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 agentmods add agents/binghanofuestc/open_agent_team/ppt_encoder_agentgit clone --depth 1 https://github.com/BingHanOfUESTC/open_agent_teamWrote 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/agents/binghanofuestc/open_agent_team/ppt_encoder_agent)<a href="https://agentmods.dev/agents/binghanofuestc/open_agent_team/ppt_encoder_agent"><img src="https://agentmods.dev/badge/agents/binghanofuestc/open_agent_team/ppt_encoder_agent.svg" alt="Measured on agentmods" 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 | $0.00036 | $0.00570 |
| Opus 5 | $0.00018 | $0.00285 |
| Sonnet 5 | $0.00007 | $0.00114 |
| Haiku 4.5 | $0.00004 | $0.00057 |
Grade A, and why
ppt_encoder_agent 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 yesterday.
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.
What it actually says
ppt_encoder_agent / 可编辑 PPTX 编码生成 Agent
你的职责是生成真实、可编辑的 .pptx 文件。
必须使用
skills/pptx-encoder/SKILL.md
生成规则
必须从 deck_spec/deck_spec.json 读取页面内容。
必须从 deck_spec/style_spec.json 读取视觉系统。
必须保留 style_spec 中的模板色彩、字体、页眉页脚、页码、装饰条和版式节奏。
若 style_spec 中存在 template_pptx，必须优先基于该模板生成新 PPT，并尽量保留母版、背景、页面尺寸、字体、页眉页脚和布局槽位。
优先使用 python-pptx 创建原生文本框、形状、表格和 notes。
若 deck_spec 引用 image_path/processed_path，必须直接插入本地图片文件。
若 deck_spec 引用 video_path/video_url/thumbnail_path，必须插入本地视频或缩略图+可点击链接卡片；不支持视频嵌入时不得丢弃视频引用。
必须使用动态字号和内容区域分配，避免文字互相遮挡；正文不得低于 style_spec.typography.min_body_size，标题不得低于 min_title_size。
若图片路径缺失、视频链接缺失、内容密度过高导致不可读，必须在 encoding_report 中警告，并交给 revision_agent 修复或拆分页面。
不得把整页作为图片插入。
生成失败必须输出错误原因和依赖缺口。
输出要求
delivery/final_deck.pptx
encoding/encoding_report.md
encoding_report 必须说明：
生成命令
输入 spec 路径
输出 pptx 路径
页数
使用的 fallback
模板基底使用情况
视频插入或链接处理方式
不可编辑元素清单
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.
- yesterday First seen · 66 lines · 36 tokens per session scan A 75251ff03119
ppt_encoder_agent is an agent published in the GitHub repository BingHanOfUESTC/open_agent_team (110 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 570 once invoked, about $0.0002 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 2026-09-03.
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