resume-experience-template

resume-experience-template is a cursor rule for Cursor from KaichenCurry/TabNexus. It costs 43 tokens per session (4,317 once invoked), scanned A, original, MIT.

A rule set for turning Chinese work, internship, and project details into concise, fact-based résumé content tailored to a job description.

In plain words
What is it for?
Use it to create, rewrite, review, or tailor Chinese résumé entries and project descriptions.
Why use it?
It prevents unsupported claims by separating confirmed facts from assumptions and tracing each statement to evidence. It also helps focus each bullet on the problem, actions, and verified result.

Cursor rule for Cursor

Install

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.

agentmods
npx agentmods add rules/kaichencurry/tabnexus/resume-experience-template
Clone the repo
git clone --depth 1 https://github.com/KaichenCurry/TabNexus

Made for: Cursor.

Wrote 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.

agentmods badge for resume-experience-template

README.md
[![agentmods](https://agentmods.dev/badge/rules/kaichencurry/tabnexus/resume-experience-template.svg)](https://agentmods.dev/rules/kaichencurry/tabnexus/resume-experience-template)
Your own site
<a href="https://agentmods.dev/rules/kaichencurry/tabnexus/resume-experience-template"><img src="https://agentmods.dev/badge/rules/kaichencurry/tabnexus/resume-experience-template.svg" alt="Measured on agentmods" height="20"></a>
Per session 43 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,317 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00043 $0.04317
Opus 5 $0.00022 $0.02159
Sonnet 5 $0.00009 $0.00863
Haiku 4.5 $0.00004 $0.00432

Measured 4d ago against content hash 7235f723f562, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

resume-experience-template 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 4d 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.

exports/resume-experience-template-portable/cursor/.cursor/rules/resume-experience-template.mdc · 366 lines

How it starts

The opening of the file, as written. The whole thing — 366 lines — stays where its author put it; the contents beside it link to each section on GitHub.

中文简历经历优化规则

当用户要求生成、改写、审阅、补强或按 JD 定向调整中文简历时,遵循本规则。将每条经历写成一条可验证的价值证明:说明解决了什么问题、如何解决、产生了什么结果。真实性和可解释性高于“高级感”。

任务模式

先判断用户需要哪种结果,可组合执行:

  1. 从零生成:把口述、流水账或材料整理成简历经历。
  2. 改写优化:重写已有经历,压缩冗余并补齐逻辑。
  3. JD 定向:提取目标岗位的核心能力,以已有证据重新排序和措辞。
  4. 项目整理:输出项目名称、项目定位和 3–5 条简历描述。
  5. 简历审阅:检查结构、事实、表达、量化、商业价值和可面试性。
  6. 模板搭建:生成整份简历或单段经历的可填写模板。

核心工作流

1. 建立事实底稿

从用户材料中提取:

  • 公司/组织、部门、岗位、时间、地点;
  • 业务背景、目标、问题或约束;
  • 用户本人承担的角色、动作和责任边界;
  • 使用的方法、工具及实际使用程度;
  • 交付物、采用情况、决策影响和商业结果;
  • 规模、基线、对标、前后变化、时间周期;
  • 目标岗位/JD 及能够对应的事实证据。

将信息分为:

  • F1 用户明确确认:可直接写入成稿;
  • F2 可合理推断但未确认:只能用于提问或给出方向,不能写成事实;
  • F3 完全缺失:不得填充。

重点核验“主导/推动/负责”的责任边界、团队成果中的个人贡献、数据口径与比较基线、分析或方案的采用情况、商业结果的归因,以及工具和方法是否真实使用过。

不要把团队成果自动归为个人成果,不要把参与升级为主导,不要补造工具、产品能力、数据、对标或商业影响。不要把“提交报告”写成“驱动增长”,不要把“参加会议”写成“推动决策”,不要把“接触过工具”写成“熟练掌握”。

若材料只剩岗位名称,无法写出任何真实动作,先提出最多 3 个高价值问题。其他信息不足场景直接给出保守成稿,并在成稿后单列待补充证据,不要用臆测阻塞任务。

2. 确定定位与取舍

根据目标岗位和证据选择低重合的能力模块,不按每日事项罗列。专业能力约占 70%,沟通、推进等通用能力约占 30%。

优先保留:

  1. 与目标岗位匹配度高的能力;
  2. 工作量占比高、本人贡献清楚的事项;
  3. 有采用、决策或商业结果的高含金量产出。

删除重复、低价值、无法解释或与岗位无关的内容。不同经历尽量承担不同的能力证明。

存在多个合理方向时,明确区分:

  • 最稳方向:完全由现有事实支持,重点体现职责、方法、交付和已验证结果;
  • 最有竞争力方向:强调所有权、规模、采用或商业影响,但只有证据足够时才能写进成稿;否则说明需要补什么,不得先写成事实。

3. 搭建结果证据链

按以下顺序追溯价值,并写到最后一个已验证环节为止:

业务问题 → 分析/执行方法 → 关键发现或交付 → 被采用/落地 → 业务结果

结果层级从高到低:

  1. L4 商业结果:收入、成本、转化、留存、风险损失、订单等;
  2. L3 落地/决策结果:方案采纳、流程上线、覆盖团队、决策依据;
  3. L2 效率/质量结果:周期缩短、准确率提升、错误减少、自动化;
  4. L1 交付结果:报告、模型、方案、材料、数据库;
  5. L0 职责描述:仅说明做过什么。

优先使用最高且已获事实支持的层级,不得从 L1 跳写为 L3/L4。没有业务结果时,用真实交付、覆盖范围和使用去向收束。

仅使用有来源的数据。近似值只有在用户确认可用且能解释口径后,才使用“约”“近”等限定词。对标必须说明基线,例如目标值、改版前、同期、团队平均或有来源的同行口径。

若只确认报告被负责人阅读,写“供负责人评审/决策参考”,不要写“驱动战略调整”。若商业结果受多因素影响,使用“支持、助力、贡献于”等准确措辞,并能解释个人贡献。

4. 撰写经历

先写一句职责概括,再按能力模块写 Bullet Point:

  • 最新或最重要经历写 3–4 条,不超过 4 条;早期或低相关经历可写 2 条;
  • 项目经历写 3–5 条;
  • 每条使用“有力动词 + 具体动作/方法 + 已验证结果”;
  • 尽量形成“问题—方法—结果”闭环,一句话只证明一个核心能力;
  • 把工具嵌入业务场景,写清使用程度、处理对象和支持的结果;
  • 使用准确的所有权动词:主导、负责、搭建、推动、产出、优化、识别、拆解、验证;动词强度必须与事实一致;
  • 使用易懂、具体、可追问的语言,删除黑话、中英混杂、长难句和主观评价。

不要机械统一句式,不要强行给每条添加夸张数字。没有数字时,优先写范围、交付和真实应用。

可参考以下骨架,但优先自然表达:

  • 负责/主导【业务问题或目标】,通过【方法/工具/关键动作】,实现/形成【结果】。
  • 针对【问题】,搭建/拆解【方法】,识别【发现】,推动/支持【已验证应用或结果】。
  • 为解决【问题】,使用【工具的具体功能】处理【规模/对象】,产出【交付】,用于【真实场景】。

Read the full file on GitHub · 366 lines

Changes

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.

  1. 4d ago First seen · 366 lines · 43 tokens per session scan A 7235f723f562

Subscribe to this mod's changes

resume-experience-template is a cursor rule published in the GitHub repository KaichenCurry/TabNexus (29 stars, last pushed 16d ago), licensed MIT. It adds 43 tokens to every session and 4,317 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.