Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add IvanYangYangXi/artclaw_bridge --skill artclaw-skill-managegit clone --depth 1 https://github.com/IvanYangYangXi/artclaw_bridgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ivanyangyangxi/artclaw_bridge/artclaw-skill-manage)<a href="https://agentmods.dev/skills/ivanyangyangxi/artclaw_bridge/artclaw-skill-manage"><img src="https://agentmods.dev/badge/skills/ivanyangyangxi/artclaw_bridge/artclaw-skill-manage/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ivanyangyangxi/artclaw_bridge/artclaw-skill-manage"><img src="https://agentmods.dev/badge/skills/ivanyangyangxi/artclaw_bridge/artclaw-skill-manage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00121 | $0.01579 |
| Opus 5 | $0.00060 | $0.00790 |
| Sonnet 5 | $0.00024 | $0.00316 |
| Haiku 4.5 | $0.00012 | $0.00158 |
Grade A, and why
artclaw-skill-manage scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ArtClaw 技能管理
管理 ArtClaw 的 Skill 技能包:列出、执行、安装、卸载、更新、发布、重命名、创建。
版本与更新模型
Skill 存在于两个位置,数据流是单向的:
源码 skills/{layer}/{dcc}/{name}/ ──更新──> 已安装 ~/.openclaw/workspace/skills/{name}/
(Git 仓库,分发给其他用户) <──发布── (本地运行时,AI 实际使用)
- 编辑:修改已安装目录中的文件(SKILL.md /
__init__.py/ references) - 发布:
publish_skill()— 已安装目录 → 源码仓库,自动 bump 版本 + git commit - 更新:
update_skill()/sync_all()— 源码仓库 → 已安装目录(覆盖安装) - 变更检测:有版本号用版本对比,无版本号用文件内容 hash 对比
调用方式
通过 MCP 工具 run_ue_python(UE)或 run_python(Maya/Max)执行 Python 代码。
常用操作
列出 Skill
from skill_hub import get_skill_hub
hub = get_skill_hub()
for s in hub.list_skills():
print(f"[{s['category']}] {s['name']} v{s.get('version','?')} - {s['description']}")
安装 / 更新 / 全量更新
from skill_sync import install_skill, update_skill, sync_all
install_skill("ue57_batch_rename_actors") # 从源码安装单个
update_skill("ue57_get_material_nodes") # 从源码更新单个
sync_all() # 安装未安装的 + 更新版本不一致的
卸载
from skill_sync import uninstall_skill
uninstall_skill("ue57_batch_rename_actors")
发布(已安装 → 源码仓库)
from skill_sync import publish_skill
result = publish_skill(
"ue57_my_tool",
target_layer="marketplace", # 或 "official"
bump="patch", # patch / minor / major
changelog="修复了多选时的bug",
dcc="unreal", # universal / unreal / maya / max
)
对比源码 vs 已安装
from skill_sync import compare_source_vs_runtime
diff = compare_source_vs_runtime()
# diff: {available, installed, updatable, orphaned, project_root, error}
重命名
from skill_sync import rename_skill
result = rename_skill("old_skill_name", "new_skill_name")
# 自动更新: 安装目录 + manifest.json + SKILL.md frontmatter + 源码目录
创建新 Skill
步骤
hub.auto_name(description)生成名称- AI 生成
__init__.py+manifest.json - 必须生成
SKILL.md(含 YAML frontmatter,见下方模板) - 保存到已安装目录
~/.openclaw/workspace/skills/<skill_name>/ publish_skill()发布到源码仓库
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 180 lines · 121 tokens per session scan A ce8fcf7ae17a
artclaw-skill-manage is a skill published in the GitHub repository IvanYangYangXi/artclaw_bridge (35 stars, last pushed 4mo ago), licensed MIT. It adds 121 tokens to every session and 1,579 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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