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 frank666199/frank-presales-skills --skill 006-frank-aigit clone --depth 1 https://github.com/frank666199/frank-presales-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/frank666199/frank-presales-skills/006-frank-ai)<a href="https://agentmods.dev/skills/frank666199/frank-presales-skills/006-frank-ai"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/006-frank-ai/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/frank666199/frank-presales-skills/006-frank-ai"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/006-frank-ai.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 | $0.00000 | $0.00635 |
| Opus 5.5 | $0.00000 | $0.00254 |
| Sonnet 5.5 | $0.00000 | $0.00127 |
| Haiku 4.5 | $0.00000 | $0.00064 |
Grade A, and why
006-Frank-AI数据可视化方案工具 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- 008-Frank-AI客户问答话术生成工具 — 86% identical, 44 lines differ
What it actually says
Skill: Frank-AI数据可视化方案工具
Profile
- Author: Frank
- Version: 1.0.0
- Language: 中文
- Category: 维度1 - AI售前工具应用
- Description: 将项目数据转化为合规售前图表，适配G/B端汇报
When to Use
方案中需要数据图表支撑论点时使用
Input Requirements
- 原始数据（表格/文本描述）
- 图表用途（汇报/标书/方案）
- 目标受众
Workflow
- AI解析原始数据，识别数据类型（对比/趋势/占比/分布/流程）
- 根据数据特征推荐最佳图表类型
- 根据目标受众调整图表风格（G端稳重/B端商务/AI科技感）
- 生成图表数据JSON和配色方案
- 输出图表说明文字（标题/图注/数据洞察）
- 提供图表绘制代码或工具配置
Output Format
图表设计方案（含数据、配色、说明文字）+ 绘制指引
Output Template
图表编号 | 图表类型 | 数据源 | 配色方案 | 标题 | 图注 | 数据洞察
Example
| 字段 | 内容 |
|---|---|
| CH001 | 柱状对比图 |
Constraints
- 数据不得虚构
- 图表标注数据来源
- 配色遵循中国政企习惯
Quality Criteria
- 图表类型匹配数据特征
- 视觉风格适配受众
- 说明文字简洁有力
Applicable Scenarios
- G端政府项目: 适用
- B端企业项目: 适用
- AI智能项目: 适用
Usage
方式1：Claude Code / Cursor / Codex
将本SKILL.md内容复制到Agent技能配置区，通过技能名触发。
方式2：飞书妙搭 / 扣子
将SKILL.md内容粘贴到Agent提示词配置区，设置触发词为技能名。
方式3：独立使用
直接复制本文件内容到AI对话中，按Workflow步骤执行。
Frank专属售前技能 | 维度1: AI售前工具应用 | 编号: 006 基于"Frank售前解决方案Skills工具集 v1.0"与实操提示词融合优化生成
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.
- 1mo ago First seen · 88 lines · 0 tokens per session scan A d81c3175a4ad
006-Frank-AI数据可视化方案工具 is a skill published in the GitHub repository frank666199/frank-presales-skills (20 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 635 tokens. 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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