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 084-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/084-frank-ai)<a href="https://agentmods.dev/skills/frank666199/frank-presales-skills/084-frank-ai"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/084-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/084-frank-ai"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/084-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 | $0.00645 |
| Opus 5.5 | $0.00000 | $0.00258 |
| Sonnet 5.5 | $0.00000 | $0.00129 |
| Haiku 4.5 | $0.00000 | $0.00064 |
Grade A, and why
084-Frank-AI风险管控工具 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.
What it actually says
Skill: Frank-AI风险管控工具
Profile
- Author: Frank
- Version: 1.0.0
- Language: 中文
- Category: 维度7 - AI项目专精
- Description: 识别AI项目的技术/数据/伦理/合规风险，生成风险应对预案
When to Use
AI项目评估和实施阶段
Input Requirements
- AI项目方案
- 应用场景
- 数据情况
Workflow
- 识别技术风险：模型精度/性能/可扩展性/技术债务
- 识别数据风险：数据质量/数据安全/数据偏见/数据合规
- 识别伦理风险：算法歧视/隐私侵犯/责任归属/社会影响
- 识别合规风险：算法备案/内容安全/数据出境/行业准入
- 识别运营风险：团队能力/成本超支/用户接受度/模型维护
- 评估风险等级（概率×影响）
- 制定风险应对预案
- 输出AI风险管控报告
Output Format
AI风险管控报告（含五维风险+风险矩阵+应对预案+监控机制）
Output Template
风险编号 | 风险类别 | 风险描述 | 概率 | 影响 | 等级 | 应对预案 | 监控指标
Example
| 字段 | 内容 |
|---|---|
| R002 | 数据风险 |
Constraints
- 风险识别基于实际情况
- 应对预案可操作
- 监控机制可执行
Quality Criteria
- 风险维度覆盖完整
- 评估客观
- 预案有效
Applicable Scenarios
- G端政府项目: 部分适用
- B端企业项目: 部分适用
- 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7: AI项目专精 | 编号: 084 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 · 90 lines · 0 tokens per session scan A d48654059d34
084-Frank-AI风险管控工具 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 645 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 2026-09-03.
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