084-Frank-AI风险管控工具

084-Frank-AI风险管控工具 is a skill for Claude Code, Codex from frank666199/frank-presales-skills. It costs 0 tokens per session (645 once invoked), scanned A, original, MIT.

An AI risk-assessment tool that reviews technical, data, ethical, legal, and operational risks and records their likelihood, impact, safeguards, and monitoring measures.

In plain words
What is it for?
Use it to create an AI risk matrix, rank risks by probability and impact, define response plans, and set indicators for ongoing monitoring.
Why use it?
It helps teams find problems such as poor model accuracy, biased data, privacy issues, compliance gaps, cost overruns, or weak user acceptance before they become failures.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code; mentions Codex.

Good fit Use it to create an AI risk matrix, rank risks by probability and impact, define response plans, and set indicators for ongoing monitoring.

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Install with agentmods
npx agentmods add skills/frank666199/frank-presales-skills/084-frank-ai
Install

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.

Any agent
npx skills add frank666199/frank-presales-skills --skill 084-frank-ai
Clone the repo
git clone --depth 1 https://github.com/frank666199/frank-presales-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for 084-Frank-AI风险管控工具

README.md
[![agentmods](https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/084-frank-ai/github.svg)](https://agentmods.dev/skills/frank666199/frank-presales-skills/084-frank-ai)
Your own site
<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.

agentmods 80×15 button for 084-Frank-AI风险管控工具

Your own site · 80×15
<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>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 645 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00645
Opus 5 $0.00000 $0.00322
Sonnet 5 $0.00000 $0.00129
Haiku 4.5 $0.00000 $0.00064

Measured 9d ago against content hash d48654059d34, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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 9d 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.

维度7-AI-Projects/084-Frank-AI风险管控工具/SKILL.md · 90 lines

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

  1. 识别技术风险:模型精度/性能/可扩展性/技术债务
  2. 识别数据风险:数据质量/数据安全/数据偏见/数据合规
  3. 识别伦理风险:算法歧视/隐私侵犯/责任归属/社会影响
  4. 识别合规风险:算法备案/内容安全/数据出境/行业准入
  5. 识别运营风险:团队能力/成本超支/用户接受度/模型维护
  6. 评估风险等级(概率×影响)
  7. 制定风险应对预案
  8. 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

Changes

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.

  1. 9d ago First seen · 90 lines · 0 tokens per session scan A d48654059d34

Subscribe to this mod's changes

084-Frank-AI风险管控工具 is a skill published in the GitHub repository frank666199/frank-presales-skills (11 stars, last pushed 2mo 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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