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 036-frankgit 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/036-frank)<a href="https://agentmods.dev/skills/frank666199/frank-presales-skills/036-frank"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/036-frank/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/036-frank"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/036-frank.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 | $0.00629 |
| Opus 5 | $0.00000 | $0.00315 |
| Sonnet 5 | $0.00000 | $0.00126 |
| Haiku 4.5 | $0.00000 | $0.00063 |
Grade A, and why
036-Frank-项目效益分析工具 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 12d 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-项目效益分析工具
Profile
- Author: Frank
- Version: 1.0.0
- Language: 中文
- Category: 维度3 - 方案编制与文档优化
- Description: 用ROI模型量化项目经济/管理/社会效益，生成决策可用报告
When to Use
方案中需要效益分析章节，或领导决策需要效益论证
Input Requirements
- 项目投资额
- 运营成本数据
- 效益预期数据
Workflow
- 量化经济效益：降本金额/增效价值/创收预期
- 量化管理效益：流程优化/决策效率/风险降低
- 量化社会效益：服务提升/公众满意度/数据价值
- 构建ROI模型：投资回收期/净现值/内部收益率
- 进行敏感度分析（乐观/基准/保守三场景）
- 生成效益分析图表
- 输出效益分析报告
Output Format
效益分析报告（含三维度效益+ROI模型+敏感度分析+图表）
Output Template
效益类型 | 效益项 | 量化指标 | 年度金额 | 计算依据 | 置信度
Example
| 字段 | 内容 |
|---|---|
| 经济效益 | 人力成本节约 |
Constraints
- 效益数据有依据
- ROI模型参数合理
- 不夸大效益
Quality Criteria
- 效益维度完整
- ROI模型科学
- 敏感度分析覆盖关键变量
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3: 方案编制与文档优化 | 编号: 036 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.
- 12d ago First seen · 89 lines · 0 tokens per session scan A e9cb9707439f
036-Frank-项目效益分析工具 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 629 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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