feat(phase9): ContentTags schema, system prompt, and GBNF grammar

ContentTags serde-serialisable. CONTENT_TAGS_SYSTEM is the system
message rendered at extraction time; INTENT_CLOSED_SET is the single
source of truth for the enum values the grammar restricts. Grammar is
strict: lowercase hyphen-joined topic 3+ chars (max enforced by
max_tokens at call site), intent from the closed set, JSON-only
output. Recursive topic-rest matches the existing GBNF style in this
file.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

crates/llm/src/prompts.rs

@@ -4,6 +4,39 @@ between 3 and 7 concrete, physical micro-steps. Each step must be a short \
 imperative sentence, actionable today, with no commentary. Output ONLY a \
 JSON array of strings.";
 
+// Phase 9 content-tag extraction. The model emits a {topic, intent}
+// JSON pair under a strict GBNF (see grammars::CONTENT_TAGS_GRAMMAR).
+// CONTENT_TAGS_SYSTEM is the system message; the user message wraps
+// the transcript text.
+pub const CONTENT_TAGS_SYSTEM: &str = "\
+You tag a transcript with ONE topic and ONE intent. \
+TOPIC is a 1 to 3 token lowercase hyphen-joined noun phrase naming the \
+dominant subject. Examples: interview-prep, grant-application, \
+daily-standup. \
+INTENT is exactly one of: planning, reflection, venting, capture, \
+decision, question. \
+Return JSON only, with this exact shape: \
+{\"topic\":\"...\",\"intent\":\"...\"}";
+
+#[derive(Debug, Clone, serde::Serialize, serde::Deserialize)]
+pub struct ContentTags {
+    pub topic: String,
+    pub intent: String,
+}
+
+pub const INTENT_CLOSED_SET: &[&str] = &[
+    "planning",
+    "reflection",
+    "venting",
+    "capture",
+    "decision",
+    "question",
+];
+
+pub fn is_valid_intent(s: &str) -> bool {
+    INTENT_CLOSED_SET.contains(&s)
+}
+
 pub const EXTRACT_TASKS_SYSTEM: &str = "\
 You are a task-extraction assistant. Given a transcript of spoken notes, \
 output a JSON array of action items the speaker committed to. Each item must \