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 013-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/013-frank)<a href="https://agentmods.dev/skills/frank666199/frank-presales-skills/013-frank"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/013-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/013-frank"><img src="https://agentmods.dev/badge/skills/frank666199/frank-presales-skills/013-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 | $0.00654 |
| Opus 5 | $0.00000 | $0.00327 |
| Sonnet 5 | $0.00000 | $0.00131 |
| Haiku 4.5 | $0.00000 | $0.00065 |
Grade A, and why
013-Frank-售前线索甄别分级工具 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-售前线索甄别分级工具
Profile
- Author: Frank
- Version: 1.0.0
- Language: 中文
- Category: 维度2 - 售前全流程标准化
- Description: 快速筛选G/B端有效线索，划分项目优先级
When to Use
获取新项目线索后，第一时间评估跟进价值
Input Requirements
- 线索来源信息
- 客户基本信息
- 项目概况描述
Workflow
- 按BANT框架评估：Budget预算/Authority决策权/Need需求/Timeline时间表
- 结合MEDDPICC补充：Metrics量化指标/Economic Buyer经济买家/Decision Criteria决策标准/Decision Process决策流程/Identify Pain痛点/Champion内线/Competition竞争
- 评估线索真实性：信息完整度、客户主动度、预算明确度
- 划分优先级：A级(立即跟进)/B级(持续培育)/C级(暂缓)/D级(放弃)
- 输出线索评估报告和跟进建议
- 生成线索台账登记信息
Output Format
线索评估报告（含BANT+MEDDPICC评分、优先级、跟进建议）
Output Template
评估维度 | 信息/评分 | 依据 | 结论
Example
| 字段 | 内容 |
|---|---|
| Budget | 预算约200万(客户口述) |
Constraints
- 评估基于事实信息，不主观臆断
- 缺失信息标注'待确认'
- 优先级评估有据可查
Quality Criteria
- 评估维度完整
- 优先级判定合理
- 跟进建议具体可操作
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2: 售前全流程标准化 | 编号: 013 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 · 88 lines · 0 tokens per session scan A b2f3fce2c16a
013-Frank-售前线索甄别分级工具 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 654 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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