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 skills/bojieli/ai-agent-book/pptxnpx skills add bojieli/ai-agent-book --skill pptxgit clone --depth 1 https://github.com/bojieli/ai-agent-bookWhat 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 | $0.00084 | $0.00678 |
| Opus 5 | $0.00042 | $0.00339 |
| Sonnet 5 | $0.00017 | $0.00136 |
| Haiku 4.5 | $0.00008 | $0.00068 |
Grade A, and why
pptx 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
pptx Skill —— 从论文生成演示文稿
核心流程（第二层）
把一份来源文本（论文 / 大纲）转成 8-12 页的演示文稿，按以下步骤：
- 通读来源：理解论文的标题、作者、问题背景、方法、关键结果、结论。
- 规划页序：一份合格的演示文稿总页数应为 8-12 页，至少覆盖——
- 标题页（论文标题 + 作者/来源作为副标题）
- 目录 / 大纲页
- 研究背景 / 问题动机
- 方法概述（必须拆成 2 页，例如「总体思路」与「关键机制」）
- 关键结果 / 实验发现（必须拆成 2 页，例如「效率指标」与「效果对比」）
- 局限性 / 讨论
- 小结 / 结论页（要点式总结全篇）
- 提炼要点：每页 3-5 条 bullet，每条一句话，避免整段照搬原文。
- 生成文件：调用本 Skill 捆绑的脚本
scripts/generate_pptx.py（通过run_skill_script工具），传入下面约定的 JSON payload。
捆绑脚本调用约定
工具：run_skill_script(name="pptx", script="generate_pptx.py", payload=<JSON字符串>)
payload 的 JSON schema：
{
"title": "演示文稿主标题（通常等于论文标题）",
"subtitle": "副标题，通常是作者或来源，可留空",
"slides": [
{"title": "页标题", "bullets": ["要点1", "要点2", "要点3"]}
]
}
约束：
slides至少 8 项（加上自动生成的标题页，总页数落在 8-12 页区间）。- 第一项通常是「目录 / 大纲」，最后一项应为「小结 / 结论」。
- 每页
bullets建议 3-5 条。
更详细的样式与实现细则（第三层）
如需了解版式、配色、python-pptx 的实现细节，或排查生成问题，
再用 read_skill_file 读取本 Skill 内的：
reference.md—— 版式、配色与 python-pptx 技术细节scripts/generate_pptx.py—— 生成器源码本身
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.
- yesterday First seen · 52 lines · 84 tokens per session scan A 24561726e75c
pptx is a skill published in the GitHub repository bojieli/ai-agent-book (43,601 stars, last pushed 2d ago), licensed Apache-2.0. It adds 84 tokens to every session and 678 once invoked, about $0.0004 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.
Other skills, from other repositories
acontext-installer
Install Acontext, Login & Init Acontext Project, Add Skill Memory to Agent.
tura
Work in the Tura agent-runtime repository. Use for Tura architecture, Rust backend, GUI/TUI, prompts, commands, providers, sessions, documentation, tests, packaging, and release work in this directory.
remem-mcp
Long-term memory for coding agents. Auto-applies at the start of any coding task — recall past context before answering, capture decisions/learnings/fixes after work, use CodeGraph instead of grep for symbol lookup. Invoke when you see [remem-mcp] in your context or when starting any non-trivial coding work.
kayba-stage-5-action-plan
Triage each insight into discard/code-fix/prompt-fix and produce a prioritized action plan with specific recommendations. Trigger when the user says "run stage 5", "make action plan", "triage skills", or when invoked by the kayba-pipeline orchestrator. Requires eval outputs from stages 1-4.
kayba-stage-2-domain-context
Gather domain context about the repository and agent — system prompt, tool definitions, domain docs, and behavior patterns from traces. Trigger when the user says "run stage 2", "gather context", "domain context", or when invoked by the kayba-pipeline orchestrator.
kayba-stage-7-fixer
Implement the approved fixes from the action plan and log all changes. Trigger when the user says "run stage 7", "implement fixes", "apply action plan", or when invoked by the kayba-pipeline orchestrator. Requires eval/actionplan.md to exist.