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 LiYu0524/Auto-Reasearch-Skills --skill paper-bananagit clone --depth 1 https://github.com/LiYu0524/Auto-Reasearch-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/liyu0524/auto-reasearch-skills/paper-banana)<a href="https://agentmods.dev/skills/liyu0524/auto-reasearch-skills/paper-banana"><img src="https://agentmods.dev/badge/skills/liyu0524/auto-reasearch-skills/paper-banana/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/liyu0524/auto-reasearch-skills/paper-banana"><img src="https://agentmods.dev/badge/skills/liyu0524/auto-reasearch-skills/paper-banana.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 | $0.00030 | $0.00987 |
| Opus 5 | $0.00015 | $0.00494 |
| Sonnet 5 | $0.00006 | $0.00197 |
| Haiku 4.5 | $0.00003 | $0.00099 |
Grade A, and why
paper-banana 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paper Banana - 学术插图生成
使用 PaperBanana 多智能体框架（Planner → Visualizer → Critic 循环）从论文方法章节文本自动生成学术插图。
前置安装
# 1. 克隆 PaperBanana
git clone https://github.com/paperbanana/PaperBanana.git ~/PaperBanana
# 2. 安装依赖
cd ~/PaperBanana
pip install -r requirements.txt
# 3. 配置模型（编辑 configs/model_config.yaml）
# 设置 OpenAI 兼容的 API base URL、API key 和模型名
核心命令
SCRIPT=~/.claude/skills/auto-research/skills/paper-banana/scripts/generate_figure.py
# 基本用法
python3 $SCRIPT \
--content "方法文本（Markdown格式）" \
--caption "Figure 1: 框架图标题" \
--output ./figure.png
# 从文件读取内容
python3 $SCRIPT \
--content @method_section.md \
--caption "Figure 1: Pipeline overview" \
--output ./fig1.png
# 高质量模式（完整管线 + 更多迭代）
python3 $SCRIPT \
--content @method.md \
--caption "Figure 2: Architecture" \
--output ./fig2.png \
--exp-mode demo_full \
--critic-rounds 5
# 生成统计图
python3 $SCRIPT \
--content "实验结果数据..." \
--caption "Figure 3: Performance comparison" \
--output ./fig3.png \
--task plot
CLI 参数
| 参数 | 默认值 | 说明 |
|---|---|---|
--content |
(必填) | 方法文本，支持 @filepath 从文件读取 |
--caption |
(必填) | 图表标题 / 视觉意图描述 |
--output |
(必填) | 输出图片路径（.png / .jpg） |
--task |
diagram |
任务类型：diagram（框架图）或 plot（统计图） |
--aspect-ratio |
16:9 |
宽高比 |
--exp-mode |
demo_planner_critic |
管线模式 |
--retrieval-setting |
none |
参考检索策略 |
--critic-rounds |
3 |
最大 Critic 迭代轮数 |
--image-model-name |
(配置文件) | 覆盖图像生成模型 |
--paperbanana-dir |
~/PaperBanana |
PaperBanana 项目路径 |
管线模式对比
| 模式 | 流程 | 适用场景 |
|---|---|---|
demo_planner_critic |
Planner → Visualizer → Critic × N | 快速生成，推荐默认 |
demo_full |
Retriever → Planner → Stylist → Visualizer → Critic × N | 更精美，含风格优化 |
输出格式
脚本输出 JSON 到 stdout：
{
"status": "success",
"output": "/absolute/path/to/figure.png",
"format": "PNG",
"size": "1920x1080",
"exp_mode": "demo_planner_critic",
"task": "diagram"
}
失败时：
{
"status": "error",
"message": "错误描述"
}
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.
- 12d ago First seen · 114 lines · 30 tokens per session scan A 3e3a03a694df
paper-banana is a skill published in the GitHub repository LiYu0524/Auto-Reasearch-Skills (11 stars, last pushed 6mo ago), licensed MIT. It adds 30 tokens to every session and 987 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 2026-08-30.
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