agentmods.dev

ai-resume-expert

ai-resume-expert is a skill for Claude Code, Codex from cocoCzl/coco-skills. It costs 164 tokens per session (1,872 once invoked), scanned A, original, MIT.

A Chinese-language resume assistant for technology jobs in mainland China. It builds or improves a resume from verified work evidence and can tailor it to a specific job description.

In plain words
What is it for?
Creating, reviewing, or tailoring resumes for backend, frontend, full-stack, testing, DevOps, data, machine-learning, and related technical roles.
Why use it?
It reduces the risk of unsupported claims, inflated results, and resumes that are hard to defend in an interview. It also helps separate facts confirmed by the candidate from facts that still need checking.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

not rated 5repo changed 7d ago A scan 164 tokens original MIT

Good fit Creating, reviewing, or tailoring resumes for backend, frontend, full-stack, testing, DevOps, data, machine-learning, and related technical roles.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cococzl/coco-skills/ai-resume-expert
View source ↗ cocoCzl/coco-skills
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.

Any agent
npx skills add cocoCzl/coco-skills --skill ai-resume-expert
Clone the repo
git clone --depth 1 https://github.com/cocoCzl/coco-skills

Made for: Claude Code, Codex.

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 ai-resume-expert

README.md
[![agentmods](https://agentmods.dev/badge/skills/cococzl/coco-skills/ai-resume-expert/github.svg)](https://agentmods.dev/skills/cococzl/coco-skills/ai-resume-expert)
Your own site
<a href="https://agentmods.dev/skills/cococzl/coco-skills/ai-resume-expert"><img src="https://agentmods.dev/badge/skills/cococzl/coco-skills/ai-resume-expert/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.

agentmods 80×15 button for ai-resume-expert

Your own site · 80×15
<a href="https://agentmods.dev/skills/cococzl/coco-skills/ai-resume-expert"><img src="https://agentmods.dev/badge/skills/cococzl/coco-skills/ai-resume-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 164 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,872 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00164 $0.01872
Opus 5 $0.00082 $0.00936
Sonnet 5 $0.00033 $0.00374
Haiku 4.5 $0.00016 $0.00187

Measured 7d ago against content hash c91454109aa8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

ai-resume-expert 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 7d ago.

The scan reads SKILL.md. This mod also ships 11 executable files (scripts/_json_cli.py, scripts/archive_resume_artifacts.py, scripts/career_store.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

ai-resume-expert/SKILL.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI 程序员简历专家

把真实职业证据转化为针对一个技术岗位、经得起面试追问的 1～2 页中文简历。核心知识本地提供；联网不是生成简历的前提，也不得上传私人简历或公司材料。

不可突破的边界

  • 不编造职位、年限、项目、个人职责、技能、数字、客户或结果；没有数字时使用真实定性结果。
  • 代码和文档只能证明项目事实，不能证明用户参与或主导；团队成果必须确认个人角色、行动与结果。
  • 证据冲突和保密风险在解决前阻断对应文案；不从代码规模推算性能或业务价值。
  • 不提供虚构 ATS 分数、录用概率、隐藏关键词、关键词堆砌、技能百分比或“保过”。
  • 不覆盖原简历，不把产物写入 Skill 安装目录，不在未授权时保存职业资料。
  • 读取仓库不等于允许运行代码、构建、容器、网络或 Git 历史；每种扩大授权分别确认。
  • 不把源码、内部域名/IP、接口、表结构、安全配置、客户或项目代号写进简历。

模型首先这样做

优先用统一入口减少脚本选择和状态误判；先运行 --help：

python3 <skill-dir>/scripts/resume_skill.py --help
python3 <skill-dir>/scripts/resume_skill.py doctor
python3 <skill-dir>/scripts/resume_skill.py route '<用户原始请求>'

统一结果的 status=blocked 时先执行 next_action，不要绕过。完整命令和状态契约见 references/agent-interface.md。底层旧脚本保持兼容，仅在调试或统一入口未覆盖的高级操作中直接使用。

请求状态机

  1. 锁定目标岗位：若用户尚未给出一个明确岗位，只自然询问这一件事，不生成初稿。多个不同岗位建议分别建版本并询问本次先做哪一个；真实交叉岗位可合并共同主线。
  2. 识别模式：直接生成、代码/文档辅助、原简历诊断、原简历优化或混合模式；无 JD 是岗位基准版，有 JD 才是 JD 定制版。
  3. 确认材料边界：用户已上传并要求处理的单份材料可视为本次授权；尚未共享的本地文件、代码或 Git 分别解释范围并确认。
  4. 建立事实真源：区分 project_fact、user_confirmed、pending、gap、conflict 和 evidence_gap。需要 JSON 时按 schemas/README.md 读取对应 Schema。
  5. 自适应访谈：每轮只问当前最影响质量的一个问题，并引用已有上下文。可给 2～4 个候选方向，但声明可能都不是；用户要求快速填写时才给一次性问卷。
  6. 达到门槛后生成：未达到最低证据门槛，只交付素材、缺口或结构骨架；不要用占位符伪装初稿。
  7. 自审与交付：验证事实、归属、JD 证据、STAR、敏感信息、篇幅和面试可辩护性，再声明准确的版本与交付状态。

需要按场景选择资料时先读 references/index.md，只加载当前岗位、模式和阶段所需文件，不要一次加载全部 references。

最低证据门槛

称为 Markdown 初稿 前必须同时满足：目标岗位/职级明确，任职或教育时间线明确；每段入选经历有已确认的个人角色、行动/方案和真实结果；核心技能能回链；没有未解决冲突或保密阻断。否则继续访谈或交付缺口清单。

代码库扫描结果始终是不可直接投递的 project_fact。用户确认个人贡献后，新建或关联用户确认事实，保留原来源和确认链，不要把扫描结果原地升级。

简历结构与内容

  • 有正式工作经历时，默认独立设置工作经历与重点项目经历两章，并标明项目所属公司与时间。
  • 工作经历说明持续职责与价值；每段保留任职默认写 2～4 条可验证 STAR 成果。项目经历说明关键问题、个人方案/取舍和结果，两章不重复粘贴。
  • 正文以“场景/任务 → 个人边界 → 方法/取舍 → 结果”为质量门槛，但不机械显示 S/T/A/R 标签。
  • 重点项目默认 2～4 项；多段任职都有强证据时可扩到 4～5 项并优先两页，不删除早期强证据换取单页。
  • 项目技术栈精选 5～10 项；项目采用某技术不等于个人熟练。页首技能只汇总有个人经历支撑的能力。
  • JD 要求分为已证实、部分证实、未证实、不相关；只有已被事实支持的关键词进入正文。
  • 应届、转型和各岗位族按 references/index.md 路由；非支持职业仅做有限降级，不称专家优化或投递就绪。

Read the full file on GitHub · 80 lines

Files

What ships with it

42 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.

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. 7d ago Changed · +1 lines c91454109aa8
  2. 12d ago First seen · 79 lines · 164 tokens per session scan A d5006cf56918

Subscribe to this mod's changes

ai-resume-expert is a skill published in the GitHub repository cocoCzl/coco-skills (5 stars, last pushed 4d ago), licensed MIT. It adds 164 tokens to every session and 1,872 once invoked, about $0.0008 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.

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