write-resume

write-resume is a skill for Codex from asherzj/ashers-agent-skills. It costs 82 tokens per session (4,821 once invoked), scanned A, original, MIT.

A resume and CV writing workflow for turning real work experience into concise, evidence-based application content.

In plain words
What is it for?
Use it to write or revise resumes, project bullet points, summaries, job-description matches, and applications for jobs, internships, promotions, or career changes.
Why use it?
It helps replace vague claims with concrete responsibilities, decisions, measurable results, and details that can be defended in an interview.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to write or revise resumes, project bullet points, summaries, job-description matches, and applications for jobs, internships, promotions, or career changes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/asherzj/ashers-agent-skills/write-resume
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 asherzj/ashers-agent-skills --skill write-resume
Clone the repo
git clone --depth 1 https://github.com/asherzj/ashers-agent-skills

Made for: 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 write-resume

README.md
[![agentmods](https://agentmods.dev/badge/skills/asherzj/ashers-agent-skills/write-resume/github.svg)](https://agentmods.dev/skills/asherzj/ashers-agent-skills/write-resume)
Your own site
<a href="https://agentmods.dev/skills/asherzj/ashers-agent-skills/write-resume"><img src="https://agentmods.dev/badge/skills/asherzj/ashers-agent-skills/write-resume/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 write-resume

Your own site · 80×15
<a href="https://agentmods.dev/skills/asherzj/ashers-agent-skills/write-resume"><img src="https://agentmods.dev/badge/skills/asherzj/ashers-agent-skills/write-resume.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 82 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,821 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 $0.00082 $0.04821
Opus 5.5 $0.00033 $0.01928
Sonnet 5.5 $0.00016 $0.00964
Haiku 4.5 $0.00008 $0.00482

Measured 1mo ago against content hash 3398c820f56c, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

write-resume 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 1mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/resume_pipeline.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.

career/write-resume/SKILL.md · 163 lines

How it starts

The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.

简历写作

目标

把原始经历转化为简洁、可信、能赢得面试机会的简历。把简历当作一份“决策材料”:每个部分都应该帮助读者判断“这个人值得进入面试”。

核心原则

  • 提供决策点:用事实支撑候选人值得继续推进。
  • 只在真实且可自证的前提下制造挑战点:强表达应该能引出面试问题,并且候选人答得出来。
  • 内容组织优先呈现最强证据,不机械复制模板中的示例内容;生成正式文件时,视觉和布局仍必须遵循“模板一致性”要求。
  • 用证据替代标签。不要只说“owner 意识强”,要通过范围、决策、取舍和结果展示 ownership。
  • 量化有决策价值的结果;没有可靠数字时,可以写清技术取舍、交付范围或团队工作方式的变化,不为了每条都有数字而添加弱指标。
  • 数值变化优先写同口径的“从 A 到 B”,并核对统计周期、样本范围和比较对象。只有终值时可客观陈述终值;只有有据可查的变化比例时保留比例及口径,不倒推未知基线。无法支持的变化结论改为已确认事实,关键缺口才追问。百分比与百分点必须区分,例如从 18% 到 24% 是提升 6 个百分点。
  • 区分个人贡献、系统规模与业务共同结果。读取双跑不等于双写,协作人数不等于直属团队,迁移零事故不等于整个平台零故障。日常与应急、规则发布与规划发布等指标不合并;不同版本口径不同,不能直接判断哪个结果更好。
  • 保持真实。可以优化表达,但不要编造事实、数字、职级或 ownership。资料不足时,使用待确认占位符、提出针对性问题,或说明可补充的证据类型。
  • 面向快速浏览写作:每条只表达一个重点,强信息前置。每个 bullet 尽量一行,一行是默认目标,两行是有理由的例外。 先删除重复背景、空泛修饰和次要实现细节,再收紧句式;只有继续压缩会丢失关键取舍、个人贡献、结果或必要指标范围时,才保留接近完整的两行。不同贡献可以拆条,但不把同一行动与结果机械拆开。不得缩小字号、压缩页边距、强制不换行或删去必要口径来凑一行。
  • 跨行重要文本块的末行不得只剩少量字词。检查范围至少包括 bullet、项目描述、角色说明、联系方式、目标岗位、项目标题和 Mock 标识;末行必须同时包含至少 8 个有效字符并占该文本块参考行宽至少 15%。固定流水线以 PDF 实际排版坐标强制检查,任一不满足即构建失败。
  • 非末页不得因显式分页、整体防拆或不合理的内容编排留下大块底部空白。固定流水线要求非末页最下方可见内容默认达到页面高度的 82%;未达到时先修复分页和内容流,不得靠缩小字体、压缩页边距或降低门禁掩盖问题。
  • 让简历 bullet 能匹配面试故事。简历给出论点和关键证据,面试展开细节。

工作流程

  1. 确定任务与交付形式

    • 先判断用户需要比较/诊断、整体改写、局部修改、针对 JD 定制,还是生成完整文件。比较或诊断只读原件,先给判断和证据,不自动改写或导出。
    • 比较版本时读取用户指定的实际附件,不用同名旧文件或可编辑稿代替;PDF 同时检查正文和所有相关页面的实际渲染。区分表达质量与事实核验,不凭排版或更大数字判优。
    • 局部修改继承最新已接受稿和偏好,只处理指定内容;不擅自恢复旧章节顺序、迁移术语或指标范围。
    • 用户指定的格式、模板和交付方式优先;修改现有简历时,默认保留原格式和有用的视觉设计。生成新的完整简历文件时,必须执行下方“模板一致性”规则。
    • 用户只需要内容优化时,直接在对话中交付,不额外生成文件。
  2. 引导用户提供信息

    • 生成完整简历或进行大范围重写前,读取 references/resume-intake.md,根据其中的采集表引导用户提供目标岗位、原始经历、证据、教育与技能、输出要求和隐私约束。
    • 先从用户已经提供的简历、JD、作品集、经历笔记和对话中提取信息,列出“已掌握的信息”和“仍影响成稿的关键缺口”;不要让用户重复填写已有内容。
    • 用户没有现成简历时,给出可直接复制填写的采集表。明确说明无需润色,可以提供零散事实;不知道、不适用或不愿披露的项目可分别标记为“待补充”“不适用”或“不披露”。
    • 局部诊断或改写只收集完成当前任务所需的信息,不要求用户填写完整采集表。
    • 优先一次性追问会改变岗位定位、内容取舍或强主张可信度的缺口。非关键缺口可以保留待确认占位符,不要以信息不完整为由阻塞可交付的草稿。
  3. 明确目标

    • 明确目标岗位、职级、行业、公司类型,以及简历主要面向真人阅读、ATS 系统,还是两者兼顾。
    • 如果有 JD,提取核心要求和必要关键词。
    • 如果目标未知,基于用户最强证据优化到最合理的目标岗位。
  4. 盘点证据

    • 收集工作经历、教育背景、项目、成果、指标、奖项、论文、开源项目、作品集和有意义的兴趣爱好。
    • 核对数值变化的基线、终值或已证实比例,以及统计周期和样本范围;只追问影响定位或强主张的缺口,其他内容使用已确认事实继续成稿。
    • 区分“项目发生了什么”和“候选人个人负责了什么”。
    • 区分原文记录、用户本轮确认、待核实与未来计划;用户确认可以作为来源,但不等于外部核验。生成或实质改写时,在用户材料目录维护简短来源说明:最终表述 | 来源/本轮确认 | 范围与待核实项;只读评价无需新建记录。

Read the full file on GitHub · 163 lines

Files

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.

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. 1mo ago Changed · +6 lines · -6 tokens per session 3398c820f56c
  2. 1mo ago First seen · 157 lines · 88 tokens per session scan A 3cd139ab5a4f

Subscribe to this mod's changes

write-resume is a skill published in the GitHub repository asherzj/ashers-agent-skills (3 stars, last pushed 1mo ago), licensed MIT. It adds 82 tokens to every session and 4,821 once invoked, about $0.0003 per session on Opus 5.5. 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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