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 sd-contextgit 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/sd-context)<a href="https://agentmods.dev/skills/ivanyangyangxi/artclaw_bridge/sd-context"><img src="https://agentmods.dev/badge/skills/ivanyangyangxi/artclaw_bridge/sd-context/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/sd-context"><img src="https://agentmods.dev/badge/skills/ivanyangyangxi/artclaw_bridge/sd-context.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 | $0.00062 | $0.01836 |
| Opus 5 | $0.00031 | $0.00918 |
| Sonnet 5 | $0.00012 | $0.00367 |
| Haiku 4.5 | $0.00006 | $0.00184 |
Grade A, and why
sd-context 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 10d 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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SD 编辑器上下文查询
查询 Substance Designer 当前状态:包、图、节点、参数、连接关系。 所有操作为只读,不修改任何内容。
前置条件
run_python 已预注入以下变量,直接使用,无需 import:
sd,app,graph,S,W,LSDPropertyCategory,float2,float3,float4,ColorRGBASDValueFloat,SDValueInt,SDValueBool,SDValueString
# ✅ 直接使用预注入变量
pkg_mgr = app.getPackageMgr()
ui_mgr = app.getUIMgr()
# ❌ 禁止在 exec 中 import sd.api 子模块(会超时死锁)
# from sd.api.sdapplication import SDApplication # 禁止!
# from sd.api.sdproperty import SDPropertyCategory # 禁止!
1. 获取用户包列表
列出当前加载的所有用户包(排除系统/库包):
pkg_mgr = app.getPackageMgr()
user_packages = pkg_mgr.getUserPackages()
result = []
for pkg in user_packages:
file_path = pkg.getFilePath()
pkg_id = pkg.getIdentifier() if hasattr(pkg, 'getIdentifier') else "N/A"
resources = pkg.getChildrenResources(False)
graph_count = len(resources) if resources else 0
result.append({
"identifier": pkg_id,
"file_path": file_path,
"graph_count": graph_count
})
print(f"包: {pkg_id} | 路径: {file_path} | 图数量: {graph_count}")
if not result:
print("没有加载的用户包")
2. 获取包内图列表
列出指定包的所有子图(Substance Graph):
pkg_mgr = app.getPackageMgr()
# 获取第一个用户包
user_packages = pkg_mgr.getUserPackages()
if not user_packages:
print("没有加载的用户包")
else:
pkg = user_packages[0]
resources = pkg.getChildrenResources(False)
for res in resources:
res_id = res.getIdentifier()
res_type = type(res).__name__
print(f"资源: {res_id} | 类型: {res_type}")
3. 获取当前图信息
if graph is None:
print("没有打开的图")
else:
graph_id = graph.getIdentifier()
nodes = graph.getNodes()
node_count = nodes.getSize() if nodes else 0
# 获取图的输出定义
outputs = graph.getProperties(SDPropertyCategory.Output)
output_count = len(outputs) if outputs else 0
print(f"当前图: {graph_id}")
print(f"节点数量: {node_count}")
print(f"输出数量: {output_count}")
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 261 lines · 62 tokens per session scan A 8a4e70f35891
sd-context is a skill published in the GitHub repository IvanYangYangXi/artclaw_bridge (35 stars, last pushed 4mo ago), licensed MIT. It adds 62 tokens to every session and 1,836 once invoked, about $0.0003 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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