RAG Failure Diagnostics Clinic vs Toonify Token Optimization
Side-by-side comparison with live GitHub signals. Last updated July 10, 2026.
| Metric | RAG Failure Diagnostics Clinic | Toonify Token Optimization |
|---|---|---|
| GitHub Stars | 117.3K | 117.3K |
| Contributors | 80 | 80 |
| Last Commit | Jul 10, 2026 | Jul 10, 2026 |
| Open Issues | 5 | 5 |
| License | open-source | open-source |
| Pricing | open-source | open-source |
| Free Tier | Yes | Yes |
| Category | dev-tools | dev-tools |
| Trending | No | No |
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About RAG Failure Diagnostics Clinic
A diagnostic tool that identifies why RAG pipelines produce poor results. It tests for common failure modes: irrelevant retrieval, missing context, hallucination over context, chunking issues, and embedding quality problems. Provides a structured report with specific fix recommendations for each detected issue. Essential for debugging production RAG systems. Part of the awesome-llm-apps collection.
View full listingAbout Toonify Token Optimization
Toonify is a token optimization tool that compresses LLM prompts and responses using a custom TOON format, reducing API costs by 30-60% without meaningful quality loss. It works by stripping unnecessary verbosity, abbreviating common patterns, and restructuring prompts for token efficiency. Compatible with any LLM API. Part of the awesome-llm-apps collection.
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