Files
AstrBot/astrbot/core/skills/skill_manager.py
Weilong Liao f2370cd1ba feat: supports plugin to add skills (#7945)
* feat: supports plugin to add skills

* fix tests

* fix: fs tools

* Add tests for plugin skills handling and improve skill management

- Implement test for restricted local member reading plugin skill inventory even if the plugin is inactive.
- Ensure that the skill synchronization process retains built-in skills when local skills are empty, including proper handling of plugin paths.
- Update dashboard tests to verify that plugin details include components when requested.
- Enhance skill metadata enrichment tests to include inactive plugin-provided skills for inventory.
- Add filtering tests for plugin skills based on current configuration, ensuring only allowed plugins are considered and inactive plugins are skipped.

Co-authored-by: Copilot <copilot@github.com>

* fix: handle PPIO platform context-length error messages (#7888)

* fix: 压缩算法删除 user 消息 Bug 修复

* perf: improve truncate algo

* fix: improve context length error detection for PPIO platform compatibility

- Extend error detection to handle PPIO's error message format:
  'The input is longer than the model's context length'
- Add case-insensitive matching using .lower() for robustness
- Maintain backward compatibility with existing 'maximum context length' check

This fixes the issue where PPIO platform models (e.g., ppio/zai-org/glm-5-turbo)
would fail with AgentState.ERROR due to unrecognized context length errors.

---------

Co-authored-by: Soulter <905617992@qq.com>

* fix: 支持微信客服文件消息 (#7923)

* fix: 支持微信客服文件消息

* fix: remove WeCom file message placeholder

* fix(provider): fix Anthropic custom headers and system prompt compatibility (#7587)

* fix(provider): fix Anthropic custom headers and system prompt compatibility

- Pass custom_headers via AsyncAnthropic's `default_headers` parameter
  instead of creating a separate httpx.AsyncClient. This avoids
  `isinstance` check failures when multiple httpx installations exist
  on sys.path (e.g. bundled Python + system Python).

- Use list format for the `system` parameter (`[{"type": "text", ...}]`)
  instead of a plain string. The list format is supported by the official
  Anthropic API and is also compatible with third-party API proxies that
  reject the string format.

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

* fix(provider): fix Anthropic custom headers and system prompt compatibility

- Pass custom_headers via AsyncAnthropic's `default_headers` parameter
  instead of creating a separate httpx.AsyncClient. This avoids
  `isinstance` check failures when multiple httpx installations exist
  on sys.path (e.g. bundled Python + system Python).

- Use list format for the `system` parameter (`[{"type": "text", ...}]`)
  instead of a plain string. The list format is supported by the official
  Anthropic API and is also compatible with third-party API proxies that
  reject the string format.

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

* Add test unit

---------

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

* perf: improve logic of adding models

Co-authored-by: piexian <piexian@users.noreply.github.com>

* chore: remove redundant logger messages and improve log clarity

Co-authored-by: Copilot <copilot@github.com>

* chore: ruff format

* docs: update knowledge base docs

closes: #7962

* fix(#7907): send_message_to_user cron 场景下 session 容错 (#7911)

* fix: send_message_to_user cron 场景下 session 容错 (#7907)

- LLM 在主动场景可能只传 session_id 而非完整三段式,
from_str 失败时用 current_session 补全前两段。

Co-authored-by: Copilot <copilot@github.com>

* fix: 限制 session 补全仅对裸 session_id 生效,避免误修带冒号的错误输入 (#7907)

* feat: add session information to cron job payload

Co-authored-by: Copilot <copilot@github.com>

* fix: improve clarity and consistency of safety mode prompts

Co-authored-by: Copilot <copilot@github.com>

---------

Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Weilong Liao <37870767+Soulter@users.noreply.github.com>
Co-authored-by: Soulter <905617992@qq.com>

* perf: tool rendering in conversation page (#7937)

* fix(dashboard): route conversation history tool messages through ToolCallCard

When viewing conversation history, large tool outputs (e.g. a single
git log --stat producing tens of KB) caused the browser renderer to
freeze. Root cause: formattedMessages mapped every role (including
tool / system / _checkpoint) into user/bot bubbles, and bot plain
strings went through markstream-vue's MarkdownRender. Single 88KB
tool messages plus 88-of-them adding up to ~349KB of synchronous
markdown parsing was enough to block the main thread for 5+ seconds.

This patch:

- Indexes tool-role messages by tool_call_id
- Filters formattedMessages to user/assistant only — tool, system and
  _checkpoint roles no longer render as standalone bubbles
- Converts assistant.tool_calls (OpenAI shape, with tc.name/tc.arguments
  fallbacks) into the existing tool_call MessagePart, attaching the
  paired result so MessageList's ToolCallCard renders it (default
  collapsed, no longer feeds large strings into the markdown renderer)
- Drops empty placeholder plain parts when an assistant message only
  carries tool_calls
- Sets ts/finished_ts to 0 as a sentinel: ToolCallCard.toolCallDuration
  returns "" when startTime <= 0, suppressing a misleading "0ms"
  duration that would otherwise appear because conversation history
  has no real timing data

Behavior change: tool results are now embedded in their assistant's
ToolCallCard.result instead of appearing as separate bot bubbles.
This matches the main chat UI's behavior.

Fixes #7929
Refs #7372 #7456

* style(dashboard): use single scrollbar in conversation history preview

ToolCallCard's result/args panes have their own max-height + overflow,
which produced a nested scrollbar when nested inside the history
preview's already-scrollable .conversation-messages-container. Override
those constraints inside the preview only — the outer 500px-bounded
container already provides scroll bounds, so a single scrollbar feels
cleaner. The main chat UI is unaffected.

---------

Co-authored-by: wanger <wanger@example.com>

* fix: ruff format

* feat: add python tool timeout param (#7953)

* feat: add python tool timeout param

* Update python.py

---------

Co-authored-by: Weilong Liao <37870767+Soulter@users.noreply.github.com>

* fix: 钉钉连接超时后自动重连失败 (#7924)

* fix: improve DingTalk adapter error handling in run() method

* fix: add retry logic for DingTalk SDK task unexpected exit

* fix: use task.add_done_callback to wake thread on task completion, handle UnboundLocalError

* refactor: extract retry logic into handle_retry helper function

---------

Co-authored-by: Blueteemo <Blueteemo@users.noreply.github.com>

---------

Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: leonforcode <leonbeyourside01@gmail.com>
Co-authored-by: AstralSolipsism <134063164+AstralSolipsism@users.noreply.github.com>
Co-authored-by: Pink YuDeer <wer00001@outlook.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Co-authored-by: piexian <piexian@users.noreply.github.com>
Co-authored-by: NayukiMeko <ChibaNayuki@163.com>
Co-authored-by: wanger <122891289+10knamesmore@users.noreply.github.com>
Co-authored-by: wanger <wanger@example.com>
Co-authored-by: Haoran Xu <3230105281@zju.edu.cn>
Co-authored-by: 千岚之夏 <108566281+Blueteemo@users.noreply.github.com>
Co-authored-by: Blueteemo <Blueteemo@users.noreply.github.com>
2026-05-03 16:37:36 +08:00

803 lines
30 KiB
Python

from __future__ import annotations
import json
import os
import re
import shlex
import shutil
import tempfile
import uuid
import zipfile
from dataclasses import dataclass
from datetime import datetime, timezone
from pathlib import Path, PurePosixPath
import yaml
from astrbot.core.utils.astrbot_path import (
get_astrbot_data_path,
get_astrbot_plugin_path,
get_astrbot_skills_path,
get_astrbot_temp_path,
)
SKILLS_CONFIG_FILENAME = "skills.json"
SANDBOX_SKILLS_CACHE_FILENAME = "sandbox_skills_cache.json"
DEFAULT_SKILLS_CONFIG: dict[str, dict] = {"skills": {}}
SANDBOX_SKILLS_ROOT = "skills"
SANDBOX_WORKSPACE_ROOT = "/workspace"
_SANDBOX_SKILLS_CACHE_VERSION = 1
_SKILL_NAME_RE = re.compile(r"^[\w.-]+$")
def _normalize_skill_name(name: str | None) -> str:
raw = str(name or "")
return re.sub(r"\s+", "_", raw.strip())
def _default_sandbox_skill_path(name: str) -> str:
return f"{SANDBOX_WORKSPACE_ROOT}/{SANDBOX_SKILLS_ROOT}/{name}/SKILL.md"
def _normalize_cached_sandbox_skill_path(name: str, path: str) -> str:
normalized = str(path or "").strip().replace("\\", "/")
if not normalized:
return _default_sandbox_skill_path(name)
pure_path = PurePosixPath(normalized)
if ".." in pure_path.parts:
return _default_sandbox_skill_path(name)
if pure_path.name != "SKILL.md":
return _default_sandbox_skill_path(name)
if pure_path.parent.name != name:
return _default_sandbox_skill_path(name)
return str(pure_path)
def _is_ignored_zip_entry(name: str) -> bool:
parts = PurePosixPath(name).parts
if not parts:
return True
return parts[0] == "__MACOSX"
def _normalize_skill_markdown_path(
skill_dir: Path,
*,
rename_legacy: bool = True,
) -> Path | None:
"""Return the canonical `SKILL.md` path for a skill directory.
If only legacy `skill.md` exists, it is renamed to `SKILL.md` in-place.
"""
canonical = skill_dir / "SKILL.md"
entries = set()
if skill_dir.exists():
entries = {entry.name for entry in skill_dir.iterdir()}
if "SKILL.md" in entries:
return canonical
legacy = skill_dir / "skill.md"
if "skill.md" not in entries:
return None
try:
if not rename_legacy:
return legacy
tmp = skill_dir / f".{uuid.uuid4().hex}.tmp_skill_md"
legacy.rename(tmp)
tmp.rename(canonical)
except OSError:
return legacy
return canonical
@dataclass
class SkillInfo:
name: str
description: str
path: str
active: bool
source_type: str = "local_only"
source_label: str = "local"
local_exists: bool = True
sandbox_exists: bool = False
plugin_name: str = ""
readonly: bool = False
def _parse_frontmatter_description(text: str) -> str:
"""Extract the ``description`` value from YAML frontmatter.
Expects the standard SKILL.md format used by OpenAI Codex CLI and
Anthropic Claude Skills::
---
name: my-skill
description: What this skill does and when to use it.
---
"""
if not text.startswith("---"):
return ""
lines = text.splitlines()
if not lines or lines[0].strip() != "---":
return ""
end_idx = None
for i in range(1, len(lines)):
if lines[i].strip() == "---":
end_idx = i
break
if end_idx is None:
return ""
frontmatter = "\n".join(lines[1:end_idx])
try:
payload = yaml.safe_load(frontmatter) or {}
except yaml.YAMLError:
return ""
if not isinstance(payload, dict):
return ""
description = payload.get("description", "")
if not isinstance(description, str):
return ""
return description.strip()
# Regex for sanitizing paths used in prompt examples — only allow
# safe path characters to prevent prompt injection via crafted skill paths.
_SAFE_PATH_RE = re.compile(r"[^\w./ ,()'\-]", re.UNICODE)
_WINDOWS_DRIVE_PATH_RE = re.compile(r"^[A-Za-z]:(?:/|\\)")
_WINDOWS_UNC_PATH_RE = re.compile(r"^(//|\\\\)[^/\\]+[/\\][^/\\]+")
_CONTROL_CHARS_RE = re.compile(r"[\x00-\x1F\x7F]")
def _is_windows_prompt_path(path: str) -> bool:
if os.name != "nt":
return False
return bool(_WINDOWS_DRIVE_PATH_RE.match(path) or _WINDOWS_UNC_PATH_RE.match(path))
def _sanitize_prompt_path_for_prompt(path: str) -> str:
if not path:
return ""
if _WINDOWS_DRIVE_PATH_RE.match(path) or _WINDOWS_UNC_PATH_RE.match(path):
path = path.replace("\\", "/")
drive_prefix = ""
if _WINDOWS_DRIVE_PATH_RE.match(path):
drive_prefix = path[:2]
path = path[2:]
path = path.replace("`", "")
path = _CONTROL_CHARS_RE.sub("", path)
sanitized = _SAFE_PATH_RE.sub("", path)
return f"{drive_prefix}{sanitized}"
def _sanitize_prompt_description(description: str) -> str:
description = description.replace("`", "")
description = _CONTROL_CHARS_RE.sub(" ", description)
description = " ".join(description.split())
return description
def _sanitize_skill_display_name(name: str) -> str:
if _SKILL_NAME_RE.fullmatch(name):
return name
return "<invalid_skill_name>"
def _build_skill_read_command_example(path: str) -> str:
if path == "<skills_root>/<skill_name>/SKILL.md":
return f"cat {path}"
if _is_windows_prompt_path(path):
command = "type"
path_arg = f'"{os.path.normpath(path)}"'
else:
command = "cat"
path_arg = shlex.quote(path)
return f"{command} {path_arg}"
def build_skills_prompt(skills: list[SkillInfo]) -> str:
"""Build the skills section of the system prompt.
Generates a markdown-formatted skill inventory for the LLM. Only
``name`` and ``description`` are shown upfront; the LLM must read
the full ``SKILL.md`` before execution (progressive disclosure).
"""
skills_lines: list[str] = []
example_path = ""
for skill in skills:
display_name = _sanitize_skill_display_name(skill.name)
description = skill.description or "No description"
if skill.source_type == "sandbox_only":
description = _sanitize_prompt_description(description)
if not description:
description = "Read SKILL.md for details."
if skill.source_type == "sandbox_only":
# Prefer the actual path from sandbox cache if available
rendered_path = _sanitize_prompt_path_for_prompt(skill.path)
if not rendered_path:
rendered_path = _default_sandbox_skill_path(skill.name)
else:
rendered_path = _sanitize_prompt_path_for_prompt(skill.path)
if not rendered_path:
rendered_path = "<skills_root>/<skill_name>/SKILL.md"
skills_lines.append(
f"- **{display_name}**: {description}\n File: `{rendered_path}`"
)
if not example_path:
example_path = rendered_path
skills_block = "\n".join(skills_lines)
# Sanitize example_path — it may originate from sandbox cache (untrusted)
if example_path == "<skills_root>/<skill_name>/SKILL.md":
example_path = "<skills_root>/<skill_name>/SKILL.md"
else:
example_path = _sanitize_prompt_path_for_prompt(example_path)
example_path = example_path or "<skills_root>/<skill_name>/SKILL.md"
example_command = _build_skill_read_command_example(example_path)
return (
"## Skills\n\n"
"You have specialized skills — reusable instruction bundles stored "
"in `SKILL.md` files. Each skill has a **name** and a **description** "
"that tells you what it does and when to use it.\n\n"
"### Available skills\n\n"
f"{skills_block}\n\n"
"### Skill rules\n\n"
"1. **Discovery** — The list above is the complete skill inventory "
"for this session. Full instructions are in the referenced "
"`SKILL.md` file.\n"
"2. **When to trigger** — Use a skill if the user names it "
"explicitly, or if the task clearly matches the skill's description. "
"*Never silently skip a matching skill* — either use it or briefly "
"explain why you chose not to.\n"
"3. **Mandatory grounding** — Before executing any skill you MUST "
"first read its `SKILL.md` by running a shell command compatible "
"with the current runtime shell and using the **absolute path** "
f"shown above (e.g. `{example_command}`). "
"Never rely on memory or assumptions about a skill's content.\n"
"4. **Progressive disclosure** — Load only what is directly "
"referenced from `SKILL.md`:\n"
" - If `scripts/` exist, prefer running or patching them over "
"rewriting code from scratch.\n"
" - If `assets/` or templates exist, reuse them.\n"
" - Do NOT bulk-load every file in the skill directory.\n"
"5. **Coordination** — When multiple skills apply, pick the minimal "
"set needed. Announce which skill(s) you are using and why "
"(one short line). Prefer `astrbot_*` tools when running skill "
"scripts.\n"
"6. **Context hygiene** — Avoid deep reference chasing; open only "
"files that are directly linked from `SKILL.md`.\n"
"7. **Failure handling** — If a skill cannot be applied, state the "
"issue clearly and continue with the best alternative.\n"
)
class SkillManager:
def __init__(
self,
skills_root: str | None = None,
plugins_root: str | None = None,
) -> None:
self.skills_root = skills_root or get_astrbot_skills_path()
self.plugins_root = plugins_root or get_astrbot_plugin_path()
data_path = Path(get_astrbot_data_path())
self.config_path = str(data_path / SKILLS_CONFIG_FILENAME)
self.sandbox_skills_cache_path = str(data_path / SANDBOX_SKILLS_CACHE_FILENAME)
os.makedirs(self.skills_root, exist_ok=True)
def _iter_plugin_skill_dirs(self) -> list[tuple[str, str, Path]]:
"""Return plugin-provided skill directories as (skill, plugin, dir)."""
plugins_root = Path(self.plugins_root)
if not plugins_root.is_dir():
return []
result: list[tuple[str, str, Path]] = []
for plugin_dir in sorted(plugins_root.iterdir(), key=lambda item: item.name):
if not plugin_dir.is_dir():
continue
plugin_name = plugin_dir.name
skills_dir = plugin_dir / "skills"
if not skills_dir.is_dir():
continue
direct_skill_md = _normalize_skill_markdown_path(
skills_dir,
rename_legacy=False,
)
if direct_skill_md is not None and _SKILL_NAME_RE.match(plugin_name):
result.append((plugin_name, plugin_name, skills_dir))
for skill_dir in sorted(skills_dir.iterdir(), key=lambda item: item.name):
if not skill_dir.is_dir():
continue
skill_name = skill_dir.name
if not _SKILL_NAME_RE.match(skill_name):
continue
if (
_normalize_skill_markdown_path(skill_dir, rename_legacy=False)
is None
):
continue
result.append((skill_name, plugin_name, skill_dir))
return result
def _get_plugin_skill_dir(self, name: str) -> Path | None:
for skill_name, _plugin_name, skill_dir in self._iter_plugin_skill_dirs():
if skill_name == name:
return skill_dir
return None
def _load_config(self) -> dict:
if not os.path.exists(self.config_path):
self._save_config(DEFAULT_SKILLS_CONFIG.copy())
return DEFAULT_SKILLS_CONFIG.copy()
with open(self.config_path, encoding="utf-8") as f:
data = json.load(f)
if not isinstance(data, dict) or "skills" not in data:
return DEFAULT_SKILLS_CONFIG.copy()
return data
def _save_config(self, config: dict) -> None:
with open(self.config_path, "w", encoding="utf-8") as f:
json.dump(config, f, ensure_ascii=False, indent=4)
def _load_sandbox_skills_cache(self) -> dict:
if not os.path.exists(self.sandbox_skills_cache_path):
return {"version": _SANDBOX_SKILLS_CACHE_VERSION, "skills": []}
try:
with open(self.sandbox_skills_cache_path, encoding="utf-8") as f:
data = json.load(f)
if not isinstance(data, dict):
return {"version": _SANDBOX_SKILLS_CACHE_VERSION, "skills": []}
skills = data.get("skills", [])
if not isinstance(skills, list):
skills = []
return {
"version": int(data.get("version", _SANDBOX_SKILLS_CACHE_VERSION)),
"skills": skills,
"updated_at": data.get("updated_at"),
}
except Exception:
return {"version": _SANDBOX_SKILLS_CACHE_VERSION, "skills": []}
def _save_sandbox_skills_cache(self, cache: dict) -> None:
cache["version"] = _SANDBOX_SKILLS_CACHE_VERSION
cache["updated_at"] = datetime.now(timezone.utc).isoformat()
with open(self.sandbox_skills_cache_path, "w", encoding="utf-8") as f:
json.dump(cache, f, ensure_ascii=False, indent=2)
def set_sandbox_skills_cache(self, skills: list[dict]) -> None:
"""Persist sandbox skill metadata discovered from runtime side."""
deduped: dict[str, dict[str, str]] = {}
for item in skills:
if not isinstance(item, dict):
continue
name = str(item.get("name", "")).strip()
if not name or not _SKILL_NAME_RE.match(name):
continue
description = str(item.get("description", "") or "")
path = _normalize_cached_sandbox_skill_path(
name, str(item.get("path", "") or "")
)
deduped[name] = {
"name": name,
"description": description,
"path": path,
}
cache = {
"version": _SANDBOX_SKILLS_CACHE_VERSION,
"skills": [deduped[name] for name in sorted(deduped)],
}
self._save_sandbox_skills_cache(cache)
def get_sandbox_skills_cache_status(self) -> dict[str, object]:
cache = self._load_sandbox_skills_cache()
skills = cache.get("skills", [])
count = len(skills) if isinstance(skills, list) else 0
return {
"exists": os.path.exists(self.sandbox_skills_cache_path),
"ready": count > 0,
"count": count,
"updated_at": cache.get("updated_at"),
}
def list_skills(
self,
*,
active_only: bool = False,
runtime: str = "local",
show_sandbox_path: bool = True,
) -> list[SkillInfo]:
"""List all skills.
show_sandbox_path: If True and runtime is "sandbox",
return the path as it would appear in the sandbox environment,
otherwise return the local filesystem path.
"""
config = self._load_config()
skill_configs = config.get("skills", {})
modified = False
skills_by_name: dict[str, SkillInfo] = {}
sandbox_cached_paths: dict[str, str] = {}
sandbox_cached_descriptions: dict[str, str] = {}
cache_for_paths = self._load_sandbox_skills_cache()
for item in cache_for_paths.get("skills", []):
if not isinstance(item, dict):
continue
name = str(item.get("name", "") or "").strip()
path = _normalize_cached_sandbox_skill_path(
name, str(item.get("path", "") or "")
)
if not name or not _SKILL_NAME_RE.match(name):
continue
sandbox_cached_descriptions[name] = str(item.get("description", "") or "")
sandbox_cached_paths[name] = path
for entry in sorted(Path(self.skills_root).iterdir()):
if not entry.is_dir():
continue
skill_name = entry.name
skill_md = _normalize_skill_markdown_path(entry)
if skill_md is None:
continue
active = skill_configs.get(skill_name, {}).get("active", True)
if skill_name not in skill_configs:
skill_configs[skill_name] = {"active": active}
modified = True
if active_only and not active:
continue
description = ""
try:
content = skill_md.read_text(encoding="utf-8")
description = _parse_frontmatter_description(content)
except Exception:
description = ""
sandbox_exists = (
runtime == "sandbox" and skill_name in sandbox_cached_descriptions
)
source_type = "both" if sandbox_exists else "local_only"
source_label = "synced" if sandbox_exists else "local"
if runtime == "sandbox" and show_sandbox_path:
path_str = sandbox_cached_paths.get(
skill_name
) or _default_sandbox_skill_path(skill_name)
else:
path_str = str(skill_md)
path_str = path_str.replace("\\", "/")
skills_by_name[skill_name] = SkillInfo(
name=skill_name,
description=description,
path=path_str,
active=active,
source_type=source_type,
source_label=source_label,
local_exists=True,
sandbox_exists=sandbox_exists,
)
for skill_name, plugin_name, skill_dir in self._iter_plugin_skill_dirs():
if skill_name in skills_by_name:
continue
skill_md = _normalize_skill_markdown_path(skill_dir, rename_legacy=False)
if skill_md is None:
continue
active = skill_configs.get(skill_name, {}).get("active", True)
if skill_name not in skill_configs:
skill_configs[skill_name] = {"active": active}
modified = True
if active_only and not active:
continue
description = ""
try:
content = skill_md.read_text(encoding="utf-8")
description = _parse_frontmatter_description(content)
except Exception:
description = ""
sandbox_exists = (
runtime == "sandbox" and skill_name in sandbox_cached_descriptions
)
if runtime == "sandbox" and show_sandbox_path:
path_str = sandbox_cached_paths.get(
skill_name
) or _default_sandbox_skill_path(skill_name)
else:
path_str = str(skill_md)
skills_by_name[skill_name] = SkillInfo(
name=skill_name,
description=description,
path=path_str.replace("\\", "/"),
active=active,
source_type="plugin",
source_label=plugin_name,
local_exists=True,
sandbox_exists=sandbox_exists,
plugin_name=plugin_name,
readonly=True,
)
if runtime == "sandbox":
cache = self._load_sandbox_skills_cache()
for item in cache.get("skills", []):
if not isinstance(item, dict):
continue
skill_name = str(item.get("name", "")).strip()
if (
not skill_name
or skill_name in skills_by_name
or not _SKILL_NAME_RE.match(skill_name)
):
continue
active = skill_configs.get(skill_name, {}).get("active", True)
if skill_name not in skill_configs:
skill_configs[skill_name] = {"active": active}
modified = True
if active_only and not active:
continue
description = sandbox_cached_descriptions.get(skill_name, "")
# For sandbox_only skills, show_sandbox_path is implicitly True
# since there is no local path to show. Always prefer the
# actual path from sandbox cache.
path_str = sandbox_cached_paths.get(
skill_name
) or _default_sandbox_skill_path(skill_name)
skills_by_name[skill_name] = SkillInfo(
name=skill_name,
description=description,
path=path_str.replace("\\", "/"),
active=active,
source_type="sandbox_only",
source_label="sandbox_preset",
local_exists=False,
sandbox_exists=True,
)
if modified:
config["skills"] = skill_configs
self._save_config(config)
return [skills_by_name[name] for name in sorted(skills_by_name)]
def is_sandbox_only_skill(self, name: str) -> bool:
skill_dir = Path(self.skills_root) / name
skill_md_exists = _normalize_skill_markdown_path(skill_dir) is not None
if skill_md_exists:
return False
cache = self._load_sandbox_skills_cache()
skills = cache.get("skills", [])
if not isinstance(skills, list):
return False
for item in skills:
if not isinstance(item, dict):
continue
if str(item.get("name", "")).strip() == name:
return True
return False
def is_plugin_skill(self, name: str) -> bool:
return self._get_plugin_skill_dir(name) is not None
def set_skill_active(self, name: str, active: bool) -> None:
if self.is_sandbox_only_skill(name):
raise PermissionError(
"Sandbox preset skill cannot be enabled/disabled from local skill management."
)
config = self._load_config()
config.setdefault("skills", {})
config["skills"][name] = {"active": bool(active)}
self._save_config(config)
def _remove_skill_from_sandbox_cache(self, name: str) -> None:
cache = self._load_sandbox_skills_cache()
skills = cache.get("skills", [])
if not isinstance(skills, list):
return
filtered = [
item
for item in skills
if not (
isinstance(item, dict) and str(item.get("name", "")).strip() == name
)
]
if len(filtered) != len(skills):
cache["skills"] = filtered
self._save_sandbox_skills_cache(cache)
def delete_skill(self, name: str) -> None:
if self.is_sandbox_only_skill(name):
raise PermissionError(
"Sandbox preset skill cannot be deleted from local skill management."
)
if self.is_plugin_skill(name):
raise PermissionError(
"Plugin-provided skill cannot be deleted from local skill management."
)
skill_dir = Path(self.skills_root) / name
if skill_dir.exists():
shutil.rmtree(skill_dir)
# Ensure UI consistency even when there is no active sandbox session
# to refresh cache from runtime side.
self._remove_skill_from_sandbox_cache(name)
config = self._load_config()
if name in config.get("skills", {}):
config["skills"].pop(name, None)
self._save_config(config)
def install_skill_from_zip(
self,
zip_path: str,
*,
overwrite: bool = True,
skill_name_hint: str | None = None,
) -> str:
zip_path_obj = Path(zip_path)
if not zip_path_obj.exists():
raise FileNotFoundError(f"Zip file not found: {zip_path}")
if not zipfile.is_zipfile(zip_path):
raise ValueError("Uploaded file is not a valid zip archive.")
installed_skills = []
with zipfile.ZipFile(zip_path) as zf:
names = [
name
for name in (entry.replace("\\", "/") for entry in zf.namelist())
if name and not _is_ignored_zip_entry(name)
]
file_names = [name for name in names if name and not name.endswith("/")]
if not file_names:
raise ValueError("Zip archive is empty.")
has_root_skill_md = any(
len(parts := PurePosixPath(name).parts) == 1
and parts[0] in {"SKILL.md", "skill.md"}
for name in file_names
)
root_mode = has_root_skill_md
archive_skill_name = None
if skill_name_hint is not None:
archive_skill_name = _normalize_skill_name(skill_name_hint)
if archive_skill_name and not _SKILL_NAME_RE.fullmatch(
archive_skill_name
):
raise ValueError("Invalid skill name.")
for name in names:
if not name:
continue
if name.startswith("/") or re.match(r"^[A-Za-z]:", name):
raise ValueError("Zip archive contains absolute paths.")
parts = PurePosixPath(name).parts
if ".." in parts:
raise ValueError("Zip archive contains invalid relative paths.")
if not root_mode and not overwrite:
top_dirs = {PurePosixPath(n).parts[0] for n in file_names if n.strip()}
conflict_dirs: list[str] = []
for src_dir_name in top_dirs:
if (
f"{src_dir_name}/SKILL.md" not in file_names
and f"{src_dir_name}/skill.md" not in file_names
):
continue
candidate_name = _normalize_skill_name(src_dir_name)
if not candidate_name or not _SKILL_NAME_RE.fullmatch(
candidate_name
):
continue
if archive_skill_name and len(top_dirs) == 1:
target_name = archive_skill_name
else:
target_name = candidate_name
dest_dir = Path(self.skills_root) / target_name
if dest_dir.exists():
conflict_dirs.append(str(dest_dir))
if conflict_dirs:
raise FileExistsError(
"One or more skills from the archive already exist and "
"overwrite=False. No skills were installed. Conflicting "
f"paths: {', '.join(conflict_dirs)}"
)
with tempfile.TemporaryDirectory(dir=get_astrbot_temp_path()) as tmp_dir:
for member in zf.infolist():
member_name = member.filename.replace("\\", "/")
if not member_name or _is_ignored_zip_entry(member_name):
continue
zf.extract(member, tmp_dir)
if root_mode:
archive_hint = _normalize_skill_name(
archive_skill_name or zip_path_obj.stem
)
if not archive_hint or not _SKILL_NAME_RE.fullmatch(archive_hint):
raise ValueError("Invalid skill name.")
skill_name = archive_hint
src_dir = Path(tmp_dir)
normalized_path = _normalize_skill_markdown_path(src_dir)
if normalized_path is None:
raise ValueError(
"SKILL.md not found in the root of the zip archive."
)
dest_dir = Path(self.skills_root) / skill_name
if dest_dir.exists() and overwrite:
shutil.rmtree(dest_dir)
elif dest_dir.exists() and not overwrite:
raise FileExistsError(f"Skill {skill_name} already exists.")
shutil.move(str(src_dir), str(dest_dir))
self.set_skill_active(skill_name, True)
installed_skills.append(skill_name)
else:
top_dirs = {
PurePosixPath(n).parts[0] for n in file_names if n.strip()
}
for archive_root_name in top_dirs:
archive_root_name_normalized = _normalize_skill_name(
archive_root_name
)
if (
f"{archive_root_name}/SKILL.md" not in file_names
and f"{archive_root_name}/skill.md" not in file_names
):
continue
if archive_root_name in {".", "..", ""} or not (
_SKILL_NAME_RE.fullmatch(archive_root_name_normalized)
):
continue
if archive_skill_name and len(top_dirs) == 1:
skill_name = archive_skill_name
else:
skill_name = archive_root_name_normalized
src_dir = Path(tmp_dir) / archive_root_name
normalized_path = _normalize_skill_markdown_path(src_dir)
if normalized_path is None:
continue
dest_dir = Path(self.skills_root) / skill_name
if dest_dir.exists():
if not overwrite:
raise FileExistsError(
f"Skill {skill_name} already exists."
)
shutil.rmtree(dest_dir)
shutil.move(str(src_dir), str(dest_dir))
self.set_skill_active(skill_name, True)
installed_skills.append(skill_name)
if not installed_skills:
raise ValueError(
"No valid SKILL.md found in any folder of the zip archive."
)
return ", ".join(installed_skills)