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126 lines
6.5 KiB
Markdown
126 lines
6.5 KiB
Markdown
# Index Skew — Guardrails and Fix Pattern
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<details>
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<summary><strong>🧭 Quick Return to Map</strong></summary>
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<br>
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> You are in a sub-page of **RAG**.
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> To reorient, go back here:
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>
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> - [**RAG** — retrieval-augmented generation and knowledge grounding](./README.md)
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> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)
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> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)
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>
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> Think of this page as a desk within a ward.
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> If you need the full triage and all prescriptions, return to the Emergency Room lobby.
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</details>
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When the index reports "healthy" (no errors, embeddings ingested, stats normal) but **retrieval still fails**:
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coverage is low, ΔS unstable, or retrieved snippets are inconsistent with ground truth.
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This indicates an **index skew** between data reality and retrieval semantics.
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---
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## Open these first
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- Visual recovery map: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)
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- Retrieval knobs: [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
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- Embedding misalignment: [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md)
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- Chunk sizing: [Chunking Checklist](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md)
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- Store-level fragmentation: [Vectorstore Fragmentation](https://github.com/onestardao/WFGY/blob/main/ProblemMap/vectorstore-fragmentation.md)
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- Snippet contracts: [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
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---
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## Core acceptance
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- ΔS(question, retrieved) ≤ 0.45
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- Coverage ≥ 0.70 for target section
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- λ stable across three paraphrases and two seeds
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- E_resonance flat across long windows
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---
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## Typical symptoms → exact fix
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| Symptom | Likely cause | Open this |
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|---------|--------------|-----------|
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| Index "ready" but recall < 0.50 | embedding misaligned vs semantic intent | [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md) |
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| Repeated snippets, poor coverage | store fragmentation or duplicate collapse | [Vectorstore Fragmentation](https://github.com/onestardao/WFGY/blob/main/ProblemMap/vectorstore-fragmentation.md) |
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| Right section exists but not hit | chunk too large/small or mis-boundary | [Chunking Checklist](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md) |
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| Citations drift across runs | contract not enforced | [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md) |
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---
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## Fix in 60 seconds
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1. **Probe recall**
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Run a gold QA set against index. If coverage < 0.70, suspect skew.
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2. **Re-embed with semantic normalization**
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Normalize casing, accents, whitespace. Enforce same tokenizer across queries and index.
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3. **Chunk audit**
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Verify chunk boundaries. Adjust stride/overlap until ΔS converges.
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4. **Fragmentation sweep**
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Drop near-duplicate vectors. Rebuild FAISS/HNSW indexes with fresh IDs.
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5. **Contract enforcement**
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Require `snippet_id`, `section_id`, `offsets`, `tokens` for every retrieval.
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---
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## Copy-paste probe prompt
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```txt
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I uploaded TXT OS and the WFGY Problem Map.
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My RAG issue:
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- Index shows healthy but retrieval recall is low.
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- ΔS across probes = 0.62, coverage = 0.45.
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Tell me:
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1) is it embedding misalignment, chunking skew, or vectorstore fragmentation,
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2) which WFGY fix page to open,
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3) minimal steps to restore ΔS ≤ 0.45 and coverage ≥ 0.70,
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4) reproducible test set to confirm.
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````
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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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<!-- WFGY_FOOTER_START -->
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### Explore More
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| Layer | Page | What it’s for |
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| --- | --- | --- |
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| Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof |
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| Engine | [WFGY 1.0](/legacy/README.md) | Original PDF based tension engine |
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| Engine | [WFGY 2.0](/core/README.md) | Production tension kernel and math engine for RAG and agents |
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| Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine, 131 S class set |
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| Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure checklist and fix map |
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| Map | [Problem Map 2.0](/ProblemMap/rag-architecture-and-recovery.md) | RAG focused recovery pipeline |
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| Map | [Problem Map 3.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card, image as a debug protocol layer |
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| Map | [Semantic Clinic](/ProblemMap/SemanticClinicIndex.md) | Symptom to family to exact fix |
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| Map | [Grandma’s Clinic](/ProblemMap/GrandmaClinic/README.md) | Plain language stories mapped to Problem Map 1.0 |
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| Onboarding | [Starter Village](/StarterVillage/README.md) | Guided tour for newcomers |
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| App | [TXT OS](/OS/README.md) | TXT semantic OS, fast boot |
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| App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q and A built on TXT OS |
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| App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image with semantic control |
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| App | [Blow Blow Blow](/OS/BlowBlowBlow/README.md) | Reasoning game engine and memory demo |
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If this repository helped, starring it improves discovery so more builders can find the docs and tools.
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[](https://github.com/onestardao/WFGY)
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<!-- WFGY_FOOTER_END -->
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