Semantic Kernel

🧭 Quick Return to Map

You are in a sub-page of Agents & Orchestration.
To reorient, go back here:

• Agents & Orchestration — orchestration frameworks and guardrails
• 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 when your pipeline uses Semantic Kernel planners, function tools, memories, or skills and you see wrong snippets, plan drift, tool loops, or JSON shape errors. The checks below localize the fault, then route 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: Retrieval Traceability
• Snippet and citation schema: Data Contracts
• Hybrid order control: Rerankers
• Hallucination and chunk drift: Hallucination
• Prompt injection fences: Prompt Injection
• Long chain failures: Context Drift, Entropy Collapse
• Agent role conflicts: Multi-Agent Problems

Core acceptance

• ΔS(question, retrieved) ≤ 0.45
• Coverage ≥ 0.70 for the intended section
• λ remains convergent across three paraphrases and two seeds

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Fix in 60 seconds

1. Measure ΔS
   Compute ΔS(question, retrieved) and ΔS(retrieved, anchor). Stable < 0.40, transitional 0.40–0.60, risk ≥ 0.60.

2. Clamp the planner
   Freeze the planner schema. Require task → constraints → tools → cite then explain. If plan text changes order between runs, lock headers and set deterministic seeds.

3. Apply the module

• Retrieval drift → BBMC with Data Contracts
• JSON tool variance → tighten schemas and apply Prompt Injection fences
• Long plans degrade → insert BBCR bridges and cap step depth per segment

4. Verify
   Three paraphrases reach ΔS ≤ 0.45 and coverage ≥ 0.70. λ stays convergent.

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Typical Semantic Kernel breakpoints → exact fixes

• Planner invents tools or repeats steps
  Lock tool registry. Enforce idempotent effects with keys.
  Open: Multi-Agent Problems, Data Contracts

• Memory recalls stale facts after refresh
  Split namespaces and stamp mem_rev, mem_hash.
  Open: patterns: memory desync

• High similarity yet wrong meaning
  Metric or analyzer mismatch across write and read paths.
  Open: Embedding ≠ Semantic

• Hybrid retrievers worse than single
  Query parsing split and misweighted rerank.
  Open: Query Parsing Split, Rerankers

• Tool call JSON fails silently
  Require strict argument schema. Echo schema at each call.
  Open: Prompt Injection

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Minimal SK pattern with WFGY gates

Planner:
  1) Task
  2) Constraints: cite-first, snippet schema, tool JSON strict
  3) Tools with idempotency keys
  4) Answer: cite then explain

Runtime:
  - Retrieve(k = 10 with unified analyzer)
  - Assemble(prompt with headers in fixed order)
  - Reason(model call)
  - WFGY gate: compute ΔS, record λ, verify coverage
  - If ΔS ≥ 0.60 or λ divergent, stop and return fix tip

What this enforces

• Deterministic header order across steps
• Observable retrieval with stable metric
• Schema locked citations
• A stop gate when structure collapses

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SK specific gotchas

• Planner temperature is non zero while tools expect strict JSON. Set low variance and validate before acting.
• Memories are written by multiple skills without namespace fences. Use separate namespaces and revision stamps.
• Rerun of the same plan writes duplicate side effects. Add idempotency keys before external actions.

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When to escalate

• ΔS stays ≥ 0.60 after chunk and retrieval fixes Rebuild index and recheck analyzers. Open: Retrieval Playbook

• Answers flip between sessions with unchanged inputs Check version skew and deploy order. Open: Pre-Deploy Collapse

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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

Layer	Page	What it’s for
⭐ Proof	WFGY Recognition Map	External citations, integrations, and ecosystem proof
⚙️ Engine	WFGY 1.0	Original PDF tension engine and early logic sketch (legacy reference)
⚙️ Engine	WFGY 2.0	Production tension kernel for RAG and agent systems
⚙️ Engine	WFGY 3.0	TXT based Singularity tension engine (131 S class set)
🗺️ Map	Problem Map 1.0	Flagship 16 problem RAG failure taxonomy and fix map
🗺️ Map	Problem Map 2.0	Global Debug Card for RAG and agent pipeline diagnosis
🗺️ Map	Problem Map 3.0	Global AI troubleshooting atlas and failure pattern map
🧰 App	TXT OS	.txt semantic OS with fast bootstrap
🧰 App	Blah Blah Blah	Abstract and paradox Q&A built on TXT OS
🧰 App	Blur Blur Blur	Text to image generation with semantic control
🏡 Onboarding	Starter Village	Guided entry point for new users

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