docs: clarify explainability is system-level, not foundation-model internal (#1033)

Adds a consistent scope note to README and docs (concepts, FAQ, index)
stating Semantica does not expose or reconstruct an LLM's internal
reasoning/chain-of-thought. It explains and audits the AI system
around the model: context, provenance, policies, decisions, and
execution history.

docs/concepts.md

@@ -16,6 +16,9 @@ At its core, Semantica adds a **context and accountability layer** on top of you
 - **Accountability Layer** — Provenance tracking, decision intelligence, conflict detection, and W3C PROV-O compliance make every claim in your AI stack auditable and explainable.
 - **Extension Layer** — `PluginRegistry` and `MethodRegistry` let you replace or augment any component: ingestors, extractors, reasoning engines, backends: without changing framework code.
 
+<Warning>
+  **This is system-level explainability, not foundation-model explainability.** Semantica does not expose, reconstruct, or explain what happens *inside* the LLM/foundation model — its internal reasoning or chain-of-thought stays opaque, as it does for any external system. What Semantica explains is *outside* the model: the context and data fed in, the decision produced, its provenance, the relevant relationships, the policies applied, and the full execution trail. In short, Semantica explains and audits *what the AI system did*, not the foundation model's private internal reasoning.
+</Warning>
 
 ## Knowledge Graphs
 

docs/faq.md

@@ -52,6 +52,16 @@ Semantica works alongside these frameworks, not against them.
 
 </Accordion>
 
+<Accordion title="Does Semantica explain an LLM's internal reasoning or chain-of-thought?" icon="triangle-exclamation">
+
+No. This is **system-level explainability, not foundation-model explainability**. Semantica does not expose, reconstruct, or explain what happens *inside* the LLM/foundation model — its internal reasoning or chain-of-thought stays opaque, as it does for any external system.
+
+What Semantica explains is *outside* the model: what context and data were used, what decision was produced, the provenance behind it, the relevant relationships, the policies applied, and the resulting decision trail.
+
+In short: Semantica explains and audits *what the AI system did* — not the foundation model's private internal reasoning.
+
+</Accordion>
+
 <Accordion title="Is Semantica free?" icon="tag">
 
 Yes: MIT licensed, no vendor lock-in, no paywalled features. Some capabilities require third-party API keys (e.g., OpenAI embeddings, Groq inference), but Semantica itself is always free and open source.

docs/index.md

@@ -192,7 +192,11 @@ decision_id = context.record_decision(
 
 ## Built for Where Mistakes Have Consequences
 
-Semantica was designed for domains where every decision must be explainable and every fact must be traceable:
+Semantica was designed for domains where every decision must be explainable and every fact must be traceable.
+
+<Warning>
+  **This is system-level explainability, not foundation-model explainability.** Semantica does not expose, reconstruct, or explain what happens *inside* the LLM/foundation model — its internal reasoning or chain-of-thought stays opaque, as it does for any external system. What Semantica explains is *outside* the model: the context and data fed in, the decision produced, its provenance, the relevant relationships, the policies applied, and the full execution trail. See [Core Concepts](concepts) for the full scope note.
+</Warning>
 
 **Healthcare & Life Sciences**
 - Clinical decision support with full audit trails