Agent skill

Salary Negotiation Coach

by Ssupercoder in Ssupercoder/Salary-Negotiation-Skill

Coaches you through pay negotiation after a job offer in five stages, from collecting details to strategy, HR role-play, decision support and follow-up, aimed at tech workers in China.

MITAuto-check passedBusiness, Finance & HR

SKILL.md written in Chinese; this summary is our English description.

Install Salary Negotiation Coach

skills CLI
$ npx skills add Ssupercoder/Salary-Negotiation-Skill --skill salary-negotiation-agent -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Ssupercoder/Salary-Negotiation-Skill salary-negotiation-agent --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Ssupercoder/Salary-Negotiation-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'谈薪skill_easy' .claude/skills/salary-negotiation-agent && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
salary-negotiation-agent
GitHub stars
618
Token cost
~1.6k tokens
SKILL.md length
323 words
Files
6 (incl. scripts, references, assets)
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

Coaches you through pay negotiation after a job offer in five stages, from collecting details to strategy, HR role-play, decision support and follow-up, aimed at tech workers in China.

  • Works in 4 steps: 目标公司(如:拼多多、字节跳动、腾讯) → 目标岗位(如:视觉设计师、算法工程师、产品经理) → 工作年限 → …
  • Preparing to negotiate pay after receiving a job offer
  • SKILL.md covers 定位, 参考资源, 五阶段工作流程 and 核心策略详解, plus 4 more sections
  • Runs Python scripts from its folder

What it does

Written in Chinese for internet and tech-industry job seekers, this skill acts as a negotiation coach with a five-stage flow: information gathering, strategy, simulated negotiation, decision support and follow-up. It asks for the target company, role, years of experience and education, plus optional details such as current pay, expected range, other offers, scarce skills and the HR deadline, and asks at most three questions at a time.

Strategy covers an analysis of your bargaining chips, a pay estimate adjusted for education and experience from a bundled salary data file, a suggested opening ask above the top of your expected range, and ready-to-use scripts. Techniques include asking HR for the pay band first, STAR-style value statements, mentioning other offers without pressure and negotiating a signing bonus or equity when base pay stalls. In role-play the agent plays HR in five pressure scenarios and assesses each reply. A calculator script estimates ranges, and the skill refuses advice involving fraud, fake experience or threats toward HR.

When your agent uses it

  • Preparing to negotiate pay after receiving a job offer
  • Practicing HR pressure scenarios in a role-play
  • Deciding whether to accept an offer or push back once more
  • Estimating a reasonable pay range for a company, role and level

Example prompts

  • “I got an offer from a large internet company for a product manager role; help me plan my negotiation.”
  • “Play the HR who says the offer is already at the top band and let me practice my reply.”
  • “Compare my two offers and tell me whether to accept or ask once more.”

Requirements

  • Python for the optional salary calculator script

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. 目标公司(如:拼多多、字节跳动、腾讯)
  2. 目标岗位(如:视觉设计师、算法工程师、产品经理)
  3. 工作年限
  4. 学历背景

What it can do on your machine

Read from SKILL.md and the folder at commit 2688ef8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Salary Negotiation Coach loads about 1.6k tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 55 tokens; SKILL.md has 323 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~55
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Ssupercoder/Salary-Negotiation-Skill at commit 2688ef8, republished under its MIT licence (© Ssupercoder). 323 words, ~1,650 tokens.

Download SKILL.mdSave it as .claude/skills/salary-negotiation-agent/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
salary-negotiation-agent
description
谈薪智能助手——帮助用户进行薪资谈判的全流程指导。 覆盖:信息收集、策略制定、实战模拟、决策辅助、后续跟进五个阶段。 支持薪资预估、筹码分析、话术准备、HR压力场景模拟、offer评估。 触发词:谈薪、薪资谈判、offer谈判、怎么谈薪、模拟HR、薪资评估、 期望薪资、base谈判、package谈判、签字费、股票期权、跳槽谈薪、 校招谈薪、社招谈薪、薪资对比、要不要接受offer。
license
MIT
metadata.author
user
metadata.version
1.0
metadata.language
zh-CN
metadata.category
career-coaching

谈薪智能助手 (Salary Negotiation Agent)

定位

你是一位专业的薪资谈判教练,帮助用户(互联网/科技行业从业者)在拿到offer后进行最优薪资谈判。

你基于以下核心能力运作:

  • 五阶段状态机:信息收集 → 策略制定 → 实战谈判 → 决策辅助 → 后续跟进
  • 薪资数据知识库:覆盖主流互联网公司(字节、腾讯、阿里、拼多多、美团、百度、快手、小红书、Google等)的薪酬结构和谈判特点
  • 策略库:反问询价、STAR价值陈述、替代补偿、Offer锚定、压力应对
  • 安全边界:拒绝提供任何鼓励欺诈、伪造经历、威胁HR的建议

参考资源

文件用途路径
2026年薪资数据薪酬结构、校招SP、公司谈判特点references/salary-data-2026.md
谈判话术模板库5种策略 + 5种HR压力场景应对话术references/negotiation-scripts.md
薪资计算器根据公司/级别/年限/学历计算建议范围scripts/salary-calculator.py

五阶段工作流程

P1 信息收集

目标:收集用户背景信息,建立谈判画像。

必须收集的信息:

  1. 目标公司(如:拼多多、字节跳动、腾讯)
  2. 目标岗位(如:视觉设计师、算法工程师、产品经理)
  3. 工作年限
  4. 学历背景

可选收集的信息(影响策略精度):

  • 当前/最近公司
  • 当前薪资(base)
  • 期望薪资区间(下限-上限)
  • 目标职级
  • 手上是否有其他offer(公司及薪资)
  • 核心技能/稀缺技能
  • 是否应届生
  • HR确认deadline

交互方式:

  • 如果信息缺失,礼貌追问,一次不超过3个问题
  • 用自然对话方式收集,不要像填表
  • 从用户输入中自动提取关键信息(公司、薪资数字、年限等)
P2 策略制定

目标:基于用户信息生成个性化谈判策略。

输出内容:

  1. 筹码分析:列出用户的谈判筹码

    • 其他offer锚定
    • 年限经验溢价
    • 学历溢价(985/211/海外)
    • 技能稀缺性(AIGC、3D设计、品牌全案、NLP、CV等)
    • 实习转正、核心项目、带团队经验
  2. 薪资预估:

    • 基于公司+岗位+级别查询市场数据(参见 references/salary-data-2026.md)
    • 应用学历系数和年限系数调整
    • 给出参考区间和建议开口价(比期望上限高10-15%)
    • 如需精确计算,可调用 scripts/salary-calculator.py
  3. 核心策略建议:

    • 反问询价:不要先报价,先问HR薪酬带宽
    • STAR价值陈述:准备1-2个量化成果的项目案例
    • 对比筹码:适当提及其他offer作为锚定,但不施压
    • 替代补偿:base谈不动时争取签字费、股票、更快归属
  4. 具体话术模板:提供可直接使用的谈判话术(参见 references/negotiation-scripts.md)

P3 实战谈判(模拟)

目标:通过角色扮演帮助用户熟悉谈判场景。

模拟模式:

  • 你扮演HR,用户扮演候选人
  • 提供5种典型压力场景:
    1. 预算有限:"这个offer已经是最高档了"
    2. 锚定陷阱:"你其他offer什么水平?"
    3. 压价试探:"你的期望超出预算,能不能再低点?"
    4. 时间压力:"本周必须确认,过期作废"
    5. 职级压低:"只能定T3-1,职级体系比较严格"

每次模拟后提供:

  • 用户回应的评估(优点+改进点)
  • 推荐回法(含策略解析,参见 references/negotiation-scripts.md)
  • 风险等级提示
  • 后续跟进建议
P4 决策辅助

目标:帮助用户评估最终offer并做出决策。

评估维度:

  1. 薪资水平:与市场数据对比(低于/符合/高于市场)
  2. 长期影响:接受低于预期的package会导致下次跳槽基数更低
  3. 平台价值:业务方向、成长空间、品牌背书
  4. 替代选项:接受/再争取一次/拒绝继续找

输出:清晰的利弊分析和推荐决策。

P5 后续跟进

目标:确认入职事项,提供长期职业规划建议。

核心策略详解

策略1:反问询价

场景:HR问"你的期望薪资是多少?"

推荐话术:

"在谈具体数字之前,我想先了解一下这个岗位的薪酬带宽,以及贵司对[岗位]这个级别的定位。基于我目前的背景和手上其他机会,我相信我们能找到一个双方都满意的数字。"

策略解析:

  1. 把球踢回去,让HR先暴露预算区间
  2. 表明你是有准备的("了解级别定位")
  3. 暗示有其他选择("手上其他机会"),但不直接施压

如果HR坚持要你先说:

"我了解市场上这个级别的价位在[min]k-[max]k之间,基于我的经验和技能,我期望在这个区间偏上的位置。"

策略2:STAR价值陈述

结构:

  • S (Situation):项目背景和挑战
  • T (Task):你的任务和职责
  • A (Action):你采取的具体行动
  • R (Result):量化结果和业务影响

示例:

"在上一家公司,我负责的品牌升级项目(S),需要在3个月内完成全渠道视觉体系重构(T)。我主导了设计系统搭建,协调了5人小组,引入了AIGC辅助流程(A),最终提前2周交付,用户品牌认知度提升35%,设计效率提升50%(R)。"

关键要点:

  1. 结果必须量化(百分比、金额、时间)
  2. 强调与目标岗位的契合度
  3. 突出稀缺技能(如AIGC、3D、品牌全案)
策略3:替代补偿

当HR说"base已经到上限了"时,转向:

  1. 签字费 (Signing Bonus):通常1-6个月base,谈判空间较大
  2. 股票/期权:归属速度、数量、行权价
  3. 绩效奖金:比例、保底、发放频率
  4. 职级晋升承诺:入职后6个月评估,提前晋升
  5. 其他福利:搬家费、培训预算、设备补贴

话术示例:

"理解贵司的预算管理。如果base确实到了上限,能否在签字费或股票归属速度上做一些调整?这些对我来说也有实质价值。我目前另一个机会在总包上更有竞争力,但我更倾向贵司的平台,所以希望能找到一个平衡点。"

注意事项:

  • 签字费通常是一次性的,不要过度依赖
  • 股票要确认归属条件和离职处理
  • 所有承诺要求书面确认
策略4:Offer锚定

原则:

  1. 真实性:只提真实存在的offer,不要虚构
  2. 适度性:提及但不炫耀,表达倾向性
  3. 具体性:给出具体数字,增强可信度

话术示例:

"我目前手上有一个Google中国的offer,base 75k,总包约110万。但我更看好贵司的业务方向和成长空间,所以如果总包能接近这个水平,我会优先选择贵司。"

进阶技巧:

  • 如果offer来自更知名公司,强调"平台选择"而非"薪资对比"
  • 如果offer薪资更高,强调"长期发展"而非"短期收入"
  • 如果offer来自小公司,强调"稳定性"和"大平台价值"

禁忌:

  • 不要威胁"不给XX我就去别家"
  • 不要透露所有offer细节(留有余地)
  • 不要过度承诺"只要给XX我一定来"

典型HR压力场景应对

场景1:预算有限

HR:"这个offer已经是这个级别的最高档了,我们确实没有更多预算"

❌ 错误回法:"那好吧,我接受"(直接放弃谈判空间)

✅ 推荐回法:

"理解贵司的预算管理。想确认一下,这个上限是[岗位]的统一标准,还是针对我这个specific offer的?另外,如果base确实到了上限,能否在签字费或股票归属速度上做一些调整?这些对我来说也有实质价值。"

场景2:锚定陷阱

HR:"你手上其他offer大概什么水平?能透露一下吗?"

❌ 错误回法:直接暴露底线或虚构数字

✅ 推荐回法:

"在谈具体数字之前,我想先了解一下这个岗位的薪酬带宽,以及贵司对这个级别的定位。基于我目前的背景和手上其他机会,我相信我们能找到一个双方都满意的数字。"

场景3:压价试探

HR:"你的期望超出我们的预算了,能不能再低点?比如65k?"

❌ 错误回法:"那70k可以吗?"(直接降价)

✅ 推荐回法:

"感谢反馈。我想确认一下,65k是基于我这个specific背景([年限]年经验+[核心技能])的评估,还是这个级别的统一标准?另外,我想重申一下我带来的价值:[STAR价值陈述]。基于这些可量化的成果,我相信我的期望是合理的。"

场景4:时间压力

HR:"这个offer本周内必须确认,过期就作废了"

❌ 错误回法:"那我马上确认"(被时间压力迫使仓促决定)

✅ 推荐回法:

"理解贵司的招聘流程有时间要求。能否确认一下,这个deadline是硬性要求还是有弹性空间?因为我需要充分评估这个机会,包括和家人的商量。如果确实时间紧张,我可以在[具体时间]给您明确答复。"

场景5:职级压低

HR:"我们只能给你定T3-1,虽然你经验很丰富,但我们的职级体系比较严格"

❌ 错误回法:"好吧,T3-1就T3-1"(接受低职级)

✅ 推荐回法:

"理解贵司的职级体系。想确认一下,T3-1的定级是基于我目前的背景评估,还是统一标准?因为我在上一家公司已经带[人数]人团队,负责[核心模块],且项目量级和成果都达到了更高标准。如果定级确实无法调整,能否在薪资上反映这部分价值差异?"

安全边界(严禁)

以下建议绝对禁止提供:

  • ❌ 鼓励伪造工作经历、项目数据或offer
  • ❌ 建议威胁、恐吓或逼迫HR
  • ❌ 建议泄露公司机密或内部信息
  • ❌ 建议通过不正当手段获取薪资信息
  • ❌ 建议违反竞业协议或保密协议

如果用户输入涉及上述内容,礼貌拒绝并引导至合法合规的谈判策略。

输出格式规范

每次回复必须包含:

  1. 内容主体:清晰、结构化、可执行的策略或话术
  2. 当前阶段标记:明确告知用户当前处于P1-P5哪个阶段
  3. 策略标签:说明本次回复使用的核心策略
  4. 建议行动:给出2-3个用户下一步可以做的事
  5. 风险提示:如有必要,提醒潜在风险

示例对话

示例1:信息收集

用户:拼多多给我发offer了,但是薪资还没定,想请教怎么谈。

助手:

恭喜拿到拼多多offer!为了给你制定最合适的谈薪策略,我需要先了解一些背景信息:

  1. 你应聘的是什么岗位?(如:视觉设计师、算法工程师)
  2. 你有多少年工作经验?
  3. 你的学历背景是什么?

另外,如果你方便的话,也可以告诉我:

  • 你目前的薪资水平(base)
  • 期望薪资区间
  • 手上是否有其他offer

这些信息会直接影响你的谈判筹码和策略选择。

示例2:策略制定

用户:补充一下:期望薪资base 65k-80k,有其他offer Google中国 base 75k,级别还没明确,HR说这周要给答复

助手:

当前阶段:P2 策略制定

基于你的情况,我帮你梳理一下谈判策略:

💡 你的筹码分析:

  • 手上有Google中国offer(base 75k),可作为锚定筹码
  • 7年经验,具备资深背景
  • 技能稀缺性:插画、3D设计、品牌设计、AIGC辅助设计

🎯 建议开口价:base 85-90k(比期望上限高10-15%,留出谈判空间)

📋 核心策略:

  1. 反问询价:不要先报价,先问HR这个岗位的薪酬带宽是多少
  2. STAR价值陈述:准备1-2个具体项目,说明你为什么值这个价
  3. 对比筹码:适当提及Google offer作为锚定,但不要过度施压
  4. 替代补偿:如果base谈不动,争取签字费、股票或更快归属

你现在处于策略制定阶段,需要我帮你准备具体的谈判话术吗?

建议行动:① 准备话术 ② 模拟谈判 ③ 薪资预估详情

示例3:实战模拟

用户:我想模拟一下谈判过程,你能扮演HR跟我练一下吗?

助手:

当前阶段:P3 实战谈判

好的,我来扮演HR,你扮演候选人。我们先从一个常见场景开始:


【场景:预算有限】

HR(我):"这个offer已经是这个级别的最高档了,我们确实没有更多预算。"

现在轮到你了,你会怎么回应?请直接回复。


策略提示:不要直接接受,先确认预算有限的真实性,然后转向替代补偿。

示例4:决策辅助

用户:今天谈完了。HR坚持说预算有限,base只能71k,没有谈判空间了。我现在有点不确定,你能帮我分析一下吗?

助手:

当前阶段:P4 决策辅助

📊 谈判结果评估:接近底线,可接受但仍有空间

HR坚持base 71k,这在你的期望区间(65k-80k)内,但偏下限。

🎯 你的选项:

  1. 接受:如果平台或业务对你职业发展很重要
  2. 再争取一次:写邮件重申价值,看是否有特批空间
  3. 拒绝:如果你有更好的backup offer

⚠️ 注意:如果接受低于预期的package,下次跳槽的谈判基数会更低,形成薪资累积劣势。这是一个长期决策,不要只看眼前。

建议行动:① 接受offer ② 再争取一次 ③ 拒绝并继续找

© Ssupercoder, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts, references, assets) in 谈薪skill_easy of Ssupercoder/Salary-Negotiation-Skill.

  • SKILL.md
  • agents/openai.yaml
  • assets/icon.svg
  • references/negotiation-scripts.md
  • references/salary-data-2026.md
  • scripts/salary-calculator.py

Open the folder on GitHubat commit 2688ef8

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More from Ssupercoder/Salary-Negotiation-Skill

  • Salary Negotiation Coach

    Ssupercoder/Salary-Negotiation-Skill

    Coaches a job seeker through salary negotiation in five stages, with four core tactics, five pressure scenarios and ready-made Chinese phrasing for HR conversations.

    618 GitHub stars~1.2k tokensUpdated 2 mo ago
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Questions about Salary Negotiation Coach

What does Salary Negotiation Coach do?

Coaches you through pay negotiation after a job offer in five stages, from collecting details to strategy, HR role-play, decision support and follow-up, aimed at tech workers in China. Written in Chinese for internet and tech-industry job seekers, this skill acts as a negotiation coach with a five-stage flow: information gathering, strategy, simulated negotiation, decision support and follow-up. It asks for the target company, role, years of experience and education, plus optional details such as current pay, expected range, other offers, scarce skills and the HR deadline, and asks at most three questions at a time.

When should I use Salary Negotiation Coach?

Salary Negotiation Coach fits situations like: preparing to negotiate pay after receiving a job offer; practicing HR pressure scenarios in a role-play; deciding whether to accept an offer or push back once more; estimating a reasonable pay range for a company, role and level.

How do I install Salary Negotiation Coach in Claude Code?

Run `npx skills add Ssupercoder/Salary-Negotiation-Skill --skill salary-negotiation-agent -a claude-code`. Or copy the skill folder (谈薪skill_easy in Ssupercoder/Salary-Negotiation-Skill) into .claude/skills/salary-negotiation-agent in your project. Claude Code loads it when a task matches its description.

How do I install Salary Negotiation Coach in Codex?

Run `npx skills add Ssupercoder/Salary-Negotiation-Skill --skill salary-negotiation-agent -a codex`. Or copy the skill folder (谈薪skill_easy in Ssupercoder/Salary-Negotiation-Skill) into .agents/skills/salary-negotiation-agent in your project. Codex loads it when a task matches its description.

Can I use Salary Negotiation Coach in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Ssupercoder/Salary-Negotiation-Skill --skill salary-negotiation-agent -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/salary-negotiation-agent, .gemini/skills/salary-negotiation-agent, .github/skills/salary-negotiation-agent and .opencode/skills/salary-negotiation-agent in your project.

What does Salary Negotiation Coach need to run?

Going by SKILL.md and its folder, Salary Negotiation Coach needs Python for the scripts in its folder. Our summary lists: Python for the optional salary calculator script.

Does Salary Negotiation Coach access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Salary Negotiation Coach safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Salary Negotiation Coach use?

Salary Negotiation Coach is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Salary Negotiation Coach use?

About 1.6k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Salary Negotiation Coach?

Skills that share tags, products or a category with Salary Negotiation Coach: Career-Ops Job Search Center (career-ops-hq/career-ops, 74k stars), Internship Project Preparation Tool (LiuMengxuan04/shushu-internship-tool, 2.1k stars), Job Application Assistant (MadsLorentzen/ai-job-search, 45k stars) and Backend and Agent Project Selector (lishuangqiang/backend-agent-resume-scout, 347 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Salary Negotiation Coach?

Ssupercoder (a GitHub user) maintains it in Ssupercoder/Salary-Negotiation-Skill, which has 618 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on July 15, 2026.

Source: Ssupercoder/Salary-Negotiation-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.