14 KiB
Zendesk: Guardrails and Fix Patterns
🧭 Quick Return to Map
You are in a sub-page of Chatbots & CX.
To reorient, go back here:
- Chatbots & CX — customer dialogue flows and conversational stability
- 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 page when your Zendesk experience blends Flow Builder or Advanced AI, Help Center articles, triggers, and webhooks connected to your RAG stack. The checks localize the failing layer and jump to the exact WFGY fix page. Links are absolute and text only.
Open these first
- Visual map and recovery: rag-architecture-and-recovery.md
- End to end retrieval knobs: retrieval-playbook.md
- Traceability schema and citation rules: retrieval-traceability.md
- Data schema locks: data-contracts.md
- Embedding vs meaning: embedding-vs-semantic.md
- Chunk boundaries and hallucination: hallucination.md
- Long dialogs and entropy: context-drift.md, entropy-collapse.md
- Prompt injection and tool schema: prompt-injection.md
- Multi agent and handoff conflicts: Multi-Agent_Problems.md
- Boot order and deploy traps: bootstrap-ordering.md, deployment-deadlock.md, predeploy-collapse.md
- Ordering control and rank: rerankers.md
Core acceptance for CX
- ΔS(question, retrieved) ≤ 0.45
- Coverage ≥ 0.70 to the target section
- λ remains convergent across three paraphrases and two seeds
- E_resonance stays flat over long threads
Fix in 60 seconds
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Measure ΔS Compute ΔS(question, retrieved) and ΔS(retrieved, expected anchor). Stable below 0.40, transitional 0.40 to 0.60, risk at or above 0.60.
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Probe λ_observe Change k to 5, 10, 20. Reorder prompt headers. If λ flips on harmless paraphrases, lock schema and clamp variance with BBAM.
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Apply module
- Retrieval drift → BBMC with retrieval-traceability.md and data-contracts.md
- Reasoning collapse in long chats → BBCR bridge with BBAM, verify with context-drift.md
- Dead ends in toolchains → BBPF alternate paths
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Verify Three paraphrases meet coverage and ΔS targets. λ convergent on two seeds.
Typical Zendesk symptoms → exact fix
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Answer cites the wrong Help Center article or section Locale or brand mismatch, metric mismatch, or fragmented store. → embedding-vs-semantic.md, patterns/pattern_vectorstore_fragmentation.md
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Draft vs published desync after content edits Bootstrap race or stale index hash. → bootstrap-ordering.md, predeploy-collapse.md
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Flow Builder branch loops or unexpected fallback Version skew across triggers or missing warm up fence. → deployment-deadlock.md, ops/debug_playbook.md
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Webhook returns 200 yet thread state drifts Tool JSON schema too loose, arguments allow free text, no cite then explain. → data-contracts.md, prompt-injection.md
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High similarity with wrong meaning from Guide search Analyzer and casing differ from embeddings, or chunking misaligned with anchors. → retrieval-playbook.md, chunking-checklist.md
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Long threads become inconsistent after 20 to 40 turns Entropy growth with chain length and memory collisions. → context-drift.md, entropy-collapse.md, Multi-Agent_Problems.md
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Confident bluffing or jailbreak Missing fences and citation first rules. → bluffing.md, retrieval-traceability.md
CX surface guardrails
Help Center and brands Enforce locale and brand parity between search and embeddings. Use citation first on every answer that references articles. See retrieval-traceability.md.
Flow Builder Keep policy text in a system context that never mixes with user turns. Lock tool schemas and echo them each step. See data-contracts.md.
Triggers and webhooks
Add a warm up fence for first calls after deploy. Log ΔS, λ_state, INDEX_HASH, snippet_id, dedupe_key. See bootstrap-ordering.md.
Search parity If ΔS stays high after reranking and k sweeps, rebuild chunks and verify with a small gold set. See embedding-vs-semantic.md, chunking-checklist.md.
Live ops Add probes and backoff guards. For incident handling see ops/live_monitoring_rag.md, ops/debug_playbook.md.
Minimal webhook recipe
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Warm up fence Validate
VECTOR_READY,INDEX_HASH, and secrets. If not ready, short circuit and retry with capped backoff. See bootstrap-ordering.md. -
Retrieval step Call the retriever with explicit metric and consistent analyzer. Return
snippet_id,section_id,source_url,offsets,tokens. -
ΔS probe Compute ΔS(question, retrieved). If ΔS ≥ 0.60 set
needs_fix=true. -
LLM answer step LLM reads TXT OS and WFGY schema. Enforce cite then explain across the retrieved set.
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Trace sink Store
question,ΔS,λ_state,INDEX_HASH,snippet_id,dedupe_key.
Copy paste prompt for your Zendesk webhook
You have TXT OS and the WFGY Problem Map loaded.
My Zendesk context:
- flow: {flow_name}
- channel: web | email | messaging
- retrieved: {k} snippets with fields {snippet_id, section_id, source_url, offsets, tokens}
User question: "{user_question}"
Do:
1) Enforce cite-then-explain. If citations are missing or cross-section, fail fast and return the minimal fix.
2) If ΔS(question, retrieved) ≥ 0.60, propose the smallest structural repair
referencing: retrieval-playbook, retrieval-traceability, data-contracts, rerankers.
3) Return JSON:
{ "answer": "...", "citations": [...], "λ_state": "→|←|<>|×", "ΔS": 0.xx, "next_fix": "..." }
Keep it short and auditable.
Test checklist before launch
- Three paraphrases hit coverage ≥ 0.70 on the same target section.
- ΔS(question, retrieved) ≤ 0.45 for each.
- λ convergent across two seeds.
- First call after deploy passes the warm up fence.
- Live probes alert when ΔS ≥ 0.60 or λ flips.
🔗 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
| 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 → |
👑 Early Stargazers: See the Hall of Fame — Engineers, hackers, and open source builders who supported WFGY from day one.
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