chore: import upstream snapshot with attribution

2026-07-13 12:39:59 +08:00
commit 60e0ffc959
1282 changed files with 294901 additions and 0 deletions
@@ -0,0 +1,37 @@
+# Code Mode
+
+CodeMode collapses an entire tool catalog into two meta-tools: `search` (keyword-based discovery) and `execute` (run Python scripts that chain tool calls in a sandbox). Instead of burning context tokens on every intermediate result, the LLM writes a script that runs server-side and returns only the final answer.
+
+## Run
+
+```bash
+uv run python server.py   # in one terminal
+uv run python client.py   # in another
+```
+
+## Example Output
+
+```
+══════════════════ CodeMode Transform ══════════════════
+
+┌────────────── list_tools() ──────────────┐
+│ Tool     Description                     │
+│ search   Search for available tools ...  │
+│ execute  Chain `await call_tool(...)` ... │
+└── 8 backend tools collapsed into 2 ──────┘
+
+┌──── search(query="math arithmetic") ─────┐
+│ #   Tool      Description                │
+│ 1   add       Add two numbers together.  │
+│ 2   multiply  Multiply two numbers.      │
+│ 3   fibonacci Generate the first n ...   │
+└── 3 results ─────────────────────────────┘
+
+┌────────────── execute ───────────────────┐
+│ a = await call_tool("add", {"a": 3 ...  │
+│ b = await call_tool("multiply", ...     │
+│ return b                                 │
+└── result: 14.0 ──────────────────────────┘
+```
+
+The key insight: with standard MCP, each `call_tool` is a round-trip through the LLM. With CodeMode, the LLM writes one script and all the tool calls happen server-side. Intermediate data never touches the context window.