Rewrite 548 skill descriptions to the activation rubric

Each rewritten description now states both what the skill does (concrete
capability, named tools/artifacts) and an explicit when-to-use trigger,
improving agent discovery/activation. Grounded in each skill's own body;
changes confined to the `description` field only (bodies and all other
frontmatter untouched). Produced by a gated audit->rewrite->recheck loop
(548 -> 0 flagged) with a sampled anti-invention check (0 ungrounded).

Schema: 817/817 pass. Framework-ID gate: 0 defects.

skills/implementing-llm-guardrails-for-security/SKILL.md

@@ -1,15 +1,11 @@
 ---
 name: implementing-llm-guardrails-for-security
-description: 'Implements input and output validation guardrails for LLM-powered applications
-  to prevent prompt injection, data leakage, toxic content generation, and hallucinated
-  outputs. Builds a security validation pipeline using NVIDIA NeMo Guardrails Colang
-  definitions, custom Python validators for PII detection and content policy enforcement,
-  and the Guardrails AI framework for structured output validation. The guardrails
-  system intercepts both user inputs (blocking injection attempts, stripping PII,
-  enforcing topic boundaries) and model outputs (detecting hallucinations, filtering
-  toxic content, validating JSON schema compliance). Activates for requests involving
-  LLM output validation, AI content filtering, guardrail implementation, or LLM safety
-  enforcement.
+description: 'Implements input/output validation guardrails for LLM applications using
+  NVIDIA NeMo Guardrails (Colang), custom Python validators for PII detection, and
+  the Guardrails AI framework, intercepting user inputs (prompt injection, PII,
+  off-topic queries) and model outputs (hallucinations, toxic content, schema
+  compliance). Use when adding safety controls to an LLM app/chatbot/RAG pipeline
+  or validating outputs conform to expected schemas.
 
   '
 domain: cybersecurity