Anthropic (Claude): 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.

A compact field guide to stabilize Anthropic workflows that touch RAG, tools, multi-agent plans, and long dialogs. Use these checks to localize the failure, then jump to the exact WFGY fix page.

Open these first

Visual map and recovery: RAG Architecture & Recovery
End to end retrieval knobs: Retrieval Playbook
Why this snippet (traceability schema): Retrieval Traceability
Ordering control: Rerankers
Embedding vs meaning: Embedding ≠ Semantic
Hallucination and chunk boundaries: Hallucination
Long chains and entropy: Context Drift, Entropy Collapse
Symbolic collapse and recovery: Logic Collapse
Prompt injection and schema locks: Prompt Injection
Multi-agent conflicts: Multi-Agent Problems
Bootstrap and deploy issues: 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 target section
λ remains convergent across three paraphrases and two seeds

Fix in 60 seconds

Measure ΔS Compute ΔS(question, retrieved) and ΔS(retrieved, expected anchor). Thresholds: stable < 0.40, transitional 0.40–0.60, risk ≥ 0.60.
Probe with λ_observe Vary k in retrieval (5, 10, 20). If ΔS stays flat and high, suspect metric or index mismatch. Reorder prompt headers; if ΔS spikes, lock the schema.
Apply the module

Retrieval drift → BBMC plus Data Contracts.
Reasoning collapse → BBCR bridge plus BBAM variance clamp, then verify with Logic Collapse.
Hallucination re-entry after correction → see Pattern: Hallucination Re-entry.

Typical Anthropic breakpoints and the right fix

System vs user role mixing. Claude is sensitive to misplaced policy text inside user turns. Move all non-task policy to system. Re-test ΔS. Open: Retrieval Traceability, Data Contracts.
JSON tool protocol variance. Tool schemas that allow free text responses raise ΔS and create flip states. Enforce strict argument schemas and echo back the schema in every tool step. Open: Prompt Injection.
HyDE plus BM25 query split in reruns. If recall is high but top-k order is unstable, lock the two-stage query and rerank deterministically. Open: Pattern: Query Parsing Split, Rerankers.
Tool loop or agent handoff stalls with partial memory writes. Split memory namespaces and lock writes by mem_rev and mem_hash. Open: Multi-Agent Problems.
Safety refusal that hides the cited snippet. Use citation-first prompting and SCU (symbolic constraint unlock). Open: Retrieval Traceability, Pattern: SCU.

Deep diagnostics

Three-paraphrase probe. Ask the same question three ways. Log ΔS and λ for each. If λ flips on harmless paraphrase, clamp with BBAM and tighten snippet schema.
Anchor triangulation. Compare ΔS to the expected anchor section and to a decoy section. If ΔS is close for both, re-chunk and re-embed.
Chain length audit. If entropy rises after 25–40 steps, split the plan, then re-join with a BBCR bridge. Open: Context Drift, Entropy Collapse.

Escalate and structural fixes

Index or metric mismatch. If ΔS stays high across seeds, rebuild with the semantic chunking checklist and verify with a small gold set. Open: Embedding ≠ Semantic, Chunking Checklist.
Cold boot or first call crash in fresh deploys. Check ordering, secrets, and version skew. Open: Bootstrap Ordering, Pre-deploy Collapse.
Live instability. Add live probes and backoff guards. Open: Live Monitoring for RAG, Debug Playbook.

Copy-paste prompt

You have TXTOS and the WFGY Problem Map loaded.

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

Tell me:
1) failing layer and why,
2) the exact WFGY page to open,
3) the minimal steps to push ΔS ≤ 0.45 and keep λ convergent,
4) a reproducible test to verify the fix.
Use BBMC, BBPF, BBCR, BBAM when relevant.

🔗 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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