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 binggandata/bggg-skills --skill bggg-creator-image2pptgit clone --depth 1 https://github.com/binggandata/bggg-skillsWrote 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/binggandata/bggg-skills/bggg-creator-image2ppt)<a href="https://agentmods.dev/skills/binggandata/bggg-skills/bggg-creator-image2ppt"><img src="https://agentmods.dev/badge/skills/binggandata/bggg-skills/bggg-creator-image2ppt/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/binggandata/bggg-skills/bggg-creator-image2ppt"><img src="https://agentmods.dev/badge/skills/binggandata/bggg-skills/bggg-creator-image2ppt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00179 | $0.02064 |
| Opus 5 | $0.00089 | $0.01032 |
| Sonnet 5 | $0.00036 | $0.00413 |
| Haiku 4.5 | $0.00018 | $0.00206 |
Grade A, and why
bggg-creator-image2ppt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 178 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BGGG Creator Image2PPT
用这个 skill 把平面视觉稿转换成可编辑的 .pptx。核心设计是“先形成结构化 manifest,再由脚本生成 PPTX”。
- 二进制图片输入:Codex 负责识别版式、文字和组件;默认调用
imagegenskill 生成或清理背景、装饰、产品、图表等组件图片;文本尽量还原为 PowerPoint 文本框。 - HTML/SVG 输入:优先把代码结构解析为原生 PPT 元素;复杂节点再降级为图片组件。
- 所有中间图片、manifest、诊断和输出都必须放在本 skill 的
projects/YYYYMMDD_slug/目录里。
Codex 默认策略
在 Codex 中处理 PNG/JPEG/WebP 等二进制图片时,默认执行这个顺序:
- 使用 Codex 视觉能力观察源图,列出幻灯片尺寸、背景、标题、正文、图标、照片、图表、装饰、阴影、遮罩等对象。
- 对于可编辑文字,直接写入 manifest 的
text元素,不要把文字只做成图片。 - 对于背景、照片、图标、复杂插画、图表、纹理、遮挡后需要补全的背景,使用
imagegenskill 生成、清理或重建独立组件图片。 - 把
imagegen生成的图片复制到当前项目目录的imagegen_assets/或component_images/,不要让项目依赖$CODEX_HOME的临时输出。 - 写
manifest.json,用scripts/image2pptx.py build生成 PPTX。 - 验证 PPTX 能被
python-pptx重新打开,并记录图层/文本/图片数量和已知限制。
如果用户明确要求“不重绘”“保持原图像素”,可以用原图裁切或全画布透明 PNG 作为组件图片;但默认仍要用 Codex imagegen 能力辅助背景清理、缺失区域补全和组件干净化。
项目目录约定
每次转换都创建独立项目目录:
bggg-creator-image2ppt/
└── projects/
└── YYYYMMDD_slug/
├── original_inputs/
├── component_images/
├── imagegen_assets/
├── diagnostics/
├── manifest.json
├── output.pptx
├── summary.json
└── process_notes.md
初始化:
python3 bggg-creator-image2ppt/scripts/init_project.py pitch_deck \
--source /path/to/reference.png \
--date 20260504
二进制图片转 PPTX 工作流
-
初始化项目,把源图复制到
original_inputs/。 -
识别页面结构:
- 画布比例和大致尺寸。
- 背景是纯色、渐变、照片还是复杂插画。
- 每段文字的内容、位置、字号、颜色、粗细、对齐方式。
- 组件图片的边界、层级和是否需要透明背景。
-
默认用
imagegen生成或编辑组件:- 背景:完整画布、无文字、无前景组件。
- 照片/产品/人物/图标/复杂装饰:干净边缘,必要时透明背景。
- 图表:能原生重建就用形状和文本;复杂图表可先做成图片组件。
-
把组件图片放入
component_images/或imagegen_assets/。 -
写 manifest,元素按从底到顶排序。
-
运行:
python3 bggg-creator-image2ppt/scripts/image2pptx.py build \ --manifest bggg-creator-image2ppt/projects/YYYYMMDD_slug/manifest.json \ --output bggg-creator-image2ppt/projects/YYYYMMDD_slug/output.pptx \ --summary bggg-creator-image2ppt/projects/YYYYMMDD_slug/summary.json
What ships with it
12 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.
- .gitignore 49 B
- assets/sample-manifest.json 1.4 KB
- evals/evals.json 1.8 KB
- LICENSE 1.0 KB
- projects/.gitkeep 0 B
- README_EN.md 5.4 KB
- README.md 5.2 KB
- references/implementation-notes.md 2.3 KB
- scripts/html_svg_to_manifest.py 16 KB runs code
- scripts/image2pptx.py 23 KB runs code
- scripts/init_project.py 3.7 KB runs code
- scripts/requirements.txt 70 B
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 · 178 lines · 179 tokens per session scan A 3baf34eec691
bggg-creator-image2ppt is a skill published in the GitHub repository binggandata/bggg-skills (594 stars, last pushed 1mo ago), licensed MIT. It adds 179 tokens to every session and 2,064 once invoked, about $0.0009 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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