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 agentscope-ai/QwenPaw-Data --skill bi-comparison-analysisgit clone --depth 1 https://github.com/agentscope-ai/QwenPaw-DataWrote 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/agentscope-ai/qwenpaw-data/bi-comparison-analysis)<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw-data/bi-comparison-analysis"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw-data/bi-comparison-analysis/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/agentscope-ai/qwenpaw-data/bi-comparison-analysis"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw-data/bi-comparison-analysis.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 | $0.00084 | $0.00933 |
| Opus 5 | $0.00042 | $0.00466 |
| Sonnet 5 | $0.00017 | $0.00187 |
| Haiku 4.5 | $0.00008 | $0.00093 |
Grade A, and why
bi-comparison-analysis 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 11d 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
bi-comparison-analysis
对不同时间、群体、地区、渠道、版本之间的指标差异值进行分析。
执行步骤
Step 1. 明确比较维度
一般而言，对比分析主要涉及以下 3 个维度：
| 维度 | 说明 | 目的 |
|---|---|---|
| 时间对比 (纵向) | 同比（与历史相同节点）或环比（与相邻节点） | 了解发展速度、规模水平的增减变化 |
| 空间对比 (横向) | 与同类对象、竞争对手或行业平均水平对比 | 评估自身在群体中的水平高低，找出差距 |
| 标准对比 (计划对比) | 将实际完成数据与目标、计划、预算数值对比 | 检查指标是否达标，评估业务运行是否协调 |
根据数据分析需求以及上述维度的解释说明，选择合理的对比维度。
Step 2. 设定基准与比较对象
根据所确定的比较分析维度以及提供的数据，选择合适的对比参照物（时间、空间或标准），以及确定合理的比较对象。确保参照物与比较对象的数据在统计口径、计量标准上一致，具有可比性。
整理数据为一份 CSV 文件，包含参照物相应数据列以及比较对象相应数据列。以“对比不同端转化情况”为例，可用的数据类似
业务日期,web端转化率,app端转化率
20251101,0.7856,0.2343
20251102,0.2288,0.8822
20251103,0.6677,0.7760
Step 3. 计算差异
对比分析的定量计算形式主要有以下两种
| 方式 | 计算方式 | 例子 |
|---|---|---|
| 绝对差值 | (差值=对象A - 对象B) | 数值大小比较 |
| 相对差值 | (差异率=\frac{对象A - 对象B}{对象B}) | 环比增长、同比增长 |
根据步骤 1 和步骤 2 确定的比较维度、参照物和比较对象，从中选择合适的定量计算方式计算对比差异。不遗漏任何需要比较的对象。
Step 4. 显著性分析
当对两组或多组数据进行比较，且比较结果具有多个样本时，需进行显著性分析。常用显著性检验方法如下：
| 检验方法 | 适用场景 | 数据要求 |
|---|---|---|
| t 检验 | 两组均值对比，样本量 < 30 或总体方差未知 | 连续型数据，近似正态分布 |
| z 检验 | 两组均值/比例对比，大样本量（n ≥ 30） | 连续型或二分类数据 |
| 卡方检验 | 分类变量独立性检验、拟合优度检验 | 频数数据，期望频数 ≥ 5 |
显著性检验方法选择策略如下：
if 数据为分类变量:
使用 chi_square
elif 样本量 >= 30:
使用 z_test
else:
使用 t_test
各个检验方法的具体计算方式参见 <skill-dir>/references/significance-test.md。
输出要求
输出差异定量计算结果，以及显著性检验方式、检验统计量与 P 值（如果执行了显著性分析）。不要遗失任何计算结果，包括 NaN 值。
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.
- 11d ago First seen · 74 lines · 84 tokens per session scan A 24d587a89e01
bi-comparison-analysis is a skill published in the GitHub repository agentscope-ai/QwenPaw-Data (71 stars, last pushed 2d ago), licensed Apache-2.0. It adds 84 tokens to every session and 933 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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