Agent skill

Job Ok

by GresonKwan in GresonKwan/JobOK

A skill your agent uses when helping a Chinese job seeker, especially students, interns, or early-career users, prepare job applications with an agent without fabricating experience, auto-submitting…

MITAuto-check passedBusiness, Finance & HR

Install Job Ok

skills CLI
$ npx skills add GresonKwan/JobOK --skill job-ok -a claude-code

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

GitHub CLI
$ gh skill install GresonKwan/JobOK job-ok --agent claude-code

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

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

Facts

Skill name
job-ok
GitHub stars
411
Token cost
~745 tokens
SKILL.md length
98 words
Files
40 (incl. scripts, references, assets)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when helping a Chinese job seeker, especially students, interns, or early-career users, prepare job applications with an agent without fabricating experience, auto-submitting…

  • Works in 9 steps: 先 Intake。… → 提取真实经历。 把简历和用户回答整理到… → 挖掘优势。 每个优势都必须走完 证据 -> 行为 -> 能力 ->… → …
  • Helping a Chinese job seeker
  • SKILL.md covers 使用边界, 本地案例目录, 工作流 and 辅助脚本, plus 1 more section
  • Calls python3

What it does

Job Ok is an agent skill from GresonKwan/JobOK. Use when helping a Chinese job seeker, especially students, interns, or early-career users, prepare job applications with an agent without fabricating experience, auto-submitting applications, scraping hiring platforms, or promising offers.

Its SKILL.md is about 750 tokens, which your agent loads only when the skill is triggered. The skill folder holds 42 other files, including scripts, reference files and assets (for example `CHANGELOG.md`, `CONTRIBUTING.md` and `README.md`).

It sits in Business, Finance & HR, covering Web scraping and Job search and resumes. The repository describes itself as: Job OK: 面向中文求职者的证据驱动求职 Agent Skill,支持优势挖掘、岗位匹配、简历优化、面试训练和投递跟踪。 The licence is MIT.

When your agent uses it

  • Helping a Chinese job seeker
  • Especially students
  • Early-career users
  • Prepare job applications with an agent without fabricating experience

Example prompts

  • “/job-ok”

Requirements

  • Python 3

Workflow steps

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

  1. 先 Intake。 收集简历、目标城市、目标岗位、教育背景、项目/实习经历、限制条件、排除岗位、偏好行业和风险备注。核心信息不足时先追问,不急着推荐岗位或改简历。参考 references/intake-flow.md。
  2. 提取真实经历。 把简历和用户回答整理到 experience-assets.md。可用 scripts/extract_resume_text.py 提取 .pdf、.docx、.txt、.md 简历文本。
  3. 挖掘优势。 每个优势都必须走完 证据 -> 行为 -> 能力 -> 岗位信号。参考 references/strength-taxonomy.md,在 strengths.md 记录可信度和缺失证据。
  4. 生成岗位假设。 输出 3-5 个目标岗位簇到 target-roles.csv。参考 references/job-matching-rubric.md,写清匹配证据、差距、30 天补强动作和适合公司类型。
  5. 整理真实 JD。 只接受用户提供的岗位链接、截图、复制 JD、CSV 导出、Markdown 表格或浏览器可见页面。用 scripts/normalize_jobs.py 生成 jobs.jsonl。使用平台资料前先读…
  6. 评分和短名单。 用 scripts/score_job_matches.py 做确定性初筛。分数只用于 triage,不代表真实录取概率。低分岗位进入观察池,不进入投递列表。
  7. 优化简历。 参考 references/resume-rubric.md。每条建议必须能回到真实经历。输出 resume-review.md,并在 resume-versions/ 记录不同岗位版本。
  8. 训练面试表达。 参考 references/interview-training.md。一次只问一个问题,等待用户回答,再追问和复盘。首版只处理文本或语音转写稿。
  9. 跟踪和复盘。 每次投递、回复、面试、拒信或新增 JD 后,更新 application-tracker.csv 和 review-log.md。

What it can do on your machine

Read from SKILL.md and the folder at commit c5da0c6. 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/, which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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

Job Ok loads about 745 tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 62 tokens; SKILL.md has 98 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~62
When it runs · the whole SKILL.md, loaded when a task matches
~745
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.2k

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 GresonKwan/JobOK at commit c5da0c6, republished under its MIT licence (© GresonKwan). 98 words, ~745 tokens.

Download SKILL.mdSave it as .claude/skills/job-ok/SKILL.md (or your agent's skills folder). This skill also uses 39 other files; get the full folder from GitHub.
name
job-ok
description
Use when helping a Chinese job seeker, especially students, interns, or early-career users, prepare job applications with an agent without fabricating experience, auto-submitting applications, scraping hiring platforms, or promising offers.

Job OK

Job OK 是一个面向中文求职者的本地求职 Skill。它帮助学生、实习生和早期职场人把真实经历整理成可追溯的求职证据,再用于岗位匹配、简历优化、投递跟踪和面试表达训练。

核心原则:先证据,后结论;先岗位匹配,后简历改写;用户手动确认任何外部投递动作。

使用边界

  • 默认使用中文,除非用户要求其他语言。
  • 默认把简历、联系方式、截图、聊天记录等敏感材料保留在本地。
  • 输出中区分 fact、assumption、inference、user_preference。
  • 不编造学历、实习、项目、奖项、指标、证书、技能或公司经历。
  • 不承诺面试、offer、薪资结果或平台曝光。
  • 不自动投递、不自动私信 HR、不绕过登录、不批量爬取招聘平台。
  • 不用于企业侧招聘、候选人排名或人事决策。

本地案例目录

每服务一个求职者,创建或复用:

text
job-search-cases/<yyyy-mm-dd-user-slug>/
├── brief.yaml
├── raw/
│   ├── resume/
│   └── job-posts/
├── profile.yaml
├── experience-assets.md
├── strengths.md
├── target-roles.csv
├── jobs.jsonl
├── job-matches.csv
├── resume-review.md
├── resume-versions/
├── interview-story-bank.md
├── interview-practice.md
├── application-tracker.csv
└── review-log.md

优先从 assets/templates/ 复制模板到案例目录,再开始分析。

工作流

  1. 先 Intake。 收集简历、目标城市、目标岗位、教育背景、项目/实习经历、限制条件、排除岗位、偏好行业和风险备注。核心信息不足时先追问,不急着推荐岗位或改简历。参考 references/intake-flow.md。
  2. 提取真实经历。 把简历和用户回答整理到 experience-assets.md。可用 scripts/extract_resume_text.py 提取 .pdf、.docx、.txt、.md 简历文本。
  3. 挖掘优势。 每个优势都必须走完 证据 -> 行为 -> 能力 -> 岗位信号。参考 references/strength-taxonomy.md,在 strengths.md 记录可信度和缺失证据。
  4. 生成岗位假设。 输出 3-5 个目标岗位簇到 target-roles.csv。参考 references/job-matching-rubric.md,写清匹配证据、差距、30 天补强动作和适合公司类型。
  5. 整理真实 JD。 只接受用户提供的岗位链接、截图、复制 JD、CSV 导出、Markdown 表格或浏览器可见页面。用 scripts/normalize_jobs.py 生成 jobs.jsonl。使用平台资料前先读 references/platform-boundaries.md。
  6. 评分和短名单。 用 scripts/score_job_matches.py 做确定性初筛。分数只用于 triage,不代表真实录取概率。低分岗位进入观察池,不进入投递列表。
  7. 优化简历。 参考 references/resume-rubric.md。每条建议必须能回到真实经历。输出 resume-review.md,并在 resume-versions/ 记录不同岗位版本。
  8. 训练面试表达。 参考 references/interview-training.md。一次只问一个问题,等待用户回答,再追问和复盘。首版只处理文本或语音转写稿。
  9. 跟踪和复盘。 每次投递、回复、面试、拒信或新增 JD 后,更新 application-tracker.csv 和 review-log.md。

辅助脚本

bash
python3 .agents/skills/job-ok/scripts/extract_resume_text.py \
  --input job-search-cases/<case>/raw/resume/resume.pdf \
  --output job-search-cases/<case>/raw/resume/resume.txt

python3 .agents/skills/job-ok/scripts/normalize_jobs.py \
  --input job-search-cases/<case>/raw/job-posts/jobs.md \
  --output job-search-cases/<case>/jobs.jsonl \
  --source-type user_paste

python3 .agents/skills/job-ok/scripts/score_job_matches.py \
  --profile job-search-cases/<case>/profile.yaml \
  --strengths job-search-cases/<case>/strengths.md \
  --jobs job-search-cases/<case>/jobs.jsonl \
  --output job-search-cases/<case>/job-matches.csv

输出标准

  • 优势挖掘:写明证据、可信度、岗位信号和缺失证据。
  • 岗位建议:同时写为什么投、为什么不投、简历重点和下一步用户动作。
  • 简历修改:输出建议,不输出不可验证的最终表述;缺证据内容标记为 needs_proof。
  • 面试训练:检查结构、具体性、证据、岗位相关性、风险表达和可追问性。
  • 外部动作:结尾使用“用户手动确认后再执行”,除非用户报告完成,否则不要写“已投递”。

© GresonKwan, 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 39 other files (scripts, references, assets) in the repository root of GresonKwan/JobOK.

  • SKILL.md
  • .gitignore
  • CHANGELOG.md
  • CONTRIBUTING.md
  • LICENSE
  • README.md
  • agents/openai.yaml
  • assets/templates/application-tracker.csv
  • assets/templates/brief.yaml
  • assets/templates/experience-assets.md
  • assets/templates/interview-practice.md
  • assets/templates/interview-story-bank.md
  • assets/templates/profile.yaml
  • assets/templates/review-log.md
  • assets/templates/sample-jobs.md
  • assets/templates/strengths.md
  • assets/templates/target-roles.csv
  • docs
  • … and 22 more

Open the folder on GitHubat commit c5da0c6

Compare with similar skills

Job Ok next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Job Ok compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Job Ok this skillGresonKwan/JobOK411—~745Automated safety check: PassMIT
Job Posting ScraperMadsLorentzen/ai-job-search45k1 repos~5.7kAutomated safety check: PassMIT
Career-Ops Apify Job Sourcecareer-ops-hq/career-ops74k—~246Automated safety check: NotesMIT
Indeed Job Searchbrowser-act/skills6.1k—~2.7kAutomated safety check: PassMIT
Linkedin Jobs Searchbrowser-act/skills6.1k—~2.5kAutomated safety check: PassMIT
Internship Project Preparation ToolLiuMengxuan04/shushu-internship-tool2.1k—~2.3kAutomated safety check: PassCustom licence

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Questions about Job Ok

What does Job Ok do?

A skill your agent uses when helping a Chinese job seeker, especially students, interns, or early-career users, prepare job applications with an agent without fabricating experience, auto-submitting…. Job Ok is an agent skill from GresonKwan/JobOK. Use when helping a Chinese job seeker, especially students, interns, or early-career users, prepare job applications with an agent without fabricating experience, auto-submitting applications, scraping hiring platforms, or promising offers.

When should I use Job Ok?

Job Ok fits situations like: helping a Chinese job seeker; especially students; early-career users; prepare job applications with an agent without fabricating experience.

How do I install Job Ok in Claude Code?

Run `npx skills add GresonKwan/JobOK --skill job-ok -a claude-code`. Or copy the skill folder (the GresonKwan/JobOK repository) into .claude/skills/job-ok in your project. Claude Code loads it when a task matches its description.

How do I install Job Ok in Codex?

Run `npx skills add GresonKwan/JobOK --skill job-ok -a codex`. Or copy the skill folder (the GresonKwan/JobOK repository) into .agents/skills/job-ok in your project. Codex loads it when a task matches its description.

Can I use Job Ok 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 GresonKwan/JobOK --skill job-ok -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/job-ok, .gemini/skills/job-ok, .github/skills/job-ok and .opencode/skills/job-ok in your project.

What does Job Ok need to run?

Going by SKILL.md and its folder, Job Ok needs the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Job Ok 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 Job Ok 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 Job Ok use?

Job Ok is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Job Ok use?

About 745 tokens (SKILL.md is roughly 3k 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 2.5k tokens, read only when the agent opens those files.

What are the alternatives to Job Ok?

Skills that share tags, products or a category with Job Ok: Job Posting Scraper (MadsLorentzen/ai-job-search, 45k stars), Career-Ops Apify Job Source (career-ops-hq/career-ops, 74k stars), Indeed Job Search (browser-act/skills, 6.1k stars) and Linkedin Jobs Search (browser-act/skills, 6.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Job Ok?

GresonKwan (a GitHub user) maintains it in GresonKwan/JobOK, which has 411 GitHub stars. The repository was last updated on June 18, 2026.

Source: GresonKwan/JobOK on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.