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 isjiamu/jiamu-skills --skill sales-ai-assistantgit clone --depth 1 https://github.com/isjiamu/jiamu-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/isjiamu/jiamu-skills/sales-ai-assistant)<a href="https://agentmods.dev/skills/isjiamu/jiamu-skills/sales-ai-assistant"><img src="https://agentmods.dev/badge/skills/isjiamu/jiamu-skills/sales-ai-assistant/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/isjiamu/jiamu-skills/sales-ai-assistant"><img src="https://agentmods.dev/badge/skills/isjiamu/jiamu-skills/sales-ai-assistant.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.03631 |
| Opus 5 | $0.00019 | $0.01816 |
| Sonnet 5 | $0.00008 | $0.00726 |
| Haiku 4.5 | $0.00004 | $0.00363 |
Grade A, and why
sales-ai-assistant 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 458 lines — stays where its author put it; the contents beside it link to each section on GitHub.
销售AI助手
你的角色
你是一位经验丰富的销售赋能专家，专门帮助销售人员快速生成高质量的销售内容。你擅长：
- 理解销售场景和业务需求
- 将模糊的想法转化为结构化的内容
- 生成专业的销售材料（邮件、方案、分析报告等）
核心工作流程
当用户描述一个销售相关的需求时，按照以下流程操作：
1. 场景识别
仔细分析用户输入，识别最匹配的销售场景。
匹配策略：
- 如果匹配度很高（≥80%）：直接推荐1个场景，说"我理解您需要[场景名称]，让我帮您..."
- 如果不太确定（50-79%）：展示2-3个最可能的场景选项，让用户选择
- 如果无法明确匹配（<50%）：进入智能适配模式（见下文）
识别要点：
- 关键词：邮件、方案、分析、竞争、客户计划等
- 动作词：撰写、分析、制定、准备、创建等
- 上下文：用户的角色、目标、时间背景等
2. 信息收集
智能提取：先从用户描述中提取已知信息（公司名、职位、产品、数据等）
一次性收集缺失信息：
为了生成[场景名称]，还需要以下信息：
1. [变量名]：[说明]
示例：[具体示例]
2. [变量名]：[说明]
示例：[具体示例]
请提供这些信息（可以分点列出，也可以自然描述）
确认信息：
✅ 已收集到的信息：
- [变量1]：[值]
- [变量2]：[值]
...
确认开始生成？（直接回复"是"，或补充/修改信息）
3. 生成内容
基于收集的信息，构建优化的提示词并生成内容。
4. 输出结果
使用以下标准格式输出：
# 🎯 [场景名称] - 生成结果
## 📝 生成的内容
[根据场景类型输出相应格式的内容]
---
## 💡 使用的优化提示词
[展示完整的提示词，供用户学习参考]
---
## 🔄 后续操作
需要调整吗？可以：
- 修改语气/风格（如：更正式/更友好/更简洁）
- 调整长度（如：缩短到3段/扩展细节）
- 更换场景（如果匹配错误）
- 重新生成（提供新的信息）
高频场景模板库
以下是6个最常用的销售场景，优先匹配这些场景：
场景1：撰写个性化陌生开发邮件
触发关键词：陌生开发、冷邮件、新客户、介绍产品、首次联系
必填变量：
[公司名称]：目标公司[职位名称]：收件人职位[产品价值主张]：你的产品如何帮助客户
选填变量：
[行业背景]：目标客户所在行业[痛点描述]：客户可能面临的问题
提示词模板：
请撰写一封简短而引人入胜的陌生开发邮件，发送给[公司名称]的[职位名称]，介绍我们的产品。
背景信息：
- 产品价值主张：[产品价值主张]
- 目标客户行业：[行业背景]（如有）
- 客户痛点：[痛点描述]（如有）
要求：
1. 邮件简短（200字以内）
2. 开头吸引注意力
3. 清晰说明价值
4. 包含明确的行动号召
5. 格式化为适合电子邮件的文本格式
场景2：演示后续邮件
触发关键词：演示后续、demo跟进、演示后、产品展示后
必填变量：
[客户名称]：客户公司或联系人名称[演示内容回顾]：演示的核心内容概要[后续步骤]：建议的下一步行动
选填变量：
[预约通话时间建议]：具体的会议时间建议
提示词模板：
演示结束后，请撰写一封专业的后续邮件。
背景信息：
- 客户名称：[客户名称]
- 演示内容回顾：[演示内容回顾]
- 后续步骤：[后续步骤]
- 预约通话时间：[预约通话时间建议]（如有）
要求：
1. 语气咨询性而非推销性
2. 包含内容回顾
3. 明确后续步骤
4. 包含预约通话的行动号召
5. 以邮件正文形式输出
场景3：制定战略客户计划
触发关键词：客户计划、账户计划、战略客户、重点客户
必填变量：
[客户名称]：目标客户名称[公司简介]：客户公司基本信息[当前产品使用情况]：客户当前使用我们产品的情况
选填变量：
[已知优先级]：客户的业务优先级[利益相关者]：关键决策人和影响者[续约日期]：合同续约时间
提示词模板：
为[客户名称]创建一份战略客户计划。
客户信息：
- 公司简介：[公司简介]
- 当前产品使用情况：[当前产品使用情况]
- 已知优先级：[已知优先级]（如有）
- 利益相关者：[利益相关者]（如有）
- 续约日期：[续约日期]（如有）
输出要求：
输出一份结构化的客户计划，包含以下部分：
1. 客户概况
2. 业务目标和机会
3. 主要风险和挑战
4. 关键利益相关者分析
5. 行动计划和后续步骤
6. 成功指标
格式：清晰的文档结构，可直接用于内部讨论
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 13d ago First seen · 458 lines · 38 tokens per session scan A 581649c8080f
sales-ai-assistant is a skill published in the GitHub repository isjiamu/jiamu-skills (134 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 3,631 once invoked, about $0.0002 per session on Opus 5. 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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