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-conversion-rategit 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-conversion-rate)<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw-data/bi-conversion-rate"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw-data/bi-conversion-rate/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-conversion-rate"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw-data/bi-conversion-rate.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 | $0.00050 | $0.00660 |
| Opus 5 | $0.00025 | $0.00330 |
| Sonnet 5 | $0.00010 | $0.00132 |
| Haiku 4.5 | $0.00005 | $0.00066 |
Grade A, and why
bi-conversion-rate 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 10d 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-conversion-rate
计算用户从接触目标行为（起始阶段）到完成目标行为（结束阶段）的转化率。
执行步骤
Step 0: 检查数据以及确定计算指标
- 转化率计算涉及的指标以及数据范围（初始状态数据以及目标状态数据）已经明确，如指标明确为“对话转化率”，转化率计算需“访问用户数”与“对话用户数”；
- 数据已经保存为 CSV 文件，且包含转化率计算所需关键数据，如上述的“访问用户数”与“对话用户数”。如
date,访问用户数,对话用户数
2025-01-01,10000,3000
2025-01-02,10500,1000
2025-01-03,9800,100
Step 1: 执行转化率计算
使用 <skill-dir>/scripts/compute_conversion.py 脚本，计算用户从某初始状态到目标状态的转化率（计算结果保留小数点后 5 位）。
python <skill-dir>/scripts/compute_retention.py --input_file "<输入数据文件路径 (CSV)>" --metric_name "<转化率名称>" --begin_col "<初始行为状态的对象列名>" --end_col "<目标/结束行为状态的对象列名>"
参数说明：
| 参数 | 说明 | 默认值 |
|---|---|---|
| --input_file | 输入数据文件路径 (.csv) | (必填) |
| --metric_name | 计算指标名称（如对话转化率等） | 转化率 |
| --begin_col | 初始行为状态的对象列名 | (必填) |
| --end_col | 目标/结束行为状态的对象列名 | (必填) |
对于所有需要计算的转化率指标都需调用该脚本计算，不能遗失任何必要的指标计算。
fallback (指引模式)
无脚本环境时按以下计算公式手动计算转化率：
$$ \text{转换率}=\frac{\text{User at the final stage}}{\text{User at the beginning stage}} $$
- 分母：起始阶段用户数（接触过目标行为或进入漏斗起点）
- 分子：结束阶段用户数（完成目标行为）
- 口径须与业务一致（例如结束阶段用户是否为起始阶段的子集、是否去重同一用户）
输出要求
输出所有需要计算的转化率指标结果，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.
- 10d ago First seen · 57 lines · 50 tokens per session scan A 43b5c19ac574
bi-conversion-rate is a skill published in the GitHub repository agentscope-ai/QwenPaw-Data (71 stars, last pushed yesterday), licensed Apache-2.0. It adds 50 tokens to every session and 660 once invoked, about $0.0003 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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