molecule-core/workspace/skill_loader/loader.py
Hongming Wang d0057912d2 feat(skills): per-skill runtime compatibility (#119, hermes pattern)
SKILL.md frontmatter can now declare `runtime: [claude-code]` or
`runtime: [hermes, claude-code]` to opt out of incompatible adapters
instead of failing at first invocation. Default `["*"]` means universal —
existing skill libraries need zero migration.

Borrowed from hermes' declarative skill-compat pattern surfaced in the
hermes architecture survey. The remaining two patterns (event-log
layer, observability config block) stay open under #119.

Wiring:
- SkillMetadata.runtime: list[str] = ["*"]
- _normalize_runtime_field accepts list, string-sugar, missing -> ["*"];
  malformed warns and falls back to universal so a typo never silently
  drops a skill.
- load_skills(..., current_runtime=...) filters out skills whose runtime
  list lacks "*" or current_runtime, with an INFO log line.
- BaseAdapter.start passes type(self).name() so the live adapter drives
  the filter; SkillsWatcher takes the same kwarg so hot-reload honors it.

8 new tests cover default universal, no-field universal, explicit
match/mismatch, string sugar, wildcard short-circuit, current_runtime=None
(preserves old behavior), and malformed-warns-not-drops.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-27 01:57:43 -07:00

238 lines
8.4 KiB
Python

"""Load skill packages from the workspace config directory."""
import importlib.util
import logging
import os
import sys
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any
import yaml
logger = logging.getLogger(__name__)
try:
from builtin_tools.security_scan import SkillSecurityError, scan_skill_dependencies
_SECURITY_SCAN_AVAILABLE = True
except ImportError: # lightweight test environments without tools/ on sys.path
_SECURITY_SCAN_AVAILABLE = False
@dataclass
class SkillMetadata:
id: str
name: str
description: str
tags: list[str] = field(default_factory=list)
examples: list[str] = field(default_factory=list)
# Runtime compatibility — list of adapter `name()` values this skill
# supports, or ["*"] for universal. Borrowed from hermes' declarative
# skill-compat pattern: a skill that depends on claude-code-only tools
# should declare `runtime: [claude-code]` so hermes (or any other
# adapter) skips it at load time instead of failing at first invocation.
runtime: list[str] = field(default_factory=lambda: ["*"])
@dataclass
class LoadedSkill:
metadata: SkillMetadata
instructions: str
tools: list[Any] = field(default_factory=list)
def parse_skill_frontmatter(skill_md_path: Path) -> tuple[dict, str]:
"""Parse YAML frontmatter from a SKILL.md file.
Runtime-side: tolerant of malformed frontmatter (returns ``({}, body)``
so the skill loads with empty metadata rather than crashing the
workspace at startup). The SDK's :func:`molecule_plugin.parse_skill_md`
is the authoring-time strict validator that surfaces the same errors.
Keep behaviour aligned: if you change acceptance rules here, mirror
them in the SDK's parser.
"""
content = skill_md_path.read_text()
if not content.startswith("---"):
return {}, content
parts = content.split("---", 2)
if len(parts) < 3:
return {}, content
try:
frontmatter = yaml.safe_load(parts[1]) or {}
except yaml.YAMLError:
logger.warning("SKILL.md at %s has malformed frontmatter; loading with empty metadata", skill_md_path)
frontmatter = {}
if not isinstance(frontmatter, dict):
logger.warning("SKILL.md at %s frontmatter is not a mapping; ignoring", skill_md_path)
frontmatter = {}
body = parts[2].strip()
return frontmatter, body
def load_skill_tools(scripts_dir: Path) -> list[Any]:
"""Dynamically load tool functions from a skill's scripts/ directory.
Follows the agentskills.io spec layout: each skill's executable code
lives under ``scripts/``. Returns an empty list if the directory
doesn't exist.
"""
tools = []
if not scripts_dir.exists():
return tools
# Import langchain only when we actually have scripts to process.
# Keeps test environments (and empty skills) from needing langchain.
from langchain_core.tools import BaseTool
# Sensitive env vars that must not be readable by skill scripts.
# Fix C (Cycle 5): scrub before exec_module() so a malicious skill cannot
# exfiltrate credentials even if it somehow bypasses the POST /plugins
# auth gate (defence in depth).
_SCRUB_KEYS = (
"CLAUDE_CODE_OAUTH_TOKEN",
"ANTHROPIC_API_KEY",
"OPENAI_API_KEY",
"WORKSPACE_AUTH_TOKEN",
"GITHUB_TOKEN",
"GH_TOKEN",
)
for py_file in sorted(scripts_dir.glob("*.py")):
if py_file.name.startswith("_"):
continue
# Verify the script is actually inside the expected scripts directory
# (path traversal guard — glob shouldn't produce outside paths, but
# belt-and-suspenders for symlink attacks).
try:
py_file.resolve().relative_to(scripts_dir.resolve())
except ValueError:
logger.warning("skill_loader: rejecting script outside scripts_dir: %s", py_file)
continue
module_name = f"skill_tool_{py_file.stem}"
spec = importlib.util.spec_from_file_location(module_name, py_file)
if spec is None or spec.loader is None:
continue
module = importlib.util.module_from_spec(spec)
sys.modules[module_name] = module
# Temporarily remove sensitive env vars before running skill code.
_saved_env = {k: os.environ.pop(k) for k in _SCRUB_KEYS if k in os.environ}
try:
spec.loader.exec_module(module)
finally:
# Always restore so the rest of the agent process retains them.
os.environ.update(_saved_env)
# Look for functions decorated with @tool (BaseTool instances)
for attr_name in dir(module):
attr = getattr(module, attr_name)
if isinstance(attr, BaseTool):
tools.append(attr)
return tools
def _normalize_runtime_field(raw: Any, skill_name: str) -> list[str]:
"""Normalize the optional `runtime` frontmatter field to a list[str].
Accepts: ["*"] (default), ["claude-code"], "claude-code" (string sugar),
or absent (-> ["*"]). Anything else logs a warning and falls back to
universal so a malformed manifest doesn't silently filter the skill.
"""
if raw is None:
return ["*"]
if isinstance(raw, str):
return [raw]
if isinstance(raw, list) and all(isinstance(x, str) for x in raw):
return raw or ["*"]
logger.warning(
"SKILL.md for '%s' has invalid `runtime` field %r; treating as universal",
skill_name, raw,
)
return ["*"]
def load_skills(
config_path: str,
skill_names: list[str],
current_runtime: str | None = None,
) -> list[LoadedSkill]:
"""Load all skills specified in the config.
If ``current_runtime`` is provided, skills whose ``runtime`` frontmatter
list does not include ``"*"`` or ``current_runtime`` are skipped (with a
log line) instead of being loaded — matches hermes' declarative compat
model so adapter-specific skills don't get force-loaded into runtimes
that can't actually execute their tools.
"""
skills_dir = Path(config_path) / "skills"
loaded = []
# Resolve security scan mode once before the loop
scan_mode = "warn"
fail_open_if_no_scanner = True # safe default matches security_scan.py default
if _SECURITY_SCAN_AVAILABLE:
try:
from config import load_config
_cfg = load_config(config_path)
scan_mode = _cfg.security_scan.mode
fail_open_if_no_scanner = _cfg.security_scan.fail_open_if_no_scanner
except Exception:
pass # use defaults — never block on config error
for skill_name in skill_names:
skill_path = skills_dir / skill_name
skill_md = skill_path / "SKILL.md"
if not skill_md.exists():
logger.warning("SKILL.md not found for %s, skipping", skill_name)
continue
# --- Security scan before loading any code from the skill ------------
if _SECURITY_SCAN_AVAILABLE and scan_mode != "off":
try:
scan_skill_dependencies(
skill_name, skill_path, scan_mode,
fail_open_if_no_scanner=fail_open_if_no_scanner,
)
except SkillSecurityError as exc:
logger.warning("Skipping skill '%s': blocked by security scan — %s", skill_name, exc)
continue
frontmatter, instructions = parse_skill_frontmatter(skill_md)
runtime_compat = _normalize_runtime_field(frontmatter.get("runtime"), skill_name)
if current_runtime is not None and "*" not in runtime_compat and current_runtime not in runtime_compat:
logger.info(
"Skipping skill '%s': runtime=%s not compatible with current=%s",
skill_name, runtime_compat, current_runtime,
)
continue
metadata = SkillMetadata(
id=skill_name,
name=frontmatter.get("name", skill_name),
description=frontmatter.get("description", ""),
tags=frontmatter.get("tags", []),
examples=frontmatter.get("examples", []),
runtime=runtime_compat,
)
# Executables live under scripts/ per the agentskills.io spec.
tools = load_skill_tools(skill_path / "scripts")
loaded.append(LoadedSkill(
metadata=metadata,
instructions=instructions,
tools=tools,
))
return loaded