feat: add Claude Code orchestration setup with MCP and subagents
Add comprehensive Claude Code configuration for Rust/Go projects, including: - CLAUDE.md with delegation heuristics and guardrails - Subagents: qwen3-worker (LM Studio), code-reviewer, task-planner - Skills for delegation rules and Rust/Go conventions - Hooks: post-write-lint, pre-bash-guard, subagent-stop-log - MCP server (stdio) to interface with LM Studio - README and technical report documenting the architecture
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.claude/mcp/qwen3-mcp/agent_lm.py
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182
.claude/mcp/qwen3-mcp/agent_lm.py
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#!/usr/bin/env -S .claude/venv/bin/python3
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"""
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Agent loop local (~120 lignes) pour interagir avec LM Studio via l'API OpenAI-compatible.
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Usage : python3 .claude/mcp/qwen3-mcp/agent_lm.py --task "..." --files file1.py file2.go
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"""
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import argparse
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import json
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import os
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import sys
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from pathlib import Path
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import requests
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LMSTUDIO_URL = "http://localhost:1248/v1/chat/completions"
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LMSTUDIO_MODELS_URL = "http://localhost:1248/v1/models"
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DEFAULT_MODEL = "qwen/qwen3-coder-next"
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SYSTEM_PROMPT = """Tu es un assistant de codage spécialisé. Tu effectues des tâches atomiques sur des fichiers source.
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Règles :
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- Ne modifie que ce qui est demandé
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- Ne change pas les signatures publiques (traits Rust, interfaces Go exportées)
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- Retourne uniquement le code, sans explication ni markdown
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- Si tu ne peux pas accomplir la tâche, réponds avec: ERROR: <raison>
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"""
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def list_models() -> list[str]:
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"""Retourne la liste des modèles disponibles dans LM Studio."""
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try:
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resp = requests.get(LMSTUDIO_MODELS_URL, timeout=10)
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resp.raise_for_status()
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return [m["id"] for m in resp.json().get("data", [])]
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except requests.RequestException as e:
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print(f"Impossible de contacter LM Studio : {e}", file=sys.stderr)
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return []
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def read_files(paths: list[str]) -> str:
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"""Lit les fichiers et les formate pour le prompt."""
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context = ""
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for path in paths:
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try:
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content = Path(path).read_text(encoding="utf-8")
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context += f"=== {path} ===\n{content}\n\n"
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except OSError as e:
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context += f"=== {path} === ERREUR: {e}\n\n"
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return context
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def call_lmstudio(task: str, file_context: str, model: str) -> str:
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"""Envoie la tâche à LM Studio et retourne la réponse."""
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user_message = f"TÂCHE: {task}\n\nFICHIERS:\n{file_context}" if file_context else f"TÂCHE: {task}"
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payload = {
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"model": model,
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"messages": [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": user_message},
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],
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"temperature": 0.2,
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"max_tokens": 4096,
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}
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try:
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resp = requests.post(LMSTUDIO_URL, json=payload, timeout=120)
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resp.raise_for_status()
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return resp.json()["choices"][0]["message"]["content"]
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except requests.Timeout:
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return "ERROR: LM Studio timeout (>120s)"
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except requests.RequestException as e:
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return f"ERROR: {e}"
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except (KeyError, IndexError) as e:
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return f"ERROR: réponse inattendue de LM Studio : {e}"
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def write_file(path: str, content: str) -> bool:
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"""Écrit le contenu dans un fichier, crée les répertoires si nécessaire."""
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try:
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Path(path).parent.mkdir(parents=True, exist_ok=True)
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Path(path).write_text(content, encoding="utf-8")
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return True
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except OSError as e:
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print(f"Erreur écriture {path}: {e}", file=sys.stderr)
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return False
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def run_lint(file_path: str) -> tuple[bool, str]:
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"""Lance le linter approprié selon l'extension."""
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import subprocess
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if file_path.endswith(".rs"):
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result = subprocess.run(
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["cargo", "clippy", "--quiet"],
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capture_output=True, text=True, timeout=60
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)
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elif file_path.endswith(".go"):
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result = subprocess.run(
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["golangci-lint", "run", file_path],
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capture_output=True, text=True, timeout=60
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)
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else:
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return True, "no linter for this file type"
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passed = result.returncode == 0
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output = (result.stdout + result.stderr).strip()
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return passed, output
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def agent_loop(task: str, input_files: list[str], output_file: str | None, model: str, max_retries: int = 2) -> dict:
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"""Boucle principale : génère, écrit, lint, corrige (max_retries fois)."""
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file_context = read_files(input_files) if input_files else ""
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result = {"status": "failure", "files_modified": [], "summary": "", "lint": "skipped"}
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for attempt in range(max_retries + 1):
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response = call_lmstudio(task, file_context, model)
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if response.startswith("ERROR:"):
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result["summary"] = response
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break
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target = output_file or (input_files[0] if input_files else None)
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if not target:
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result["status"] = "success"
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result["summary"] = response
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result["lint"] = "skipped (no output file)"
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break
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if write_file(target, response):
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result["files_modified"] = [target]
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lint_ok, lint_output = run_lint(target)
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result["lint"] = "passed" if lint_ok else f"failed: {lint_output[:500]}"
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if lint_ok:
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result["status"] = "success"
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result["summary"] = f"Attempt {attempt + 1}: task completed successfully"
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break
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elif attempt < max_retries:
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task = f"{task}\n\nCORRECTION REQUISE (tentative {attempt + 1}):\n{lint_output}"
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file_context = read_files([target])
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else:
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result["status"] = "partial"
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result["summary"] = f"Lint failed after {max_retries + 1} attempts"
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return result
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def main():
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parser = argparse.ArgumentParser(description="Agent loop local pour LM Studio")
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parser.add_argument("--task", required=True, help="Description de la tâche")
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parser.add_argument("--files", nargs="*", default=[], help="Fichiers source à lire")
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parser.add_argument("--output", help="Fichier de sortie (défaut: premier fichier input)")
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parser.add_argument("--model", default=DEFAULT_MODEL, help="Modèle LM Studio")
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parser.add_argument("--list-models", action="store_true", help="Liste les modèles disponibles")
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parser.add_argument("--json", action="store_true", dest="json_output", help="Sortie JSON")
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args = parser.parse_args()
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if args.list_models:
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models = list_models()
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if models:
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print("Modèles disponibles :")
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for m in models:
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print(f" - {m}")
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else:
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print("Aucun modèle trouvé ou LM Studio inaccessible.")
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return
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result = agent_loop(args.task, args.files, args.output, args.model)
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if args.json_output:
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print(json.dumps(result, ensure_ascii=False, indent=2))
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else:
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print(f"STATUS: {result['status']}")
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print(f"FILES_MODIFIED: {', '.join(result['files_modified']) or 'none'}")
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print(f"SUMMARY: {result['summary']}")
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print(f"LINT: {result['lint']}")
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sys.exit(0 if result["status"] == "success" else 1)
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if __name__ == "__main__":
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main()
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