WFGY/ProblemMap/GlobalFixMap/MemoryLongContext
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Memory & Long-Context — Global Fix Map

Keep threads coherent across long windows and session restarts.
Detect and repair entropy melt, boundary drift, state forks, and ghost contexts.


What this page is

  • A compact checklist for long contexts and multi-session memory.
  • Copyable guardrails to stop drift and collapse before they spread.
  • Concrete measures with ΔS and λ_observe to verify stability.

When to use

  • Dialogs grow past 50k100k tokens and answers degrade.
  • Facts flip after tab refresh or model switch.
  • Citations look right but reasoning goes flat or chaotic.
  • OCR transcripts look fine but capitalization and spacing drift.
  • Multi-day support threads lose task state or rewrite history.

Quick routes to per-page guides


Acceptance targets

  • Retrieval coverage ≥ 0.70 to the intended section
  • ΔS(question, retrieved) ≤ 0.45 and joins ≤ 0.50
  • λ remains convergent across three paraphrases
  • No state fork across tabs or agents for the same task_id

🔗 Quick-Start Downloads (60 sec)

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

🧭 Explore More

Module Description Link
WFGY Core WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack View →
Problem Map 1.0 Initial 16-mode diagnostic and symbolic fix framework View →
Problem Map 2.0 RAG-focused failure tree, modular fixes, and pipelines View →
Semantic Clinic Index Expanded failure catalog: prompt injection, memory bugs, logic drift View →
Semantic Blueprint Layer-based symbolic reasoning & semantic modulations View →
Benchmark vs GPT-5 Stress test GPT-5 with full WFGY reasoning suite View →
🧙‍♂️ Starter Village 🏡 New here? Lost in symbols? Click here and let the wizard guide you through Start →

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