A methodology designed to measure the contribution of the features to the predictive performance of any econometric or machine learning model.
GitHub repository with 18 stars and 1 forks.
Language: Python
Topics: explainability, interpretability, machine-learning, performance-metrics, shap, shapley-value
2026-06-05: 18 stars and 1 forks.
Interactive architecture diagrams for codebases
GitHub repository with 2,091 stars and 177 forks.
Trending score: 1.26; stars gained: +20; forks gained: +1.
Language: Python
Topics: agents, aiagentic, explainability, llms, static-analysis, codedocs
The agent that grows with you
GitHub repository with 181,917 stars and 31,216 forks.
Trending score: 5.95; stars gained: +1,867; forks gained: +361.
Language: Python
Topics: ai, ai-agent, ai-agents, anthropic, chatgpt, claude
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.
GitHub repository with 13,768 stars and 870 forks.
Trending score: 5.69; stars gained: +2,829; forks gained: +175.
Language: Python
Topics: agent, ai, anthropic, compression, context-engineering, context-window
Academic Research Skills for Claude Code: research → write → review → revise → finalize
GitHub repository with 27,484 stars and 2,256 forks.
Trending score: 5.52; stars gained: +1,079; forks gained: +89.
Language: Python
Topics: academic-pipeline, academic-writing, ai-research, claude, claude-code, literature-review
Learn it. Build it. Ship it for others.
GitHub repository with 28,622 stars and 4,680 forks.
Trending score: 5.32; stars gained: +1,261; forks gained: +238.
Language: Python
Topics: agents, ai, ai-agents, ai-engineering, computer-vision, course
GitHub repository with 30,060 stars and 4,235 forks.
Trending score: 4.88; stars gained: +688; forks gained: +114.
Language: Python
An opinionated list of Python frameworks, libraries, tools, and resources
GitHub repository with 301,396 stars and 28,042 forks.
Trending score: 4.60; stars gained: +518; forks gained: +24.
Language: Python
Topics: awesome, python, collections, python-frameworks, python-libraries, python-tools
Interactive architecture diagrams for codebases
GitHub repository with 2,091 stars and 177 forks.
Trending score: 1.26; stars gained: +20; forks gained: +1.
Language: Python
Topics: agents, aiagentic, explainability, llms, static-analysis, codedocs
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
GitHub repository with 20,597 stars and 2,576 forks.
Trending score: 0.84; stars gained: +5; forks gained: +1.
Topics: machine-learning, mlops, interpretability, explainability, responsible-ai, deep-learning
A game theoretic approach to explain the output of any machine learning model.
GitHub repository with 25,504 stars and 3,726 forks.
Trending score: 0.56; stars gained: +2; forks gained: +0.
Language: Jupyter Notebook
Topics: interpretability, machine-learning, deep-learning, gradient-boosting, shap, shapley
Fit interpretable models. Explain blackbox machine learning.
GitHub repository with 6,867 stars and 784 forks.
Trending score: 0.03; stars gained: +0; forks gained: +0.
Language: C++
Topics: ai, artificial-intelligence, bias, blackbox, differential-privacy, explainability
The flowchart pattern for backend code — self-explainable systems that AI can reason about. Causal traces, auto-generated tool descriptions, transactional state.
GitHub repository with 8 stars and 2 forks.
Trending score: 0.02; stars gained: +0; forks gained: +0.
Language: TypeScript
Topics: ai, ai-tools, backend, causal-trace, debugging, dfs