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 ue57_viewport_capturegit 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/ue57_viewport_capture)<a href="https://agentmods.dev/skills/ivanyangyangxi/artclaw_bridge/ue57_viewport_capture"><img src="https://agentmods.dev/badge/skills/ivanyangyangxi/artclaw_bridge/ue57_viewport_capture/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/ue57_viewport_capture"><img src="https://agentmods.dev/badge/skills/ivanyangyangxi/artclaw_bridge/ue57_viewport_capture.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 | $0.00092 | $0.01480 |
| Opus 5 | $0.00046 | $0.00740 |
| Sonnet 5 | $0.00018 | $0.00296 |
| Haiku 4.5 | $0.00009 | $0.00148 |
Grade A, and why
ue57-viewport-capture 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
UE 视口截图与场景分析
截取 UE 编辑器视口画面（支持颜色/深度/法线等多 Buffer），收集相机变换和场景元数据，构建 AI 视觉分析上下文。
调用方式
通过 run_ue_python 执行 Python 代码。所有函数在 __init__.py 中定义。
核心概念
Buffer 类型
| Buffer | 说明 | 格式 | 用途 |
|---|---|---|---|
color |
最终渲染画面 (LDR) | JPG | 默认，通用分析 |
base_color |
基础颜色（无光照） | JPG | 材质/贴图分析 |
depth |
场景深度 | PNG | 空间关系、遮挡分析 |
normal |
世界法线 | PNG | 几何质量、表面朝向 |
hdr |
HDR 颜色 | EXR | 曝光/色调分析 |
分析模式
| Mode | 说明 |
|---|---|
general |
综合分析（内容、构图、光照、颜色、优化） |
composition |
构图分析（三分法、视觉焦点、空间层次） |
lighting |
光照分析（光源、阴影、GI、色温） |
performance |
性能分析（过度绘制、LOD、光源数量） |
color |
色彩分析（色调、配色、后处理） |
custom |
自定义分析（需提供 custom_prompt） |
分辨率策略
- 截图分辨率 (
quick_capture): 1920×1080，保证画面质量 - 分析分辨率 (
quick_analyze): 1024×576，节省 token（颜色 JPG ~49KB，三 buffer 合计 ~233KB base64） - 颜色类 buffer 用 JPG 压缩（quality=85），深度/法线用 PNG 保持精度
操作示例
模块导入（每次使用前）
import importlib, sys
skill_path = r"C:\Users\yangjili\.openclaw\workspace\skills\ue57_viewport_capture"
if skill_path not in sys.path:
sys.path.insert(0, skill_path)
if "ue57_viewport_capture" in sys.modules:
importlib.reload(sys.modules["ue57_viewport_capture"])
from ue57_viewport_capture import quick_capture, quick_analyze, capture_viewport_scenecapture, cleanup_captures
1. 快速截图（全分辨率）
from ue57_viewport_capture import quick_capture
result = quick_capture() # 仅颜色
result = quick_capture(buffers=["color", "depth", "normal"]) # 多 buffer
print(result["images"]) # {"color": "D:/.../capture_xxx_color.jpg"}
print(result["camera"]) # {"location": {...}, "rotation": {...}}
2. AI 分析截图（小分辨率，省 token）
from ue57_viewport_capture import quick_analyze
# 综合分析
context = quick_analyze(mode="general")
# 光照分析（含深度）
context = quick_analyze(mode="lighting", buffers=["color", "depth"])
# 性能分析（全 buffer）
context = quick_analyze(mode="performance", buffers=["color", "depth", "normal"])
# 自定义分析
context = quick_analyze(
mode="custom",
buffers=["color"],
custom_prompt="请分析这个场景是否适合作为恐怖游戏的关卡。"
)
What ships with it
2 files 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.
- 12d ago First seen · 173 lines · 92 tokens per session scan A 864e2db83b51
ue57-viewport-capture is a skill published in the GitHub repository IvanYangYangXi/artclaw_bridge (35 stars, last pushed 4mo ago), licensed MIT. It adds 92 tokens to every session and 1,480 once invoked, about $0.0005 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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