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/zju-real/easel/data-reportnpx skills add ZJU-REAL/Easel --skill data-reportgit clone --depth 1 https://github.com/ZJU-REAL/EaselWrote 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/zju-real/easel/data-report)<a href="https://agentmods.dev/skills/zju-real/easel/data-report"><img src="https://agentmods.dev/badge/skills/zju-real/easel/data-report.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 5.1 | $0.00075 | $0.01006 |
| Opus 5 | $0.00037 | $0.00503 |
| Sonnet 5 | $0.00015 | $0.00201 |
| Haiku 4.5 | $0.00007 | $0.00101 |
Grade A, and why
data-report 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 6d 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.
What it actually says
数据可视化报告
你是一名数据可视化专家。把用户提供的 CSV/Excel/JSON 数据，转成一份自包含的 HTML 可视化报告（KPI 卡片 + 图表 + 数据洞察 + 数据表）。
数据读取、聚合、出图、HTML 组装都由 scripts/report.py 确定性完成，
你只负责"写洞察文字"这一需要理解的环节，不要手算聚合、手拼图表。
与其他图表 SKILL 的区别
三者都能"生成图表"，但机制与产物不同，按需求路由：
- data-report（本 SKILL） = 输入 CSV/Excel/JSON，产出整页可视化报告（KPI 卡 + 多图 + 洞察 + 表格）。要一份完整报告页时用它。
- chart-visualization = 调 AntV 远程 API，产出单张静态图片 URL（25+ 类型）。只要一张标准统计图、直接拿图片链接时用它。
- infographic = 本地 JS 渲染，产出信息图 / GIF 动画图表。要结构化信息图或带动画的 GIF/MP4 时用它。
输入
- 数据文件：
.csv/.json/.xlsx（Excel 需环境有 openpyxl，缺失时脚本会提示） - 可选：报告标题、想突出的 KPI 列名
输出
- 一个自包含 HTML 报告文件（图表以 base64 内嵌，可离线打开），写入
outputs/ - 可选：把 HTML 渲染成一张长图用于社媒分享
执行步骤
1. 读数据概览（供你写洞察）
python skills/openclaw/data-report/scripts/report.py analyze <数据文件>
返回 JSON：行列数、每列类型与缺失、数值列的 min/max/mean/median/sum/std、 每个类别列的 Top 5。据此判断数据讲了什么，为第 3 步准备洞察文字。
2. 生成报告 HTML
python skills/openclaw/data-report/scripts/report.py report <数据文件> \
-o outputs/主题名/report.html \
--title "报告标题" \
--kpi 列名1 列名2 # 可选，不给则自动挑数值列
脚本自动：算 KPI（数值列汇总）、自动选型出 2-4 张图（时间序列→折线、 类别→柱状、占比→饼图）、拼成含 KPI 卡 + 内嵌图 + 数据表的整页 HTML。 matplotlib 用 Agg 后端并已配好中文字体，不会乱码。
3. 补写洞察文字（可选但推荐）
基于第 1 步的概览，在生成的 HTML 里补 3-5 条洞察（emoji 开头、像产品周报： 趋势、异常、对比、行动建议）。用 Edit 在报告的洞察区插入即可——数据都是 真实的，不要捏造数字，只做解读。
4. 渲染成长图分享（可选）
python skills/shared/scripts/render_card.py \
--html outputs/主题名/report.html \
--out outputs/主题名/report.png \
--full-page --width 1080
Profile 感知
- 有 Profile：从
style.md读品牌主色，用 Edit 改 HTML 里--main变量统一配色。 - 无 Profile：用脚本默认专业配色。
要点
- 必须用脚本解析真实数据，KPI 与图表由脚本从数据算出，不要手写数值。
- 洞察是你唯一"创作"的部分，其余都走脚本保证确定性。
- 无数值列时脚本仍出数据表（会打印 WARN），报告依然可用。
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.
- 6d ago First seen · 82 lines · 75 tokens per session scan A 56f511a83c6e
data-report is a skill published in the GitHub repository ZJU-REAL/Easel (352 stars, last pushed yesterday), licensed Apache-2.0. It adds 75 tokens to every session and 1,006 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.
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