# n8n Guardrails and Patterns
🧭 Quick Return to Map
> You are in a sub-page of **Automation Platforms**. > To reorient, go back here: > > - [**Automation Platforms** — stabilize no-code workflows and integrations](./README.md) > - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md) > - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md) > > 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 page when your RAG or agent workflow runs in **n8n**. It maps common automation failures to the exact structural fixes in the Problem Map and gives a minimal recipe you can paste into a workflow. **Core acceptance** - ΔS(question, retrieved) ≤ 0.45 - coverage ≥ 0.70 for the target section - λ stays convergent across 3 paraphrases --- ## Typical breakpoints and the right fix - Nodes fire before dependencies are ready Fix No.14: **Bootstrap Ordering** → [Open](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md) - First call after deploy crashes or uses wrong env/secret Fix No.16: **Pre-Deploy Collapse** → [Open](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md) - Circular waits between index build and retriever, or Merge nodes loop forever Fix No.15: **Deployment Deadlock** → [Open](https://github.com/onestardao/WFGY/blob/main/ProblemMap/deployment-deadlock.md) - High vector similarity but wrong meaning Fix No.5: **Embedding ≠ Semantic** → [Open](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md) - Wrong snippet chosen or citations do not line up Fix No.8: **Retrieval Traceability** → [Open](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) Contract the payload: **Data Contracts** → [Open](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md) - Hybrid retrieval performs worse than a single retriever Pattern: **Query Parsing Split** → [Open](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_query_parsing_split.md) Also review: **Rerankers** → [Open](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md) - Some facts never surface even though indexed Pattern: **Vectorstore Fragmentation** → [Open](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_vectorstore_fragmentation.md) - Two sources get merged in the answer Pattern: **Symbolic Constraint Unlock (SCU)** → [Open](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_symbolic_constraint_unlock.md) --- ## Minimal setup checklist for any n8n flow 1) **Warm-up fence before RAG or LLM nodes** Validate `VECTOR_READY == true`, `INDEX_HASH` matches, and secrets exist. If not ready, short-circuit to a Wait node then retry with a capped counter. Spec: [Bootstrap Ordering](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md) 2) **Idempotency and dedupe** Compute `dedupe_key = sha256(source_id + revision + index_hash)`. Check or write the key using Redis, Postgres, or n8n’s Data Store. Drop duplicates. 3) **RAG boundary contract** Require fields: `snippet_id`, `section_id`, `source_url`, `offsets`, `tokens`. Enforce cite then explain. Forbid cross section reuse. Specs: [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md) · [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) 4) **Observability probes** Log ΔS(question, retrieved). Log λ per step: retrieve, assemble, reason. Alert when ΔS ≥ 0.60 or λ flips divergent. Overview: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) 5) **Concurrency guard** Use a single writer for index updates. Set queue mode or global mutex for write steps. See: [Deployment Deadlock](https://github.com/onestardao/WFGY/blob/main/ProblemMap/deployment-deadlock.md) 6) **Regression gate** Require coverage ≥ 0.70 and ΔS ≤ 0.45 before publishing. Eval: [RAG Precision/Recall](https://github.com/onestardao/WFGY/blob/main/ProblemMap/eval/eval_rag_precision_recall.md) --- ## n8n recipe you can copy > Replace the concrete nodes with your stack. Keep the guardrails. 1. **Trigger** Fixed `source_id` and `revision`. Record `wf_rev`. 2. **Warm-up Check (Code node)** Pull `INDEX_HASH`, `VECTOR_READY`, and secrets. If not ready, set `ready=false`. 3. **Branch: Not ready** Wait 30–90 seconds. Increment a retry counter. Stop after N attempts. 4. **Branch: Ready** **Retrieval node** - Call retriever with explicit metric and same analyzer as the writer. - Emit `snippet_id`, `section_id`, `source_url`, `offsets`, `tokens`. **ΔS probe node** - Compute ΔS(question, retrieved). If ΔS ≥ 0.60 set `needs_fix=true`. **LLM node** - Model reads TXT OS and follows the WFGY schema. Enforce cite then explain. **Trace sink** - Store `question`, `snippet_id`, `ΔS`, `λ_state`, `INDEX_HASH`, `dedupe_key`. **Idempotency guard** - Before side effects, check the KV for `dedupe_key`. Skip if it already exists. --- ## Copy-paste prompt for the LLM node ``` I uploaded TXT OS and the WFGY Problem Map files. This n8n flow retrieved {k} snippets with fields {snippet\_id, section\_id, source\_url, offsets}. Question: "{user\_question}" Do: 1. Validate cite-then-explain. If citations are missing, fail fast and return the fix tip. 2. If ΔS(question, retrieved) ≥ 0.60, propose the minimal structural fix referencing: retrieval-playbook, retrieval-traceability, data-contracts, rerankers. 3. Return a JSON plan: { "citations": \[...], "answer": "...", "λ\_state": "→|←|<>|×", "ΔS": 0.xx, "next\_fix": "..." } Keep it auditable and short. ``` --- ## Common n8n gotchas - **Set** or **Move** nodes rename fields and break your data contract Lock field names and run a schema check before the LLM node. - Merge or Split In Batches cause duplicate writes Add a single writer stage with idempotency keys and a queue. - Cron triggers overlap with long runs Use a global mutex or skip if `dedupe_key` already exists. - HyDE prompt built inside the flow differs from the API client Keep tokenizer and casing identical, or switch to reranking. See: [Rerankers](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md) --- ## When to escalate - ΔS stays ≥ 0.60 after chunk and retrieval fixes Rebuild index with explicit metric and normalization. See: [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) - Answers alternate across runs with identical input Investigate memory desync and version skew. See: [Pre-Deploy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md) --- ### 🔗 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 | Layer | Page | What it’s for | | --- | --- | --- | | ⭐ Proof | [WFGY Recognition Map](/recognition/README.md) | External citations, integrations, and ecosystem proof | | ⚙️ Engine | [WFGY 1.0](/legacy/README.md) | Original PDF tension engine and early logic sketch (legacy reference) | | ⚙️ Engine | [WFGY 2.0](/core/README.md) | Production tension kernel for RAG and agent systems | | ⚙️ Engine | [WFGY 3.0](/TensionUniverse/EventHorizon/README.md) | TXT based Singularity tension engine (131 S class set) | | 🗺️ Map | [Problem Map 1.0](/ProblemMap/README.md) | Flagship 16 problem RAG failure taxonomy and fix map | | 🗺️ Map | [Problem Map 2.0](/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis | | 🗺️ Map | [Problem Map 3.0](/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map | | 🧰 App | [TXT OS](/OS/README.md) | .txt semantic OS with fast bootstrap | | 🧰 App | [Blah Blah Blah](/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS | | 🧰 App | [Blur Blur Blur](/OS/BlurBlurBlur/README.md) | Text to image generation with semantic control | | 🏡 Onboarding | [Starter Village](/StarterVillage/README.md) | Guided entry point for new users | If this repository helped, starring it improves discovery so more builders can find the docs and tools. 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