docs: update README and SHOWCASE for kOREInference + core/outlier analysis

README.md

@@ -79,6 +79,11 @@ Agent: Let me check what pattern the existing community roles follow.
 
 **With Dervish:** one MCP call returns a ~60-token grammar known to match 15/15 existing roles. The agent follows it reliably.
 
+**Core+outlier mode:** When generating a new role, the agent can call with
+`min_coverage=0.8` to learn the mainstream pattern while seeing which roles
+deviate and why — useful when the user's case resembles an outlier
+(e.g., a PHP app like phpmyadmin that needs raw `lineinfile`).
+
 ## Quick Start
 
 ```bash
@@ -125,6 +130,8 @@ Dervish has been tested against public datasets from Ansible Galaxy, Helm, and G
 
 The sweet spot: **multiple implementations of the same abstract task** with a shared but undocumented pattern. Not everything works — Dockerfiles, pre-commit configs, and schema-enforced formats are too rigid or too diverse to yield a convention.
 
+> **kOREInference note:** Algorithm 4 (iDRegEx with MDL, arXiv 1004.2372) is included for paper-faithful correctness. On real tool-sequence data, its rwr₀ repair step returns ∅ because the k-OA is rarely SORE (interconnected symbols). The ensemble falls back to CRX or iDRegEx automatically.
+
 ## Algorithm Selection Guide
 
 | When | Use | Why |
@@ -139,8 +146,9 @@ The sweet spot: **multiple implementations of the same abstract task** with a sh
 
 | Data property | Winner | Why |
 |---------------|--------|-----|
-| Diverse patterns, full vocabulary needed | CRX | Captures all symbols. iDRegEx/kOREInference return ∅. |
+| Diverse patterns, full vocabulary needed | CRX | Captures all symbols. iDRegEx returns ∅. |
 | Clean sequences with clear core | iDRegEx | Extracts minimal common subsequence. CRX buries it in optional noise. |
+| Interconnected (non-SORE) data | CRX | kOREInference (rwr₀) returns ∅ when k-OA is not SORE. CRX handles it. |
 | Single sequence | iDRegEx (+ RWR₀) | RWR₀ repair produces a grammatical regex from one example. |
 | 2–3 sequences | iDRegEx | CRX overfits. iDRegEx handles noise better. |
 | Many sequences, tight pattern | CRX | Learns precise concatenation with optional suffixes. |

SHOWCASE.md

@@ -34,6 +34,25 @@ All 15/15 match. **~29× compression** (7200+ modules → ~250 chars).
 exact structure: fail-check first, then vars, then packages, then config/svc.
 No guessing.
 
+### Bonus: core+outlier analysis
+
+Set `min_coverage=0.8` to find the tight grammar for the majority while
+flagging outlier roles with unusual module usage:
+
+```
+Core CRX (80% coverage, 3 outliers):
+  fail?.(include_vars+set_fact+package+file+template+service+...)+
+
+Outlier sequences:
+  1. phpmyadmin: include_vars → set_fact → include → include → lineinfile
+  2. composer:   fail → set_fact → stat → uri → get_url → command
+  3. pip:        package → file → pip
+```
+
+phpmyadmin uses raw `lineinfile` instead of templates; composer needs
+a `stat` check + `uri` download; pip is purely `pip` — all three deviate
+from the mainstream install → configure → enable pattern.
+
 ## 2. Helm chart (kube-prometheus-stack, 6 configs)
 
 6 different `values.yaml` files rendered through the same chart:
@@ -77,10 +96,15 @@ with a shared but undocumented pattern.
 ## Usage
 
 ```python
-from bex.mcp_server import infer_best_grammar
+from bex import infer_ensemble
 
-output = infer_best_grammar(
-    sequences=role_sequences,
-    prefer="crx",
-)
+# Pick best across all 3 algorithms (CRX + iDRegEx + kOREInference)
+result = infer_ensemble(role_sequences)
+print(f"Best: {result['best']['algorithm']}")
+print(f"Grammar: {result['best']['grammar']}")
+
+# Or: find the tight core + flag outliers
+result = infer_ensemble(role_sequences, min_coverage=0.8)
+print(f"Core: {result['core']['grammar']}")
+print(f"Outliers: {result['core']['outliers']}")
 ```