Add cross-project pattern registry for retrieval-augmented generalization

- Create patterns/ directory with README, manifest, and 10 initial patterns
  covering Ollama JSON fallback, API escaping, deprecation, PTY auth,
  queue-poll, LLM-as-parser, credential rotation, reverse proxy binding,
  human approval gates, and transient retry.
- Wire pattern loading into architecture/pipeline.js based on task tags.
- Update architecture/orchestrator.js to load patterns and surface them in
  the system prompt.
- Update MEMORY.md, ARCHITECTURE.md, and CONTEXT.md to document the registry
  and record the decision.

patterns/ollama-structured-output-fallback.md

@@ -0,0 +1,35 @@
+# Pattern: Ollama Structured Output Fallback
+
+## Symptom
+A workflow calls a local Ollama model (e.g., `gemma3:4b`, small quantized models) with a structured-output or JSON schema request, but the returned text is not valid JSON, misses required fields, wraps the JSON in prose, or otherwise fails schema validation.
+
+## Affected Projects
+- Cyber Tips Newsletter pipeline
+- Proxmox VE snapshot summarizer
+- AI video generation pipeline (ComfyUI + WAN 2.1 payloads)
+- Forex trading analysis workflow
+
+## Root Cause
+Small local instruction-tuned models have weaker schema adherence than frontier APIs. They may produce JSON-like text that does not strictly conform to the requested schema, especially under complex prompts or when asked to combine generation with strict formatting.
+
+## Standard Fix
+Add a downstream JavaScript Code node (or equivalent parser) in n8n that:
+1. Attempts a strict `JSON.parse()` first.
+2. On failure, applies regex-based JSON extraction to pull the first `{...}` or `[...]` block from the text.
+3. Optionally sanitizes common issues (trailing commas, unescaped newlines, code fences).
+4. Falls back to a safe default or error flag if extraction still fails.
+
+This is a deliberate workaround, not a substitute for fixing the model. Document it as such wherever applied.
+
+## When to Apply
+- Any new n8n workflow that uses a local Ollama model for structured extraction, classification, or JSON generation.
+- Any integration where the downstream node requires strict JSON and the LLM is under ~8B parameters or known to drift.
+
+## Verification
+- Test the fallback with intentionally malformed LLM output.
+- Confirm downstream nodes receive valid parsed JSON.
+- Log fallback events so model quality can be monitored separately.
+
+## Related Patterns
+- `json-escaping-downstream-api`
+- `llm-as-parser-fallback`