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ProblemMap/GlobalFixMap/MemoryLongContext/chunking-checklist.md
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# Chunking Checklist — Stability at Joins
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Long-context retrieval often fails not at the level of whole documents but at the **joins between chunks**.
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This checklist enforces stable, reproducible chunking so citations line up and entropy does not melt across boundaries.
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---
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## When to use
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- Citations drift by a few lines between runs.
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- Long transcripts lose alignment after OCR or parsing.
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- Model answers cover the right fact but cite the wrong block.
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- ΔS spikes exactly at chunk joins.
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- Different agents disagree on chunk IDs.
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---
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## Core acceptance targets
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- Each join ΔS ≤ **0.50**.
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- Overall ΔS(question, retrieved) ≤ **0.45**.
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- Coverage ≥ **0.70** of intended section.
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- λ remains convergent across 3 paraphrases.
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- Each chunk has immutable `chunk_id`, `start_line`, `end_line`.
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---
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## Checklist for stable chunking
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- **Deterministic boundaries**
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Split on semantic units (sections, paragraphs, headings). Never by raw token count alone.
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- **Overlap fence**
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Add 10–15% overlap at joins. Enforce consistent overlap across every run.
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- **Immutable IDs**
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Generate `chunk_id = sha256(doc_id + start_line + end_line)`. Store and reuse.
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- **Audit trail**
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Store `{chunk_id, start_line, end_line, source_url, tokens}` for every chunk.
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- **Normalization**
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Apply Unicode NFC, collapse whitespace, unify casing.
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- **Confidence gating**
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Drop OCR or parsing lines with low confidence before chunking.
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---
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## Fix in 60 seconds
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1. Re-chunk corpus using semantic units.
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2. Apply overlap fence and store immutable chunk IDs.
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3. Run ΔS probes at joins. If ΔS > 0.50, re-check boundaries.
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4. Store all chunk metadata in trace logs.
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5. Require cite-then-answer. Reject any orphan chunk references.
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---
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## Copy-paste prompt
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```
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You have TXT OS and the WFGY Problem Map.
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Task: enforce stable chunking.
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Protocol:
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1. Verify each snippet has {chunk\_id, start\_line, end\_line, section\_id, source\_url}.
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2. Reject orphans: if citation lacks chunk\_id, stop and request fix.
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3. Require cite-then-answer.
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4. Probe ΔS across joins, keep ≤ 0.50.
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5. Report ΔS(question,retrieved), ΔS(joins), and λ state.
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```
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---
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## Common failure signals
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- Answers cite correct fact but wrong block → chunk IDs not stable.
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- ΔS spikes exactly at joins → overlap missing.
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- OCR transcripts break alignment → normalization skipped.
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- Multi-agent systems cite different chunk IDs → contract drift.
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---
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### 🔗 Quick-Start Downloads (60 sec)
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| Tool | Link | 3-Step Setup |
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|------|------|--------------|
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| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
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| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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### 🧭 Explore More
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| Module | Description | Link |
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|-----------------------|----------------------------------------------------------|----------|
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| WFGY Core | WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack | [View →](https://github.com/onestardao/WFGY/tree/main/core/README.md) |
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| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) |
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| Problem Map 2.0 | RAG-focused failure tree, modular fixes, and pipelines | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) |
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| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) |
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| Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) |
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| Benchmark vs GPT-5 | Stress test GPT-5 with full WFGY reasoning suite | [View →](https://github.com/onestardao/WFGY/tree/main/benchmarks/benchmark-vs-gpt5/README.md) |
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| 🧙♂️ Starter Village 🏡 | New here? Lost in symbols? Click here and let the wizard guide you through | [Start →](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) |
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---
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> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** —
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> Engineers, hackers, and open source builders who supported WFGY from day one.
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> <img src="https://img.shields.io/github/stars/onestardao/WFGY?style=social" alt="GitHub stars"> ⭐ [WFGY Engine 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the [Unlock Board](https://github.com/onestardao/WFGY/blob/main/STAR_UNLOCKS.md).
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<div align="center">
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[](https://github.com/onestardao/WFGY)
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[](https://github.com/onestardao/WFGY/tree/main/OS)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)
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[](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)
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</div>
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