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Vibe Coding2026-07-28 · source-backed
Compounding at ~847 stars/day to 97,447, built on tree-sitter AST parsing across 36+ languages plus Leiden community detection, with no vector store anywhere in the pipeline. Every edge is labeled EXTRACTED (explicit in source) or INFERRED (derived through resolution), which is the transparency argument against embedding-based code retrieval, and a real one. 45.3% QA accuracy on LOCOMO (n=300), 76% on LongMemEval-S (n=50), claiming parity with dense RAG at zero LLM cost for code-only extraction. Dual Apache-2.0/MIT. (GitHub)
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Graphify-Labs/graphify (MIT, v0.9.17 on July 16) has sustained roughly 780 stars/day since April 3. It parses ~40 languages with tree-sitter AST locally and deterministically, then tags every edge as EXTRACTED (explicit in source) or INFERRED (derived), so you can tell what wa...
MemPalace (57,821 stars, v3.6.0) reports 96.6% raw recall@5 on LongMemEval with no LLM required, 98.4% with hybrid v4 on a held-out 450 questions, LoCoMo R@10 rising 60.3% → 88.9%, ConvoMem 92.9%, MemBench 80.3%, while explicitly refusing head-to-head comparison against Mem0,...
1. Use claude agents --json to build session dashboards. Claude Code v2.1.145 outputs all live agent sessions as structured JSON with status, model, elapsed time, and parent relationships. Pipe it into a tmux status bar widget or session picker script for switching between bac...
Graphify-Labs/graphify ships as a /graphify skill for Claude Code, Cursor, Codex and Gemini CLI using local deterministic AST parsing with no API cost. The scope claim is what separates it: non-code artifacts land in the same graph, so "which endpoint reads this table" resolve...
The headline number on this repo is 65% token savings. The number you should actually care about is 33.2%, and the reason to trust the project is that the maintainer tells you the difference. JuliusBrussee/caveman cut v2.1.0 on August 16 at 19:22 UTC (GitHub). The GitHub API r...
Memori turns agent execution traces into structured persistent state, outperforming Zep, LangMem, and Mem0 on the LoCoMo benchmark while reducing prompt size by 67% vs Zep. Python and TypeScript SDKs. If you're building agents that need memory, benchmark this against whatever...
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