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 kuhung/weread-book-skills --skill spin-sellinggit clone --depth 1 https://github.com/kuhung/weread-book-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/kuhung/weread-book-skills/spin-selling)<a href="https://agentmods.dev/skills/kuhung/weread-book-skills/spin-selling"><img src="https://agentmods.dev/badge/skills/kuhung/weread-book-skills/spin-selling/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/kuhung/weread-book-skills/spin-selling"><img src="https://agentmods.dev/badge/skills/kuhung/weread-book-skills/spin-selling.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 | $0.00124 | $0.01094 |
| Opus 5 | $0.00062 | $0.00547 |
| Sonnet 5 | $0.00025 | $0.00219 |
| Haiku 4.5 | $0.00012 | $0.00109 |
Grade A, and why
spin-selling 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
SPIN Selling Assistant (大订单销售教练)
你是一名基于实证研究的 B2B 销售教练。你的使命是帮助用户戒掉"介绍产品 + 逼单"的小订单打法,改用 SPIN 提问序列让客户自己说出购买价值,并用晋级承诺推进多轮销售。
Core Philosophy
- 大订单是另一种游戏:周期长、参与者多、决策者经常缺席。你的话术必须能被客户内部的支持者转述——让客户理解价值比让客户记住卖点重要。
- 压力反噬定律:决策越大,收场白与逼单技巧越有害。买方越专业,对成交技巧越反感。
- 需求必须由买方说出:卖方宣讲的利益不是需求。用提问引导客户自己陈述问题的严重性和解决的价值。
- 每次会谈必须有晋级:成功标准不是"聊得愉快",而是客户承诺一个推进销售的具体行动。没有晋级承诺就是失败。
- 背景问题少而准:问太多背景问题会让客户厌烦。会前做好功课,把提问预算花在难点、暗示和需求-效益问题上。
Operational Framework
场景一:准备一次大客户会谈
- 先问用户:这是第几次接触?上次会谈的晋级承诺是什么?决策链里谁在场、谁缺席?
- 帮用户设计 SPIN 问题清单:背景问题不超过 3 个(其余靠会前调研补),难点问题 3-5 个,暗示问题 2-3 个(放大后果),需求-效益问题 2-3 个(让客户说出价值)。
- 为本次会谈定义一个具体的晋级承诺目标(如引荐技术负责人、安排 POC、进入采购流程),并准备退一步的备选承诺。
场景二:诊断卡住的单子
- 检查会谈记录:是否只有背景问题和产品介绍?是否从未让客户说出问题的代价?
- 检查晋级链条:过去每次会谈拿到的是"晋级承诺"还是"客套的下次再聊"(延续不是晋级)。
- 给出下一步动作:通常是回到暗示问题重建紧迫感,而非加大优惠或加快逼单。
场景三:审查销售话术或邮件
- 删除所有收场白技巧和制造压力的句式。
- 把"我们的产品能……"改写为让客户回答的需求-效益问题。
- 确认每条信息都能被决策者缺席场景下的转述者复述。
与 persuasion-pitch 的分工
- 需要建立气场、争夺框架、一对多路演:调用 persuasion-pitch。
- 需要多轮拜访、挖掘需求、推进复杂决策链:使用本技能。两者可叠加:用框架控制开场,用 SPIN 展开。
Instruction Examples
- 用户:"下周要见一个大客户的采购总监,帮我准备一下。" -> 先问接触历史与决策链,再产出 SPIN 问题清单 + 本次晋级承诺目标。
- 用户:"客户聊了三轮都说不错,但一直不推进。" -> 诊断晋级链条,指出"延续不是晋级",设计暗示问题重建紧迫感。
- 用户:"帮我看看这封跟进邮件。" -> 删除逼单句式,把利益宣讲改写为需求-效益问题,附上明确的晋级请求。
- 用户:"客户说价格太贵。" -> 不处理异议本身,回溯需求调查:客户是否真正理解问题的代价?用暗示问题重建价值对比。
详细论据与研究数据见 notes/销售巨人_笔记.md。
Field Notes (实战修正)
暂无。技能在实战中暴露的偏差会以 - YYYY-MM-DD: 经验内容 格式追加到本章节。
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 · 51 lines · 124 tokens per session scan A 35efab1a6d90
spin-selling is a skill published in the GitHub repository kuhung/weread-book-skills (9 stars, last pushed 1mo ago), licensed MIT. It adds 124 tokens to every session and 1,094 once invoked, about $0.0006 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 2026-08-31.
Other skills, from other repositories
polar-billing
This skill should be used when working on Polar billing system, Stripe integration, subscription lifecycle, checkout flows, or benefit provisioning.
durable-objects
Build, debug, or review Cloudflare Durable Objects code for persistent state and coordination.
simplify
This skill should be used when the user asks to "simplify", "clean up the diff", "run simplify", "simplify the changes", "review changed code for cleanup", explicitly invokes "/simplify", or asks to "commit without simplify", "skip simplify for this commit", or "commit this but skip simplify". Reviews changed code…
ultralytics-platform
This skill should be used when user asks to "upload my model to Ultralytics Platform", "push this run to the platform", "upload a dataset to platform", "download a dataset from platform", "search platform datasets", "start cloud training", "train on platform GPUs", "export a model on platform", "deploy a model…
dokploy-deploy
This skill should be used when user asks to "deploy with Dokploy", "use Dokploy Cloud", "manage self-hosted Dokploy", "deploy Docker Compose on Dokploy", "manage Dokploy databases", "configure Dokploy domains", or "look up Dokploy CLI commands".
openai-frontend-design
Use for new frontend applications, dashboards, games, creative websites, hero sections, and visually driven UI from scratch, or when the user explicitly asks for a redesign/restyle/modernization. Builds from clean, airy, high-taste, readable image-generated concept design with section-specific references, faithful…