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🏥 Semantic Clinic Index — Your ER Triage Desk for Broken Pipelines

🌙 3AM: a dev collapsed mid-debug… 🩺 WFGY Triage Center — Emergency Room & Grandma’s AI Clinic

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🚑 WFGY Emergency Room (for developers)

👨‍⚕️ Now online:
Dr. WFGY in ChatGPT Room

This is a share window already trained as an ER.
Just open it, drop your bug or screenshot, and talk directly with the doctor.
He will map it to the right Problem Map / Global Fix section, write a minimal prescription, and paste the exact reference link.
If something is unclear, you can even paste a screenshot of Problem Map content and ask — the doctor will guide you.

⚠️ Note: for the full reasoning and guardrail behavior you need to be logged in — the share view alone may fallback to a lighter model.

💡 Always free. If it helps, a ⭐ star keeps the ER running.
🌐 Multilingual — start in any language.


👵 Grandma’s AI Clinic (for everyone)

Visit Grandma Clinic →

  • 16 common AI failure modes, each explained as a grandma story.
  • Everyday metaphors: wrong cookbook, salt-for-sugar, burnt first pot.
  • Shows both the life analogy and the minimal WFGY fix.
  • Perfect entry point for beginners, or anyone who wants to “get it” in 30 seconds.

💡 Tip: Both tracks lead to the same Problem Map numbers.
Choose Emergency Room if you need a fix right now.
Choose Grandma’s Clinic if you want to understand the bug in plain words.

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A complete triage hub for AI failures — beyond the core 16 — powered by WFGY.
Use this page when you don’t yet know which thing is breaking. Start from symptoms, jump to a failure family, then open the exact fix page. All fixes are driven by WFGY instruments: ΔS (semantic stress), λ_observe (layered observability), and E_resonance (coherence control).

If this page saves you time, a ⭐ helps others find it.


Quick Nav

Getting Started · Patterns Index · Examples · Eval · Ops · Multi-Agent Problems · Retrieval Playbook · Rerankers · Data Contracts · Multilingual Guide · Privacy & Governance · FAQ · Glossary


How to use this page

  1. Identify the symptom in the table below.
  2. Open the family (Prompting / Retrieval / Reasoning / Memory / Agents / Infra / Eval).
  3. Follow the fix page, then verify with ΔS ≤ 0.45 and convergent λ.

Prefer a pipeline-first view (OCR → chunk → embed → store → retrieve → prompt → LLM)?
Read RAG Architecture & Recovery.

Want the full catalog instead? See Problem Map Index.
🧩 Or, jump straight to MVP Demos: Run minimal WFGY examples →


Quick triage by symptom

Symptom you see Likely family Open this
Answers cite wrong snippet / mismatch with ground truth Retrieval → RAG hallucination.md
Chunks look right but reasoning is wrong Reasoning retrieval-collapse.md
High similarity, wrong meaning Retrieval / Embeddings embedding-vs-semantic.md
Model can’t explain why (no trace) Observability retrieval-traceability.md
Output degrades over 100k-token dialogs Memory / Long-context entropy-collapse.md · context-drift.md
OCR PDFs look correct yet answers drift Data / OCR ocr-parsing-checklist.md
Hybrid (HyDE + BM25) gets worse than single retriever Retrieval / Querying patterns/pattern_query_parsing_split.md
High recall but top-k ordering is messy Retrieval / Reranking rerankers.md · retrieval-playbook.md
Corrections don’t stick; model re-asserts old claim Reasoning / Prompting patterns/pattern_hallucination_reentry.md
“Who said what” merges across sources Prompting / Constraints patterns/pattern_symbolic_constraint_unlock.md
Some facts can’t be retrieved though indexed Retrieval / Index patterns/pattern_vectorstore_fragmentation.md
Answers flip between sessions / tabs Memory / State patterns/pattern_memory_desync.md
Need a standard schema for snippets/citations Prompting / Traceability data-contracts.md
Non-English corpus drifts / tokenizer mismatch Language / Locale multilingual-guide.md
PII/compliance concerns with traces/logs Governance privacy-and-governance.md
Multi-agent tools fight each other Agents Multi-Agent_Problems.md
First prod call crashes after deploy Infra / Boot predeploy-collapse.md
Tools fire before data is ready (RAG boot fence) Infra / Boot patterns/pattern_bootstrap_deadlock.md

Still lost? Open the Beginner Guide symptom checklist first.


Families & maps (with exact fixes)

A) Prompting & Safety

Guard against injections, role drift, and schema leakage.

Verification: ΔS(question, context) ≤ 0.45; λ remains convergent across paraphrases; constraint probes do not flip λ.


B) Retrieval, Data & Vector Stores

Make the index correct, measured, and explainable.

Verification: coverage ≥ 0.70 to target section; ΔS(question, retrieved) ≤ 0.45; flat-high ΔS vs k ⇒ index/metric mismatch.


C) Reasoning & Logic Control

Detect and repair logic collapse, dead ends, and abstraction failures.

Verification: fix point when λ stays convergent after BBCR (bridge) + BBAM (variance clamp).


D) Memory & Long-Context

Keep threads coherent across sessions and very long windows.

Verification: E_resonance flat; ΔS stable at window joins.


E) Multi-Agent & Orchestration

Coordinate tools, roles, and shared memory without conflict.

Verification: when agents couple, ΔS does not spike; arbitration logs traceable.


F) Infra / Deploy

Boot in a known-good order, every time.

Verification: deterministic warm-up; idempotent index builds; version/secret checks pass.


G) Evaluation & Guardrails

Detect “double hallucination” and prevent regression.

Acceptance: retrieve QA coverage ≥ 0.70 and ΔS ≤ 0.45; λ convergent; repeatability across seeds.


Ask the AI to fix your AI (safe prompt)

Read the WFGY TXT OS and Problem Map docs. Extract ΔS, λ_observe, E_resonance and the modules (BBMC, BBPF, BBCR, BBAM).
Given my failure:

- symptom: [describe]
- traces: [ΔS probes, λ states if any]

Tell me:
1) which layer/family is failing and why,
2) which fix page to open,
3) minimal steps to push ΔS ≤ 0.45 and keep λ convergent,
4) how to verify the fix.

🔗 Quick-Start Downloads (60 sec)

Tool Link 3-Step Setup
WFGY 1.0 PDF Engine Paper 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>”
TXT OS (plain-text OS) TXTOS.txt 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly

Explore More

Layer Page What it’s for
⭐ Proof WFGY Recognition Map External citations, integrations, and ecosystem proof
⚙️ Engine WFGY 1.0 Original PDF tension engine and early logic sketch (legacy reference)
⚙️ Engine WFGY 2.0 Production tension kernel for RAG and agent systems
⚙️ Engine WFGY 3.0 TXT based Singularity tension engine (131 S class set)
🗺️ Map Problem Map 1.0 Flagship 16 problem RAG failure taxonomy and fix map
🗺️ Map Problem Map 2.0 Global Debug Card for RAG and agent pipeline diagnosis
🗺️ Map Problem Map 3.0 Global AI troubleshooting atlas and failure pattern map
🧰 App TXT OS .txt semantic OS with fast bootstrap
🧰 App Blah Blah Blah Abstract and paradox Q&A built on TXT OS
🧰 App Blur Blur Blur Text to image generation with semantic control
🏡 Onboarding Starter Village Guided entry point for new users

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