents that automatically extract key insights from books or videos and execute tasks like summarization, Q&A, or decision-making based on that knowledge. Real-world use cases include creating study assistants, content curation bots, or domain-specific expert agents. The ceiling is limited only by the quality of source content and the agent's underlying model.
Bottom Line
This is ideal for developers who want to quickly turn rich content into agent capabilities without manual prompt crafting. Avoid if you need real-time or dynamic knowledge. The key trade-off is dependency on static content distillation.