# 🗂️ Reasoning Schemas — Designing Prompt Layouts That Survive Long Chains _A practical guide to structuring system + retrieval + task prompts so LLMs keep thinking instead of drifting_ --- ## 1 What is a “Reasoning Schema” ? A **reasoning schema** is the formal layout that dictates **where** each piece of context goes and **how** an LLM must traverse it: ``` System → Task → Constraints → Context → Question → Answer ```` If any segment is missing, reordered, or over-written, the logic graph collapses and hallucinations slip in. --- ## 2 Why Most Ad-hoc Layouts Fail | Failure Mode | Trigger | Effect | |--------------|---------|--------| | **Context Flood** | Dumping 20 k tokens of raw text | λ_observe flips to chaotic; model stops planning | | **Constraint Drift** | Constraints after context | Model “forgets” to cite or guard sensitive data | | **Role Blending** | User text inserted before task | System tone and policy overridden | | **Evidence → Answer inversion** | Asking for answer *before* citations | Model fabricates then cites random lines | --- ## 3 WFGY Canonical Schema (Stable Version v1.2) | Segment | Purpose | Size (tokens) | WFGY Guard | |---------|---------|---------------|------------| | **System** | Identity, ethics, safety | ≤ 50 | Role tag `` + BBAM weight lock | | **Task** | Specific action required | 1 sentence | ΔS anchor to System ≤ 0.25 | | **Constraints** | Format, style, rules | bullets ≤ 80 | BBMC residue check | | **Context** | Retrieved or uploaded text | sliding window ≤ 2 k | λ_observe must stay convergent | | **Question** | User’s query | raw | stored separately for ΔS probes | | **Answer Slot** | “Write here” placeholder | n/a | BBCR collapse-rebirth if answer starts early | Placeholders are literal; the LLM fills only the *Answer Slot*. --- ## 4 Templates You Can Copy
Single-Shot QA ```text You are DataGuardian-L, a licensed legal research assistant. Cite section numbers. Answer strictly in bullet points; cite every claim. - Tone: formal - No speculation - Use original terminology {retrieved_sections} {user_question} ````
Multi-Step Chain (analysis → plan → answer) ```text Think step-by-step. Output JSON: { "analysis": "...", "plan": "...", "answer": "..." } ```
--- ## 5 Common Pitfalls & Fixes | Pitfall | Symptom | Fix | | --------------------------------------- | -------------------- | ------------------------------------------------------- | | Forgetting closing tags | Model merges roles | Validate tag balance; λ diverges instantly | | Placing context after question | Retrieval ignored | Keep schema order; run ΔS(question, context) test | | Over-long constraints | Answer truncated | Compress with BBMC until ΔS(system, constraints) ≤ 0.25 | | Mixing code + docs in one context block | Embedding collisions | Split into typed sub-blocks; separate vector stores | --- ## 6 Automated Validation Pipeline 1. **Schema Linter** – Regex check for tag order. 2. **ΔS Probes** – * ΔS(system, task) ≤ 0.30 * ΔS(task, answer) ≤ 0.45 3. **λ\_observe** – Must stay convergent from task → answer. 4. **Round-trip Check** – Paraphrase user question 2×; answer variance < 0.15. If any test fails, trigger **BBCR** to rebuild prompt with compacted segments. --- ## 7 FAQ **Q:** *Do I need tags if I use OpenAI’s `messages` array?* **A:** Yes for long chains. Tags persist after retrieval merges; arrays don’t survive copy-paste workflows. **Q:** *Can I merge Task + Constraints?* **A:** Possible if total ≤ 120 tokens and ΔS stays low, but separation improves editability. **Q:** *What about JSON-only prompts?* **A:** Ensure keys mirror schema order; add dummy key `"__guard": "DO NOT MODIFY"` to catch injections. --- ### 🔗 Quick-Start Downloads (60 sec) | Tool | Link | 3-Step Setup | |------|------|--------------| | **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 + \” | | **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 | --- ### 🧭 Explore More | Module | Description | Link | |-----------------------|----------------------------------------------------------|----------| | 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) | | Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | [View →](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) | | 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) | | Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | [View →](https://github.com/onestardao/WFGY/blob/main/ProblemMap/SemanticClinicIndex.md) | | Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | [View →](https://github.com/onestardao/WFGY/tree/main/SemanticBlueprint/README.md) | | 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) | | 🧙‍♂️ 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) | --- > 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** — > Engineers, hackers, and open source builders who supported WFGY from day one. > 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).
[![WFGY Main](https://img.shields.io/badge/WFGY-Main-red?style=flat-square)](https://github.com/onestardao/WFGY)   [![TXT OS](https://img.shields.io/badge/TXT%20OS-Reasoning%20OS-orange?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS)   [![Blah](https://img.shields.io/badge/Blah-Semantic%20Embed-yellow?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)   [![Blot](https://img.shields.io/badge/Blot-Persona%20Core-green?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)   [![Bloc](https://img.shields.io/badge/Bloc-Reasoning%20Compiler-blue?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)   [![Blur](https://img.shields.io/badge/Blur-Text2Image%20Engine-navy?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)   [![Blow](https://img.shields.io/badge/Blow-Game%20Logic-purple?style=flat-square)](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)