WFGY/ProblemMap/GlobalFixMap/Automation/README.md

Automation & Integrations — Index

Zapier / Make / n8n adapters for RAG pipelines and agent workflows. Use this page to route automation bugs to the right structural fix and verify with ΔS ≤ 0.45 and convergent λ.

Quick links (tool adapters)

• Zapier Guardrails: open
• Make (Integromat) Guardrails: open
• n8n Guardrails: open

What typically breaks in automations

• No.14 Bootstrap ordering: tools fire before deps are ready (e.g., vector index empty, secrets missing).
  Fix spec: Bootstrap Ordering
• No.15 Deployment deadlock: circular waits between retriever/index, DB/migrator, or tool auth loops.
  Fix spec: Deployment Deadlock
• No.16 Pre-deploy collapse: first call after deploy crashes due to version skew / missing env.
  Fix spec: Pre-Deploy Collapse
• RAG miswiring: wrong field mapping → the retriever queries an empty/partial store; citations don’t line up.
  Fix spec: Retrieval Traceability · Data Contracts
• Hybrid retrievers acting weird: HyDE + BM25 tokenization split, noisy ordering.
  Fix spec: Retrieval Playbook · Rerankers
• Webhook storms / duplicates: idempotency keys missing; retries create conflicting states.
  Pattern: Bootstrap Deadlock (semantic boot fence)

Minimal repair checklist (paste into your runbook)

1. Warm-up fence before LLM/RAG steps
   • Check VECTOR_READY == true, INDEX_HASH matches, and secret set present.
   • If not ready → short-circuit flow and retry with backoff.
     Specs: bootstrap-ordering.md
2. Idempotent triggers
   • Deduplicate by (source_id, revision, hash); discard stale retries.
3. RAG contract at the boundary
   • Require snippet_id, section_id, source_url, offsets.
   • Enforce cite → then explain; forbid cross-section reuse.
     Specs: data-contracts.md · retrieval-traceability.md
4. Observability probes
   • Log ΔS(question, retrieved) and λ state per step; alert when ΔS ≥ 0.60.
     Reference: RAG Architecture & Recovery
5. Fail the merge on regression
   • Add CI gate for coverage ≥ 0.70 and ΔS ≤ 0.45.
     Eval: eval_rag_precision_recall.md

How to route a live bug

• Looks fine but answers are wrong: run ΔS and coverage → if high/low, fix chunking/retrieval first.
  Start: Retrieval Playbook
• First run after deploy fails: jump to infra fixes.
  Start: predeploy-collapse.md
• Hybrid ranking is chaotic: confirm tokenizer parity → consider reranker clamp.
  Start: rerankers.md

Copy/paste prompt (safe to use with your assistant)

I’m running an automation flow (Zapier/Make/n8n) that calls a RAG step.
Read the WFGY Problem Map pages for bootstrap-ordering, predeploy-collapse,
retrieval-traceability, data-contracts, and retrieval-playbook.
Propose the minimal structural fixes to achieve:

* ΔS(question, retrieved) ≤ 0.45
* coverage ≥ 0.70
* convergent λ across 3 paraphrases
  Return a step-by-step checklist I can paste into my scenario.

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🔗 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

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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