AWS CodeWhisperer: Guardrails and Fix Patterns

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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.

Use this guide when completions or chat inside CodeWhisperer feel flaky, tool steps loop, or RAG-style answers cite the wrong things. The fixes below map to WFGY pages with measurable targets so you can verify quickly and avoid infra changes.

Open these first

Visual map and recovery: RAG Architecture & Recovery
End-to-end retrieval knobs: Retrieval Playbook
Why this snippet, not another: Retrieval Traceability
Ordering control for top-k: Rerankers
Embedding vs meaning drift: Embedding ≠ Semantic
Long dialogs and chain fatigue: Context Drift, Entropy Collapse
Prompt injection and schema locks: Prompt Injection
Multi-agent conflicts and handoffs: Multi-Agent Problems
Cold boot and deploy ordering: Bootstrap Ordering, Deployment Deadlock, Pre-Deploy Collapse
Snippet and citation schema: Data Contracts

Core acceptance

ΔS(question, retrieved) ≤ 0.45
Coverage ≥ 0.70 to the correct section
λ remains convergent across three paraphrases and two seeds
E_resonance flat across the dialog window

Typical CodeWhisperer breakpoints → exact fix

Region or account skew between your IDE plugin, credentials, and model endpoint. Verify region and identity consistently. If first call in a fresh boot fails, fix ordering. Open: Bootstrap Ordering, Pre-Deploy Collapse
IDE chat cites the wrong file or wrong snippet after retrieval. Lock the snippet contract and require cite-then-explain. Open: Retrieval Traceability, Data Contracts
High similarity yet wrong answer when CodeWhisperer consults docs. Suspect metric or index mismatch, or fragmented store. Open: Embedding ≠ Semantic, Vectorstore Fragmentation
Hybrid retrieval gets worse than single retriever in chat plans. Stabilize query split and lock reranking deterministically. Open: Query Parsing Split, Rerankers
Tool loop or agent handoff stalls when chat triggers build, test, or docs tools. Split memory namespaces, apply timeouts, and fence writes by mem_rev and mem_hash. Open: Multi-Agent Problems
Security or policy blocks cause silent fallbacks that change outputs. Make refusal paths explicit and keep the schema locked to avoid hidden branches. Open: Prompt Injection

Fix in 60 seconds

Measure ΔS Compute ΔS(question, retrieved) and ΔS(retrieved, anchor section). Stable < 0.40, transitional 0.40–0.60, risk ≥ 0.60.
Probe λ_observe Re-order headers minimally and vary k as 5, 10, 20. If ΔS stays flat and high, rebuild metric and normalize. If λ flips on harmless paraphrase, clamp with BBAM.
Apply the module Retrieval drift → BBMC + Data Contracts Reasoning collapse → BBCR bridge + BBAM, then verify with Logic Collapse Dead ends in long chains → BBPF alternate paths
Verify Coverage ≥ 0.70 on three paraphrases. λ convergent on two seeds. E_resonance flat over ten-step dialogs.

IDE checklist for stable runs

Warm-up fence before chat or retrieval. Confirm INDEX_HASH, VECTOR_READY, and current credentials. See: Bootstrap Ordering
Idempotency for any write step triggered by chat tools. Compute dedupe_key = sha256(source_id + revision + index_hash) and drop duplicates.
Cite-then-explain as a hard rule in the prompt template. Forbid cross-section reuse unless explicitly allowed by contract.
Observability probes inside the IDE task. Log ΔS and λ states for retrieve, assemble, reason. Alert when ΔS ≥ 0.60 or λ turns divergent.
Regression gate before you trust the session. See: RAG Precision/Recall

Copy-paste prompt for CodeWhisperer Chat

You have TXTOS and the WFGY Problem Map loaded.

My task:
- symptom: [one line]
- traces: ΔS(question,retrieved)=..., ΔS(retrieved,anchor)=..., λ states across 3 paraphrases

Do:
1) identify which layer fails and why,
2) point me to the exact WFGY page,
3) give minimal steps to push ΔS ≤ 0.45 and keep λ convergent,
4) return a short JSON plan with {citations, steps, ΔS, λ_state, next_fix}.
Use BBMC, BBPF, BBCR, BBAM when relevant. Enforce cite-then-explain.

When to escalate

ΔS stays ≥ 0.60 after chunking and metric fixes Rebuild with the semantic chunking checklist and verify on a small gold set. Open: Chunking Checklist
Answers flip between identical runs in the same IDE session Investigate memory and version skew. Open: Pre-Deploy Collapse

🔗 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 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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