fix(ai-red-teaming): correct stale catalog counts (goals/transforms/scorers)

capabilities/ai-red-teaming/agents/ai-red-teaming-agent.md

@@ -5,7 +5,7 @@ description: >
   Unified AI Red Teaming agent for probing security and safety vulnerabilities in LLMs,
   agentic systems, MCP servers, multi-agent architectures, ML classifiers, and custom AI endpoints.
   Orchestrates 70+ attack strategies covering traditional ML and generative AI, 590+ transforms,
-  140+ scorers, and 260 bundled harm goals across OWASP LLM Top 10,
+  140+ scorers, and 279 bundled harm goals across OWASP LLM Top 10,
   OWASP ASI01-ASI10, and MITRE ATLAS frameworks.
 ---
 
@@ -379,7 +379,7 @@ Three tiers with sub-categories:
 | agentic_cascading_failure | Agentic Cascading Failure | 10 | ASI08 |
 | agentic_trust_exploitation | Agentic Trust Exploitation | 10 | ASI09 |
 
-**Total: 25 sub-categories, 260 bundled goals across 3 tiers.**
+**Total: 25 sub-categories, 279 bundled goals across 3 tiers.**
 
 ## Agentic Red Teaming
 

capabilities/ai-red-teaming/capability.yaml

@@ -11,7 +11,7 @@ description: >
   and NIST AI RMF compliance frameworks. Also probes traditional black-box ML
   classifiers: model extraction (model stealing), membership inference (training-data
   leakage), and model evasion (adversarial examples) across tabular, image, and text.
-  590+ transforms, 140+ scorers, and 260 bundled harm goals across 25
+  590+ transforms, 140+ scorers, and 279 bundled harm goals across 25
   sub-categories in safety, security, and agentic tiers.
 
 agents:

capabilities/ai-red-teaming/skills/compliance-mapping/SKILL.md

@@ -96,7 +96,7 @@ Maps AIRT attacks, transforms, and scorers to major AI security compliance frame
 - MCP security — 12 transforms, 7 scorers
 - Multi-agent security — 10 transforms, 6 scorers
 - Exfiltration — 8 transforms, 5 scorers
-- Content policy — 260 bundled goals across 25 sub-categories
+- Content policy — 279 bundled goals across 25 sub-categories
 - System prompt extraction — 6 transforms
 - RAG poisoning — 7 transforms
 

capabilities/ai-red-teaming/skills/scorer-reference/SKILL.md

@@ -1,12 +1,12 @@
 ---
 name: scorer-reference
-description: Complete catalog of all 84 scorers with exact names, categories, and when to use each
+description: Catalog of AIRT scorers - 146 user-selectable (+ agentic *_detected scorers auto-wired per OWASP-ASI category); documents the core set with exact names, categories, and when to use each
 allowed-tools: generate_attack generate_agentic_attack
 ---
 
 # Scorer Reference
 
-All 84 scorers available in the AIRT SDK. Use these EXACT names in the `scorers` parameter.
+The AIRT SDK exposes **146 user-selectable scorers** (plus agentic `*_detected` scorers that the agentic suite auto-wires per OWASP-ASI category). The tables below document the core set - use these EXACT names in the `scorers` parameter, or ask `"Show me the available scorers"` for the full list.
 
 ## Default Scorer
 

capabilities/ai-red-teaming/skills/transform-reference/SKILL.md

@@ -1,12 +1,12 @@
 ---
 name: transform-reference
-description: Complete catalog of all 183 transforms with exact names, parameters, categories, and LLM requirements
+description: Catalog of AIRT transforms - 429 text transforms (596 incl. multimodal/variants); documents the core set with exact names, parameters, categories, and LLM requirements
 allowed-tools: generate_attack generate_agentic_attack
 ---
 
 # Transform Reference
 
-All 183 transforms available in the AIRT SDK. Use these EXACT names in the `transforms` parameter.
+The AIRT SDK resolves **429 text transforms** (596 incl. multimodal + parameterized variants). The tables below document the core set - use these EXACT names in the `transforms` parameter, or ask `"Show me all available transforms"` for the full list.
 
 ## Encoding (17 transforms)
 

capabilities/ai-red-teaming/tools/attacks.py

@@ -224,7 +224,7 @@ def generate_category_attack(
     """Generate a multi-goal attack across bundled harm categories.
 
     Sweeps attacks across entire goal sub-categories from the bundled
-    dataset (260 goals across 25 sub-categories in safety/security/agentic
+    dataset (279 goals across 25 sub-categories in safety/security/agentic
     tiers). Goal text is embedded in the generated script — never
     returned to the agent.