# Microsoft Power Automate — Guardrails and Fix Patterns
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> 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 when your workflow is built with **Power Automate** (cloud flows, AI Builder, custom connectors) and you see wrong citations, unstable answers, mixed sources, or silent failures that “look green” in run history. **Acceptance targets** - ΔS(question, retrieved) ≤ 0.45 - Coverage ≥ 0.70 to the intended section/record - λ remains convergent across 3 paraphrases --- ## Typical breakpoints → exact fixes - Output is plausible yet cites the wrong doc/snippet Fix No.1: **Hallucination & Chunk Drift** → [Hallucination](https://github.com/onestardao/WFGY/blob/main/ProblemMap/hallucination.md) · [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) - Vector similarity looks fine, meaning is off Fix No.5: **Embedding ≠ Semantic** → [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md) - Some facts exist in SharePoint/Dataverse but never surface in top-k Pattern: **Vectorstore Fragmentation** → [Vectorstore Fragmentation](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_vectorstore_fragmentation.md) - Can’t explain *why* a snippet was chosen; run history shows only final text Fix No.8: **Retrieval Traceability** with snippet schema → [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) · [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md) - Long chains or approvals flatten tone and drift logically Fix No.3/No.9: **Context Drift** and **Entropy Collapse** → [Context Drift](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md) · [Entropy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md) - Flow passes in Test but fails after environment or connection swap Infra: **Pre-Deploy/Bootstrap/Deadlock** → [Pre-Deploy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md) · [Bootstrap Ordering](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md) · [Deployment Deadlock](https://github.com/onestardao/WFGY/blob/main/ProblemMap/deployment-deadlock.md) - Confident tone with wrong answers in AI Builder actions Fix No.4: **Bluffing/Overconfidence** → [Bluffing](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bluffing.md) --- ## Minimal Power Automate pattern with WFGY checks Below is a compact flow outline. It enforces **cite-first schema**, **observable retrieval**, and a **ΔS/λ post-check**. ```txt Trigger: When an HTTP request is received Actions: 1) Initialize variable "k" = 10 2) Parse JSON "question" from request 3) HTTP → your retriever endpoint - Method: POST - Body: { "question": "@{variables('question')}", "k": "@{variables('k')}" } 4) Compose "context" = join(retrieved.snippets) 5) Compose "prompt" = SYSTEM: Cite lines before any explanation. TASK: Answer the user's question using the provided context. CONSTRAINTS: - Do not mix sources - Provide snippet_id for each citation CONTEXT: @{outputs('Compose_context')} QUESTION: @{variables('question')} 6) AI Builder / Custom Connector → LLM with "prompt" 7) HTTP → wfgyCheck (custom Azure Function) - Body: { "question": "@{variables('question')}", "context": "@{outputs('Compose_context')}", "answer": "@{outputs('LLM_action')}" } 8) Condition: If deltaS ≥ 0.60 OR lambda != "→" → Terminate flow (Warn) "High semantic stress. See trace log." Else → Return 200 with { answer, deltaS, lambda, coverage, citations[] } ```` **What this enforces** * Retrieval parameters are explicit and logged in flow run details. * Prompt is **schema-locked** with **cite-first**. * WFGY check runs after generation and can **fail fast** when ΔS is high or λ flips divergent. * Trace table (snippet\_id ↔ citation) is returned for audit. Reference specs [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md) · [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) · [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) · [Data Contracts](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md) --- ## Power Automate specific gotchas * **Environment or connection drift**: different Dataverse/SharePoint connections between ingestion and query. Pin connections per environment and re-verify secrets. See [Pre-Deploy Collapse](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md) * **Throttling/parallel branches** change ordering of records. Add a **rerank** stage only after per-source ΔS ≤ 0.50. See [Rerankers](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rerankers.md) * **Parse JSON** actions silently drop fields, breaking snippet\_id propagation. Validate schemas and keep `snippet_id` mandatory. See [Retrieval Traceability](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md) * **Embedding metric mismatch** between ingestion code (Azure Function/Logic App) and query side. Normalize vectors and pin cosine vs. inner product. See [Embedding ≠ Semantic](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md) * **Scheduled flows** rebuild indices unintentionally. Make builds idempotent and gate by boot checks. See [Bootstrap Ordering](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md) --- ## When to escalate * ΔS remains ≥ 0.60 after chunking and retrieval fixes Work through the playbook, then rebuild the index with explicit metric flags and unit normalization. [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md) * Answers flip between Dev/UAT/Prod Verify version skew, connection references, and secrets. [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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