feat(context): tambah context::tokens dengan tiktoken-rs

Ganti tiga heuristik char-count (/3 di shortsend, /4 di loop turn, /4
di status bar) yang saling tidak konsisten dengan satu BPE tokenizer
nyata. tiktoken-rs membundel vocab lewat include_str! saat build, jadi
tidak ada akses jaringan saat runtime.

src/app/runtime/context/mod.rs

@@ -0,0 +1,13 @@
+//! Context management: token counting, cross-call tool-result dedup,
+//! per-result compression, budget-based shaping, and shared
+//! context-window resolution — replaces `runtime::shortsend`.
+//!
+//! No facade function here: `dedup`, `shaping`, and `tokens` are called
+//! directly from each call site (the per-turn auto-compaction loop in
+//! `actions::run_agent_turn`, and `Action::Compact`), matching this
+//! codebase's "no DI, call modules directly" convention. An orchestration
+//! layer would only serve one of the two callers generically — the
+//! auto-loop already needs per-stage control to decide when to emit
+//! `TurnEvent::Compacted`.
+
+pub mod tokens;

src/app/runtime/context/tokens.rs

@@ -0,0 +1,69 @@
+//! Unified token-count estimation for context-window budgeting.
+//!
+//! Flow: text -> `tiktoken_rs::o200k_base_singleton()` (BPE vocab embedded
+//! in the binary via `include_str!`, no network access) -> `encode_ordinary`
+//! -> token count.
+//!
+//! Why: replaces three independent char-count heuristics that disagreed
+//! with each other (`/3` in the old `shortsend.rs`, `/4` in the turn
+//! loop, `/4` again in the status bar) with one real BPE tokenizer.
+//! `o200k_base` is an approximation for non-OpenAI providers but is far
+//! closer than a flat byte-per-token guess; it's only used for the
+//! 85%/95% budget thresholds, not for billing-accurate counts.
+
+use crate::dto::chat::message::ChatMessage;
+
+/// Count tokens in a single string under `o200k_base`.
+///
+/// Return: the BPE token count for `text`. `encode_ordinary` (not
+/// `encode`/`encode_with_special_tokens`) is used deliberately — message
+/// content that happens to contain a special-token-shaped substring
+/// (e.g. literal text `<|endoftext|>` pasted by a user) must be counted
+/// as ordinary text, not interpreted as a control token.
+pub fn count_tokens(text: &str) -> usize {
+    tiktoken_rs::o200k_base_singleton().encode_ordinary(text).len()
+}
+
+/// Count tokens in a `ChatMessage`'s text content.
+///
+/// Return: 0 for a message with no `content` (e.g. an assistant message
+/// that only carries `tool_calls`).
+pub fn count_message_tokens(msg: &ChatMessage) -> usize {
+    msg.content.as_deref().map_or(0, count_tokens)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::dto::chat::message::ChatMessage;
+
+    #[test]
+    fn empty_string_has_zero_tokens() {
+        assert_eq!(count_tokens(""), 0);
+    }
+
+    #[test]
+    fn known_short_phrase_has_expected_token_count() {
+        // Verified empirically against tiktoken-rs 0.12's o200k_base:
+        // "hello world" -> [24912, 2375], i.e. 2 tokens.
+        assert_eq!(count_tokens("hello world"), 2);
+    }
+
+    #[test]
+    fn known_code_snippet_has_expected_token_count() {
+        // Verified empirically: 9 tokens under o200k_base.
+        assert_eq!(count_tokens("fn main() { println!(\"hi\"); }"), 9);
+    }
+
+    #[test]
+    fn message_with_no_content_counts_zero() {
+        let msg = ChatMessage::assistant(None);
+        assert_eq!(count_message_tokens(&msg), 0);
+    }
+
+    #[test]
+    fn message_token_count_matches_count_tokens_on_its_content() {
+        let msg = ChatMessage::user("hello world");
+        assert_eq!(count_message_tokens(&msg), count_tokens("hello world"));
+    }
+}

src/app/runtime/mod.rs

@@ -2,5 +2,6 @@
 //! and the LLM streaming pipeline.
 pub mod actions;
 pub mod commands;
+pub mod context;
 pub mod shortsend;
 pub mod stream;