WFGY/ProblemMap/GlobalFixMap/PromptAssembly/citation_first.md

Citation-First Prompting — Guardrails and Fix Pattern

🧭 Quick Return to Map

You are in a sub-page of PromptAssembly.
To reorient, go back here:

• PromptAssembly — prompt engineering and workflow composition
• WFGY Global Fix Map — main Emergency Room, 300+ structured fixes
• WFGY Problem Map 1.0 — 16 reproducible failure modes

Think of this page as a desk within a ward.
If you need the full triage and all prescriptions, return to the Emergency Room lobby.

Stabilize evidence-based answers by requiring citations before explanation. This page gives a minimal contract, validation steps, and fast routes to structural fixes when citations vanish, drift, or point to the wrong text.

Open these first

• Visual map & recovery: RAG Architecture & Recovery
• Snippet traceability & fields: Retrieval Traceability
• Contract the payload: Data Contracts
• Ordering control: Rerankers
• Long chains & drift: Context Drift, Entropy Collapse
• Semantic ≠ cosine: Embedding ≠ Semantic
• Reasoning collapse: Logic Collapse

When to use

• Answers sound right but show no citations.
• Citations appear but don’t align with the quoted text.
• Different runs cite different sections for the same question.
• After reranking, citations drift or vanish.
• Multi-turn dialogs slowly lose the cite-then-explain order.

Acceptance targets

• Cite-then-explain compliance ≥ 0.98 over 50 queries.
• Field completeness ≥ 0.99 for: snippet_id, section_id, source_url, offsets, tokens.
• ΔS(question, retrieved) ≤ 0.45 and stable across 3 paraphrases.
• Coverage ≥ 0.70 to the target section.
• λ convergent across two seeds.

---

Fix in 60 seconds

1. Enforce the contract
   The model must cite before any reasoning. Reject outputs that invert the order.

2. Validate fields
   Require the full snippet schema. Reject partial or fuzzy references.

3. Pin rerank & order
   If citations change with header tweaks, lock your header order and rerank configuration.

4. Probe ΔS and λ
   If ΔS stays high while citations look plausible, rebuild chunking or metrics.

---

Minimal prompt block to paste

System:
You must CITE before you EXPLAIN.
Required fields per snippet: snippet\_id, section\_id, source\_url, offsets, tokens.
Order is strict:

1. "citations": \[...]
2. "answer": "..."

If citations are missing or fields incomplete, STOP and return:
{"citations": \[], "answer": "", "next\_fix": "open data-contracts & retrieval-traceability"}

User:
Question: "\<user\_question>"
Top-k retrieved: <passed from retriever>
Acceptance: ΔS(question,retrieved) ≤ 0.45; coverage ≥ 0.70.

---

JSON response shape (auditable)

{
  "citations": [
    {
      "snippet_id": "S-28391",
      "section_id": "SEC-3.2",
      "source_url": "https://...",
      "offsets": [2312, 2450],
      "tokens": 172
    }
  ],
  "answer": "…",
  "λ_state": "→|←|<>|×",
  "ΔS": 0.37
}

---

Typical breakpoints → exact fix

• Citations missing but answer present Reject and re-emit with the contract. Open: Data Contracts

• Citation fields incomplete or wrong offsets Enforce the full schema, verify offsets/tokens against the corpus. Open: Retrieval Traceability

• High similarity but wrong meaning Rerank or rebuild with correct metric/normalization. Open: Retrieval Playbook, Embedding ≠ Semantic

• Header tweak breaks citations Freeze header order; clamp variance with BBAM. Open: Logic Collapse

• Long runs lose citation discipline Split plan, bridge with BBCR; add mid-chain citation checks. Open: Context Drift, Entropy Collapse

---

Validator stub (copy into your pipeline)

Step 1  parse JSON strictly → if fail, stop.
Step 2  require citations[].length ≥ 1 before answer.
Step 3  verify fields & offsets; reject if any missing.
Step 4  compute ΔS and coverage; block if ΔS>0.45 or coverage<0.70.
Step 5  log λ across three paraphrases; alert if non-convergent.

Eval gates before ship

• Cite-then-explain ≥ 0.98 on 50 queries.
• Field completeness ≥ 0.99.
• ΔS ≤ 0.45, coverage ≥ 0.70, λ convergent on two seeds.

---

🔗 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

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Explore More

Layer	Page	What it’s for
Proof	WFGY Recognition Map	External citations, integrations, and ecosystem proof
Engine	WFGY 1.0	Original PDF based tension engine
Engine	WFGY 2.0	Production tension kernel and math engine for RAG and agents
Engine	WFGY 3.0	TXT based Singularity tension engine, 131 S class set
Map	Problem Map 1.0	Flagship 16 problem RAG failure checklist and fix map
Map	Problem Map 2.0	RAG focused recovery pipeline
Map	Problem Map 3.0	Global Debug Card, image as a debug protocol layer
Map	Semantic Clinic	Symptom to family to exact fix
Map	Grandma’s Clinic	Plain language stories mapped to Problem Map 1.0
Onboarding	Starter Village	Guided tour for newcomers
App	TXT OS	TXT semantic OS, fast boot
App	Blah Blah Blah	Abstract and paradox Q and A built on TXT OS
App	Blur Blur Blur	Text to image with semantic control
App	Blow Blow Blow	Reasoning game engine and memory demo

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