8.5 KiB
Semantic Kernel — Guardrails and Fix Patterns
🧭 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
Fix in 60 seconds
-
Measure ΔS
Compute ΔS(question, retrieved) and ΔS(retrieved, anchor). Stable < 0.40, transitional 0.40–0.60, risk ≥ 0.60. -
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. -
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
- Verify
Three paraphrases reach ΔS ≤ 0.45 and coverage ≥ 0.70. λ stays convergent.
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 stampmem_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
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
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.
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
🔗 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 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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