fix: Dev-Agent handles all non-test issues, broaden issue scope beyond qe-feedback label

agents/DEV_AGENT.md

@@ -52,10 +52,19 @@ description: AI 开发专家，负责 document_analyzer 项目的功能开发、
 
 ### 1. 轮询 Issue
 
-使用 `python scripts/agent_poller.py --action list` 列出当前开启的、带有以下标签的 Issue：
+使用 `python scripts/agent_poller.py --action list` 列出所有当前开启的 Issue。
 
-- `qe-feedback` — QE-Agent 提交的功能/质量问题
-- `ci-failure` — CI 自动创建的测试失败 Issue
+**处理范围**：Dev-Agent 负责处理**所有非纯测试开发**相关的 Issue。具体来说：
+
+| 处理 | 跳过 |
+|------|------|
+| `ci-failure` — CI 测试失败 | 标注为 QE-Agent 负责或纯测试实现的 Issue |
+| `bug` — 功能缺陷 | |
+| `qe-feedback` — QE 反馈的功能/质量问题 | |
+| `feature` / `enhancement` — 新功能或改进需求 | |
+| 无标签或自定义标签的 Issue | |
+
+**判断原则**：如果 Issue 涉及功能代码、算法逻辑、IR 生成质量、一致性、覆盖率改进 — 你负责。如果 Issue 纯粹是关于测试框架搭建、测试用例编写 — 那是 QE-Agent 的领域。
 
 ### 2. 分析 Issue
 
@@ -65,7 +74,8 @@ python scripts/agent_poller.py --action get --issue N
 
 根据 Issue 来源决定处理优先级：
 - **ci-failure**：最高优先级，代码已 break，需要立即修复
-- **qe-feedback**：分析 QE-Agent 的反馈，判断是功能缺失、一致性问题还是覆盖率问题，制定改进方案
+- **bug / qe-feedback**：分析反馈，定位根因，制定修复方案
+- **feature / enhancement**：评估可行性和影响范围，设计方案后实施
 
 ### 3. 开发 / 修复
 

scripts/agent_poller.py

@@ -19,7 +19,7 @@ GITEA_REPO = os.environ.get("GITEA_REPO", "pzhang_zywl/document_analyzer")
 GITEA_TOKEN = os.environ.get("GITEA_API_TOKEN", "")
 
 BASE = f"{GITEA_URL}/api/v1/repos/{GITEA_REPO}"
-TARGET_LABELS = {"qe-feedback", "ci-failure"}
+TARGET_LABELS = set()  # List all issues, Dev-Agent handles all non-test issues
 
 
 def _req(method, path, data=None):
@@ -44,8 +44,7 @@ def list_issues():
         return []
     for i in issues:
         labels = [l["name"] for l in i.get("labels", [])]
-        if TARGET_LABELS & set(labels):
-            print(f"#{i['number']} [{', '.join(labels)}] {i['title']}")
+        print(f"#{i['number']} [{', '.join(labels) if labels else 'no label'}] {i['title']}")
     return issues
 
 

scripts/create_failure_issue.py

@@ -18,8 +18,8 @@ def main():
     parser.add_argument("--message", required=True)
     parser.add_argument("--api-token", default=os.environ.get("GITEA_API_TOKEN", ""))
     parser.add_argument("--workflow", default="CI", help="Workflow name that triggered this (default: CI)")
-    parser.add_argument("--labels", default="ci-failure,agent-task",
-                        help="Comma-separated labels for the issue (default: ci-failure,agent-task)")
+    parser.add_argument("--labels", default="ci-failure",
+                        help="Comma-separated labels for the issue (default: ci-failure)")
     args = parser.parse_args()
 
     sha_short = args.sha[:7]

scripts/start_dev_agent.bat

@@ -23,7 +23,7 @@ set /p MODE="请输入 (1/2/3): "
 if "%MODE%"=="1" (
     echo.
     echo 正在执行单次检查...
-    claude -p --agent agents/DEV_AGENT.md "你是 Dev-Agent，检查 Gitea 有没有新的 qe-feedback 或 ci-failure 标签的 Issue，有就领取分析并修复代码，记得同步更新测试。"
+    claude -p --agent agents/DEV_AGENT.md "你是 Dev-Agent，检查 Gitea 所有打开的 Issue，跳过纯测试相关的，其他全部领取分析并修复，记得同步更新测试。"
     pause
     exit
 )
@@ -32,7 +32,7 @@ if "%MODE%"=="2" (
     echo.
     echo 启动持续轮询模式 (每 10 分钟)...
     echo 按 Ctrl+C 停止
-    claude -p --agent agents/DEV_AGENT.md "你是 Dev-Agent，用 loop 模式每 10 分钟检查一次 Gitea Issues，发现 qe-feedback 或 ci-failure 标签就处理。处理完后在对应 Issue 下评论进度，push 代码触发 CI。"
+    claude -p --agent agents/DEV_AGENT.md "你是 Dev-Agent，用 loop 模式每 10 分钟检查一次 Gitea 所有打开的 Issue，跳过纯测试相关的，其他全部领取处理。完成后评论进度，push 触发 CI。"
     pause
     exit
 )

tests/acceptance/conftest.py

@@ -4,8 +4,11 @@ Usage::
 
     pytest tests/acceptance/ -v --run-acceptance [--acceptance-runs=3]
 
+LLM configuration is read from ``~/.openclaw/config/secrets.yaml``:
+    deepseek.apiKey / deepseek.baseUrl  → text model (deepseek-v4-flash)
+    dashscope.apiKey  / dashscope.baseUrl → vision model (qwen3-vl-plus)
+
 Environment variables:
-    DASHSCOPE_API_KEY  — LLM API key (required for Layers B/C)
     TEST_IR_PATH       — path to IR JSON to validate (default: ir_final.json sample)
     TEST_PARSED_PATH   — path to _parsed.json or _updated.json for coverage analysis
 """
@@ -20,17 +23,28 @@ from pathlib import Path
 from typing import Any
 
 import pytest
+import yaml
 
 # ── Path setup ──────────────────────────────────────────────────────────────
 
 _PROJECT_ROOT = Path(__file__).resolve().parent.parent.parent
 sys.path.insert(0, str(_PROJECT_ROOT))
 
+_SECRETS_PATH = Path.home() / ".openclaw" / "config" / "secrets.yaml"
+
 
 def _skill_path(skill_name: str) -> str:
     return str(_PROJECT_ROOT / "skills" / skill_name / "scripts")
 
 
+def _load_secrets() -> dict:
+    """Load LLM configuration from secrets.yaml."""
+    if _SECRETS_PATH.exists():
+        with open(_SECRETS_PATH, "r", encoding="utf-8") as f:
+            return yaml.safe_load(f) or {}
+    return {}
+
+
 # ── pytest configuration ────────────────────────────────────────────────────
 
 
@@ -77,11 +91,12 @@ def pytest_collection_modifyitems(config, items):
         skip_msg = pytest.mark.skip(reason="Need --run-acceptance flag to run")
         for item in acceptance_items:
             item.add_marker(skip_msg)
-        # Don't skip non-acceptance tests
         return
 
-    if not os.environ.get("DASHSCOPE_API_KEY"):
-        skip_msg = pytest.mark.skip(reason="DASHSCOPE_API_KEY not set")
+    secrets = _load_secrets()
+    has_api = bool(secrets.get("deepseek", {}).get("apiKey"))
+    if not has_api:
+        skip_msg = pytest.mark.skip(reason="No deepseek.apiKey in secrets.yaml")
         for item in acceptance_items:
             item.add_marker(skip_msg)
 
@@ -142,16 +157,93 @@ def parsed_data(parsed_path: str | None) -> dict | None:
         return json.load(f)
 
 
+# ── LLM client for acceptance tests ──────────────────────────────────────────
+
+
+class _AcceptanceLLM:
+    """Thin LLM wrapper for acceptance tests.
+
+    Uses deepseek-v4-flash for text (Layer C QE audit) via OpenAI-compatible API,
+    configured from ~/.openclaw/config/secrets.yaml.
+    """
+
+    TEXT_MODEL = "deepseek-v4-flash"
+    IMAGE_MODEL = "qwen3-vl-plus"
+    TIMEOUT = 180
+    MAX_RETRIES = 3
+
+    def __init__(self):
+        import time as _time
+        import openai
+
+        secrets = _load_secrets()
+        ds = secrets.get("deepseek", {})
+        ds_key = ds.get("apiKey", "") or os.environ.get("DEEPSEEK_API_KEY", "")
+        ds_base = ds.get("baseUrl", "https://api.deepseek.com/v1")
+
+        if not ds_key:
+            raise RuntimeError(
+                "No DeepSeek API key found. Set deepseek.apiKey in "
+                f"{_SECRETS_PATH} or DEEPSEEK_API_KEY env var."
+            )
+
+        self._api_key = ds_key
+        self._client = openai.OpenAI(
+            api_key=ds_key, base_url=ds_base, timeout=self.TIMEOUT, max_retries=self.MAX_RETRIES
+        )
+        self._prompt_tokens = 0
+        self._completion_tokens = 0
+        self._time = _time
+
+    def chat(self, model: str | None = None, messages: list[dict] | None = None,
+             response_format: dict | None = None) -> str:
+        """Send a chat completion request and return the text response."""
+        model = model or self.TEXT_MODEL
+        messages = messages or []
+
+        for attempt in range(self.MAX_RETRIES):
+            try:
+                kwargs = {"model": model, "messages": messages}
+                if response_format:
+                    kwargs["response_format"] = response_format
+                resp = self._client.chat.completions.create(**kwargs)
+                choice = resp.choices[0]
+                if choice.finish_reason == "length":
+                    raise RuntimeError(f"Response truncated (finish_reason=length)")
+                usage = resp.usage
+                if usage:
+                    self._prompt_tokens += usage.prompt_tokens or 0
+                    self._completion_tokens += usage.completion_tokens or 0
+                return choice.message.content or ""
+            except Exception as e:
+                if attempt < self.MAX_RETRIES - 1:
+                    delay = 2 ** attempt
+                    self._time.sleep(delay)
+                    continue
+                raise RuntimeError(f"LLM chat failed after {self.MAX_RETRIES} retries: {e}") from e
+        return ""
+
+    @property
+    def usage(self) -> dict:
+        return {
+            "prompt_tokens": self._prompt_tokens,
+            "completion_tokens": self._completion_tokens,
+            "total_tokens": self._prompt_tokens + self._completion_tokens,
+        }
+
+    @staticmethod
+    def estimate_tokens(text: str) -> int:
+        return max(1, len(text) // 3)
+
+
 @pytest.fixture(scope="session")
 def llm_client():
-    """Create an LLMClient instance for acceptance tests.
+    """Create an LLM client for acceptance tests.
 
-    Uses the DashScope-compatible LLMClient from the project.
+    Uses deepseek-v4-flash for text (Layer C QE audit), configured from
+    ~/.openclaw/config/secrets.yaml deepseek section.
     """
-    sys.path.insert(0, _skill_path("doc_parser_skill"))
-    from LLM import LLMClient
-
-    return LLMClient()
+    return _AcceptanceLLM()
 
 
 @pytest.fixture(scope="session")