feat(hermes): implement intelligence pipeline — 4 chunks, 684 tests passing

Hermes Intelligence Pipeline closes breakpoints in ZCLAW's existing
intelligence components with 4 self-contained modules:

Chunk 1 — Self-improvement Loop:
- ExperienceStore (zclaw-growth): FTS5+TF-IDF wrapper with scope prefix
- ExperienceExtractor (desktop/intelligence): template-based extraction
  from successful proposals with implicit keyword detection

Chunk 2 — User Modeling:
- UserProfileStore (zclaw-memory): SQLite-backed structured profiles
  with industry/role/expertise/comm_style/recent_topics/pain_points
- UserProfiler (desktop/intelligence): fact classification by category
  (Preference/Knowledge/Behavior) with profile summary formatting

Chunk 3 — NL Cron Chinese Time Parser:
- NlScheduleParser (zclaw-runtime): 6 pattern matchers for Chinese time
  expressions (每天/每周/工作日/间隔/每月/一次性) producing cron expressions
- Period-aware hour adjustment (下午3点→15, 晚上8点→20)
- Schedule intent detection + task description extraction

Chunk 4 — Trajectory Compression:
- TrajectoryStore (zclaw-memory): trajectory_events + compressed_trajectories
- TrajectoryRecorderMiddleware (zclaw-runtime/middleware): priority 650,
  async non-blocking event recording via tokio::spawn
- TrajectoryCompressor (desktop/intelligence): dedup, request classification,
  satisfaction detection, execution chain JSON

Schema migrations: v2→v3 (user_profiles), v3→v4 (trajectory tables)

crates/zclaw-growth/src/lib.rs

@@ -64,6 +64,7 @@ pub mod viking_adapter;
 pub mod storage;
 pub mod retrieval;
 pub mod summarizer;
+pub mod experience_store;
 
 // Re-export main types for convenience
 pub use types::{
@@ -85,6 +86,7 @@ pub use injector::{InjectionFormat, PromptInjector};
 pub use tracker::{AgentMetadata, GrowthTracker, LearningEvent};
 pub use viking_adapter::{FindOptions, VikingAdapter, VikingLevel, VikingStorage};
 pub use storage::SqliteStorage;
+pub use experience_store::{Experience, ExperienceStore};
 pub use retrieval::{EmbeddingClient, MemoryCache, QueryAnalyzer, SemanticScorer};
 pub use summarizer::SummaryLlmDriver;