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
This commit is contained in:
2026-03-26 12:23:54 +01:00
commit c776733402
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#!/usr/bin/env -S .claude/venv/bin/python3
"""
Agent loop local (~120 lignes) pour interagir avec LM Studio via l'API OpenAI-compatible.
Usage : python3 .claude/mcp/qwen3-mcp/agent_lm.py --task "..." --files file1.py file2.go
"""
import argparse
import json
import os
import sys
from pathlib import Path
import requests
LMSTUDIO_URL = "http://localhost:1248/v1/chat/completions"
LMSTUDIO_MODELS_URL = "http://localhost:1248/v1/models"
DEFAULT_MODEL = "qwen/qwen3-coder-next"
SYSTEM_PROMPT = """Tu es un assistant de codage spécialisé. Tu effectues des tâches atomiques sur des fichiers source.
Règles :
- Ne modifie que ce qui est demandé
- Ne change pas les signatures publiques (traits Rust, interfaces Go exportées)
- Retourne uniquement le code, sans explication ni markdown
- Si tu ne peux pas accomplir la tâche, réponds avec: ERROR: <raison>
"""
def list_models() -> list[str]:
"""Retourne la liste des modèles disponibles dans LM Studio."""
try:
resp = requests.get(LMSTUDIO_MODELS_URL, timeout=10)
resp.raise_for_status()
return [m["id"] for m in resp.json().get("data", [])]
except requests.RequestException as e:
print(f"Impossible de contacter LM Studio : {e}", file=sys.stderr)
return []
def read_files(paths: list[str]) -> str:
"""Lit les fichiers et les formate pour le prompt."""
context = ""
for path in paths:
try:
content = Path(path).read_text(encoding="utf-8")
context += f"=== {path} ===\n{content}\n\n"
except OSError as e:
context += f"=== {path} === ERREUR: {e}\n\n"
return context
def call_lmstudio(task: str, file_context: str, model: str) -> str:
"""Envoie la tâche à LM Studio et retourne la réponse."""
user_message = f"TÂCHE: {task}\n\nFICHIERS:\n{file_context}" if file_context else f"TÂCHE: {task}"
payload = {
"model": model,
"messages": [
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": user_message},
],
"temperature": 0.2,
"max_tokens": 4096,
}
try:
resp = requests.post(LMSTUDIO_URL, json=payload, timeout=120)
resp.raise_for_status()
return resp.json()["choices"][0]["message"]["content"]
except requests.Timeout:
return "ERROR: LM Studio timeout (>120s)"
except requests.RequestException as e:
return f"ERROR: {e}"
except (KeyError, IndexError) as e:
return f"ERROR: réponse inattendue de LM Studio : {e}"
def write_file(path: str, content: str) -> bool:
"""Écrit le contenu dans un fichier, crée les répertoires si nécessaire."""
try:
Path(path).parent.mkdir(parents=True, exist_ok=True)
Path(path).write_text(content, encoding="utf-8")
return True
except OSError as e:
print(f"Erreur écriture {path}: {e}", file=sys.stderr)
return False
def run_lint(file_path: str) -> tuple[bool, str]:
"""Lance le linter approprié selon l'extension."""
import subprocess
if file_path.endswith(".rs"):
result = subprocess.run(
["cargo", "clippy", "--quiet"],
capture_output=True, text=True, timeout=60
)
elif file_path.endswith(".go"):
result = subprocess.run(
["golangci-lint", "run", file_path],
capture_output=True, text=True, timeout=60
)
else:
return True, "no linter for this file type"
passed = result.returncode == 0
output = (result.stdout + result.stderr).strip()
return passed, output
def agent_loop(task: str, input_files: list[str], output_file: str | None, model: str, max_retries: int = 2) -> dict:
"""Boucle principale : génère, écrit, lint, corrige (max_retries fois)."""
file_context = read_files(input_files) if input_files else ""
result = {"status": "failure", "files_modified": [], "summary": "", "lint": "skipped"}
for attempt in range(max_retries + 1):
response = call_lmstudio(task, file_context, model)
if response.startswith("ERROR:"):
result["summary"] = response
break
target = output_file or (input_files[0] if input_files else None)
if not target:
result["status"] = "success"
result["summary"] = response
result["lint"] = "skipped (no output file)"
break
if write_file(target, response):
result["files_modified"] = [target]
lint_ok, lint_output = run_lint(target)
result["lint"] = "passed" if lint_ok else f"failed: {lint_output[:500]}"
if lint_ok:
result["status"] = "success"
result["summary"] = f"Attempt {attempt + 1}: task completed successfully"
break
elif attempt < max_retries:
task = f"{task}\n\nCORRECTION REQUISE (tentative {attempt + 1}):\n{lint_output}"
file_context = read_files([target])
else:
result["status"] = "partial"
result["summary"] = f"Lint failed after {max_retries + 1} attempts"
return result
def main():
parser = argparse.ArgumentParser(description="Agent loop local pour LM Studio")
parser.add_argument("--task", required=True, help="Description de la tâche")
parser.add_argument("--files", nargs="*", default=[], help="Fichiers source à lire")
parser.add_argument("--output", help="Fichier de sortie (défaut: premier fichier input)")
parser.add_argument("--model", default=DEFAULT_MODEL, help="Modèle LM Studio")
parser.add_argument("--list-models", action="store_true", help="Liste les modèles disponibles")
parser.add_argument("--json", action="store_true", dest="json_output", help="Sortie JSON")
args = parser.parse_args()
if args.list_models:
models = list_models()
if models:
print("Modèles disponibles :")
for m in models:
print(f" - {m}")
else:
print("Aucun modèle trouvé ou LM Studio inaccessible.")
return
result = agent_loop(args.task, args.files, args.output, args.model)
if args.json_output:
print(json.dumps(result, ensure_ascii=False, indent=2))
else:
print(f"STATUS: {result['status']}")
print(f"FILES_MODIFIED: {', '.join(result['files_modified']) or 'none'}")
print(f"SUMMARY: {result['summary']}")
print(f"LINT: {result['lint']}")
sys.exit(0 if result["status"] == "success" else 1)
if __name__ == "__main__":
main()

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requests>=2.31.0

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#!/usr/bin/env -S .claude/venv/bin/python3
"""
MCP server stdio exposant un outil `qwen3_task`.
Appelé par Claude Code via : claude mcp add --transport stdio qwen3 -- .claude/venv/bin/python3 .claude/mcp/qwen3-mcp/server.py
"""
import sys
import json
import requests
LMSTUDIO_URL = "http://localhost:1248/v1/chat/completions"
QWEN3_MODEL = "qwen/qwen3-coder-next"
TOOLS = [{
"name": "qwen3_task",
"description": "Délègue une tâche de codage atomique à Qwen3-Coder via LM Studio.",
"inputSchema": {
"type": "object",
"properties": {
"task": {"type": "string", "description": "Description précise de la tâche"},
"files": {"type": "array", "items": {"type": "string"}, "description": "Chemins des fichiers concernés"}
},
"required": ["task"]
}
}]
def send(obj: dict):
print(json.dumps(obj), flush=True)
def call_qwen3(task: str, files: list[str]) -> str:
context = ""
for path in files:
try:
with open(path) as f:
context += f"--- {path} ---\n{f.read()}\n\n"
except OSError as e:
context += f"--- {path} --- ERREUR: {e}\n\n"
prompt = f"""Tu es un assistant de codage. Effectue la tâche suivante de manière précise.
TÂCHE: {task}
FICHIERS:
{context}
Retourne uniquement le code modifié ou généré, sans explication.
"""
resp = requests.post(
LMSTUDIO_URL,
json={
"model": QWEN3_MODEL,
"messages": [{"role": "user", "content": prompt}],
"temperature": 0.2,
"max_tokens": 4096,
},
timeout=120,
)
resp.raise_for_status()
return resp.json()["choices"][0]["message"]["content"]
def handle(req: dict):
method = req.get("method", "")
req_id = req.get("id")
if method == "initialize":
send({
"jsonrpc": "2.0",
"id": req_id,
"result": {
"protocolVersion": "2024-11-05",
"capabilities": {"tools": {}},
"serverInfo": {"name": "qwen3-mcp", "version": "1.0.0"},
},
})
elif method == "notifications/initialized":
pass # notification, pas de réponse
elif method == "tools/list":
send({"jsonrpc": "2.0", "id": req_id, "result": {"tools": TOOLS}})
elif method == "tools/call":
params = req.get("params", {})
name = params.get("name", "")
args = params.get("arguments", {})
if name == "qwen3_task":
try:
text = call_qwen3(args["task"], args.get("files", []))
send({"jsonrpc": "2.0", "id": req_id, "result": {"content": [{"type": "text", "text": text}]}})
except Exception as e:
send({"jsonrpc": "2.0", "id": req_id, "result": {"content": [{"type": "text", "text": f"ERROR: {e}"}], "isError": True}})
else:
send({"jsonrpc": "2.0", "id": req_id, "error": {"code": -32601, "message": f"Outil inconnu : {name}"}})
elif req_id is not None:
send({"jsonrpc": "2.0", "id": req_id, "error": {"code": -32601, "message": f"Méthode inconnue : {method}"}})
for line in sys.stdin:
line = line.strip()
if not line:
continue
try:
handle(json.loads(line))
except Exception as e:
print(json.dumps({"error": str(e)}), file=sys.stderr, flush=True)