Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Chasen-Liao/resume-skillsnpx agentmods add skills/chasen-liao/resume-skills/resume-workflowWrote 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/chasen-liao/resume-skills/resume-workflow)<a href="https://agentmods.dev/skills/chasen-liao/resume-skills/resume-workflow"><img src="https://agentmods.dev/badge/skills/chasen-liao/resume-skills/resume-workflow/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/chasen-liao/resume-skills/resume-workflow"><img src="https://agentmods.dev/badge/skills/chasen-liao/resume-skills/resume-workflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 37 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 49 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00079 | $0.01642 |
| Opus 5 | $0.00039 | $0.00821 |
| Sonnet 5 | $0.00016 | $0.00328 |
| Haiku 4.5 | $0.00008 | $0.00164 |
Grade A, and why
resume-workflow 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
简历工作流
将 resume-builder、JD 分析、定制、ATS 审计和版本管理串成一个流程；用户只需确认事实、改写和版本操作。
先读
读取 ../resume-builder/references/resume-contract.md、../resume-builder/references/content-writing.md 和 ../resume-builder/references/resume-facts.example.yaml。按当前阶段再读取对应 skill 的 SKILL.md，不要用本文件替代其事实、排版或验证约束。
0. 建立私有工作目录
- 将用户简历保存在项目目录外的本地私有目录，例如
<个人私有目录>/resume/；不要使用源码仓库中的示例或模板目录保存真实个人数据。 - 在用户确认导入/采访结果后，按
resume-facts.example.yaml创建resume-facts.yaml。它是母版和定制版的唯一事实源；未确认字段只能保留在该文件的待确认记录或分析报告中。 - 用户明确同意后，才在这个私有目录初始化、提交或推送 Git。默认仅建议本地 Git，不默认创建远程仓库。
1. 建立或更新母版
- 用户提供已有简历时，先调用
resume-builder的导入路径：提取内容、展示解析结果，并对模糊、冲突、可能过期或缺少证据的字段增量追问。 - 用户没有简历时，调用
resume-builder的采访路径。 - 只有用户确认的 claim 才写入
resume-facts.yaml并生成母版。若某条经历职责化、贡献不清或证据不足，可条件触发resume-bullet-writer；候选改写仍须用户确认。 - 事实确认后让用户选择视觉或 ATS-safe 输出模式；视觉模式再从六个模板中选择。
2. 针对 JD 定制
- 先调用
job-description-analyzer，将 JD 要求与resume-facts.yaml中的已确认 claim 对照，输出匹配点、真实缺口和定制优先级。 - 再调用
jd-tailorer，先展示变更预览；只有用户确认前置、改写和保留的缺口后，才生成tailored/<公司名>-<岗位>/中的定制版。
3. 审计与记录
-
调用
resume-ats-optimizer作为生成后的质量关卡。报告可直接修复的呈现问题与不能伪造的事实缺口；修复前取得用户确认。 -
母版或 JD 定制流程生成视觉 HTML 后，必须先完成 PDF 验证：用
resume-builder的渲染脚本完成溢出、PDF 单页/页面密度验证并生成 hash manifest。之后询问用户是否需要本地 Canvas 预览；Canvas 是可选微调步骤。Canvas 保存会让 manifest 失效，保存后必须重新渲染与验证：在 PDF 验证和 Canvas 启动前，先验收最终 HTML 的编辑字段协议：
data-resume-editor-template与data-resume-editor-version="1"必须位于<html>；data-resume-editor-id必须数量大于 0、唯一、语义化，并分别标在可独立编辑的文本元素上。禁止把编辑 ID 放在<html>、<body>、<main>、.page、.resume、header、footer、section、ul、ol、figure或包含多个板块/多个字段的容器上，也禁止用一个根容器 ID 代表整份简历。先运行可执行校验（失败即停止交付）：npx -p @chasen-liao/resume-skills@latest resume-skills validate "<最终_visual.html路径>"，重复直到输出“校验通过”。记录字段总数、重复 ID、容器误标 ID，以及个人信息 / 经历 bullet 字段检查结果；任何失败都必须停止交付并重新生成或拆分标记。powershell -NoProfile -ExecutionPolicy Bypass -File skills/resume-builder/scripts/render_resume.ps1 -HTML "<最终_visual.html路径>" -OutputPdf "<交付目录/自定义文件名.pdf>" python skills/resume-builder/scripts/validate_resume.py --html "<最终_visual.html路径>" --pdf "<交付目录/自定义文件名.pdf>" --mode visual --check-overflow --check-layout --min-fill-ratio 0.78 --manifest "<交付目录/自定义文件名.resume-manifest.json>" --renderer "[email protected]" --json
What ships with it
1 file 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.
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.
- 3d ago Changed · +3 lines 1e9bdd9f7734
- 12d ago First seen · 60 lines · 79 tokens per session scan A 4ed04858e7f4
resume-workflow is a skill published in the GitHub repository Chasen-Liao/resume-skills (28 stars, last pushed 4d ago), licensed MIT. It adds 79 tokens to every session and 1,642 once invoked, about $0.0004 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.
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