refactor: split backend into harness (deerflow.*) and app (app.*) (#1131)

* refactor: extract shared utils to break harness→app cross-layer imports

Move _validate_skill_frontmatter to src/skills/validation.py and
CONVERTIBLE_EXTENSIONS + convert_file_to_markdown to src/utils/file_conversion.py.
This eliminates the two reverse dependencies from client.py (harness layer)
into gateway/routers/ (app layer), preparing for the harness/app package split.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* refactor: split backend/src into harness (deerflow.*) and app (app.*)

Physically split the monolithic backend/src/ package into two layers:

- **Harness** (`packages/harness/deerflow/`): publishable agent framework
  package with import prefix `deerflow.*`. Contains agents, sandbox, tools,
  models, MCP, skills, config, and all core infrastructure.

- **App** (`app/`): unpublished application code with import prefix `app.*`.
  Contains gateway (FastAPI REST API) and channels (IM integrations).

Key changes:
- Move 13 harness modules to packages/harness/deerflow/ via git mv
- Move gateway + channels to app/ via git mv
- Rename all imports: src.* → deerflow.* (harness) / app.* (app layer)
- Set up uv workspace with deerflow-harness as workspace member
- Update langgraph.json, config.example.yaml, all scripts, Docker files
- Add build-system (hatchling) to harness pyproject.toml
- Add PYTHONPATH=. to gateway startup commands for app.* resolution
- Update ruff.toml with known-first-party for import sorting
- Update all documentation to reflect new directory structure

Boundary rule enforced: harness code never imports from app.
All 429 tests pass. Lint clean.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* chore: add harness→app boundary check test and update docs

Add test_harness_boundary.py that scans all Python files in
packages/harness/deerflow/ and fails if any `from app.*` or
`import app.*` statement is found. This enforces the architectural
rule that the harness layer never depends on the app layer.

Update CLAUDE.md to document the harness/app split architecture,
import conventions, and the boundary enforcement test.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add config versioning with auto-upgrade on startup

When config.example.yaml schema changes, developers' local config.yaml
files can silently become outdated. This adds a config_version field and
auto-upgrade mechanism so breaking changes (like src.* → deerflow.*
renames) are applied automatically before services start.

- Add config_version: 1 to config.example.yaml
- Add startup version check warning in AppConfig.from_file()
- Add scripts/config-upgrade.sh with migration registry for value replacements
- Add `make config-upgrade` target
- Auto-run config-upgrade in serve.sh and start-daemon.sh before starting services
- Add config error hints in service failure messages

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix comments

* fix: update src.* import in test_sandbox_tools_security to deerflow.*

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: handle empty config and search parent dirs for config.example.yaml

Address Copilot review comments on PR #1131:
- Guard against yaml.safe_load() returning None for empty config files
- Search parent directories for config.example.yaml instead of only
  looking next to config.yaml, fixing detection in common setups

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* fix: correct skills root path depth and config_version type coercion

- loader.py: fix get_skills_root_path() to use 5 parent levels (was 3)
  after harness split, file lives at packages/harness/deerflow/skills/
  so parent×3 resolved to backend/packages/harness/ instead of backend/
- app_config.py: coerce config_version to int() before comparison in
  _check_config_version() to prevent TypeError when YAML stores value
  as string (e.g. config_version: "1")
- tests: add regression tests for both fixes

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix: update test imports from src.* to deerflow.*/app.* after harness refactor

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

backend/packages/harness/deerflow/config/agents_config.py

@@ -0,0 +1,120 @@
+"""Configuration and loaders for custom agents."""
+
+import logging
+import re
+from typing import Any
+
+import yaml
+from pydantic import BaseModel
+
+from deerflow.config.paths import get_paths
+
+logger = logging.getLogger(__name__)
+
+SOUL_FILENAME = "SOUL.md"
+AGENT_NAME_PATTERN = re.compile(r"^[A-Za-z0-9-]+$")
+
+
+class AgentConfig(BaseModel):
+    """Configuration for a custom agent."""
+
+    name: str
+    description: str = ""
+    model: str | None = None
+    tool_groups: list[str] | None = None
+
+
+def load_agent_config(name: str | None) -> AgentConfig | None:
+    """Load the custom or default agent's config from its directory.
+
+    Args:
+        name: The agent name.
+
+    Returns:
+        AgentConfig instance.
+
+    Raises:
+        FileNotFoundError: If the agent directory or config.yaml does not exist.
+        ValueError: If config.yaml cannot be parsed.
+    """
+
+    if name is None:
+        return None
+
+    if not AGENT_NAME_PATTERN.match(name):
+        raise ValueError(f"Invalid agent name '{name}'. Must match pattern: {AGENT_NAME_PATTERN.pattern}")
+    agent_dir = get_paths().agent_dir(name)
+    config_file = agent_dir / "config.yaml"
+
+    if not agent_dir.exists():
+        raise FileNotFoundError(f"Agent directory not found: {agent_dir}")
+
+    if not config_file.exists():
+        raise FileNotFoundError(f"Agent config not found: {config_file}")
+
+    try:
+        with open(config_file, encoding="utf-8") as f:
+            data: dict[str, Any] = yaml.safe_load(f) or {}
+    except yaml.YAMLError as e:
+        raise ValueError(f"Failed to parse agent config {config_file}: {e}") from e
+
+    # Ensure name is set from directory name if not in file
+    if "name" not in data:
+        data["name"] = name
+
+    # Strip unknown fields before passing to Pydantic (e.g. legacy prompt_file)
+    known_fields = set(AgentConfig.model_fields.keys())
+    data = {k: v for k, v in data.items() if k in known_fields}
+
+    return AgentConfig(**data)
+
+
+def load_agent_soul(agent_name: str | None) -> str | None:
+    """Read the SOUL.md file for a custom agent, if it exists.
+
+    SOUL.md defines the agent's personality, values, and behavioral guardrails.
+    It is injected into the lead agent's system prompt as additional context.
+
+    Args:
+        agent_name: The name of the agent or None for the default agent.
+
+    Returns:
+        The SOUL.md content as a string, or None if the file does not exist.
+    """
+    agent_dir = get_paths().agent_dir(agent_name) if agent_name else get_paths().base_dir
+    soul_path = agent_dir / SOUL_FILENAME
+    if not soul_path.exists():
+        return None
+    content = soul_path.read_text(encoding="utf-8").strip()
+    return content or None
+
+
+def list_custom_agents() -> list[AgentConfig]:
+    """Scan the agents directory and return all valid custom agents.
+
+    Returns:
+        List of AgentConfig for each valid agent directory found.
+    """
+    agents_dir = get_paths().agents_dir
+
+    if not agents_dir.exists():
+        return []
+
+    agents: list[AgentConfig] = []
+
+    for entry in sorted(agents_dir.iterdir()):
+        if not entry.is_dir():
+            continue
+
+        config_file = entry / "config.yaml"
+        if not config_file.exists():
+            logger.debug(f"Skipping {entry.name}: no config.yaml")
+            continue
+
+        try:
+            agent_cfg = load_agent_config(entry.name)
+            agents.append(agent_cfg)
+        except Exception as e:
+            logger.warning(f"Skipping agent '{entry.name}': {e}")
+
+    return agents