Jd analyzer
AI agent toolkit for Korean job applications, from resume evidence to tailored cover letters and interview prep
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Analyze a job description, hiring post, or recruitment page for role requirements, evaluation criteria, keywords, risks, and resume or cover letter angles. Use when the user provides a JD URL/text, asks what a company is looking for, wants JD-resume gap analysis, or needs inputs for a tailored cover letter.
SKILL.md
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JD Analyzer
Use this skill to convert a hiring post into practical selection criteria.
Trigger
Use this skill when the user provides a JD URL, pasted hiring post, normalized job record, or hiring notes that need Korean-market role analysis.
Do Not Trigger
Do not use this skill to draft cover letters, invent missing JD requirements, or analyze company culture pages that are not part of the hiring post.
Autonomy Level
DoF: MEDIUM
Separate deterministic parsing from conservative inference. Label every inferred evaluation criterion as inferred.
Permitted inferences:
- Hidden evaluation criteria that follow directly from explicit duties, tools, seniority, or hiring process language.
- Likely resume evidence categories needed to answer the JD.
Prohibited inferences:
- Do not add requirements absent from the JD or role context.
- Do not treat inferred criteria as explicit facts.
Input Contract
Required context:
- JD URL, JD text, normalized job record, or hiring-post notes.
Optional context:
resume.mdfor gap mapping.- Cover letter questions and length limits.
Required parameters:
source: URL, text, normalized job record, orunknown.
Outputs produced:
applications/<company-role>/jd-analysis.md
Workflow
- Accept a JD URL, pasted JD text, or mixed notes.
- Parse deterministic facts only:
- source URL or source type
- accessed date when browsing or checking a live posting
- company
- role
- seniority
- deadline
- required documents
- cover letter questions and length limits
- Analyze explicit requirements and inferred evaluation criteria in separate sections.
- Gap map the JD against
resume.mdwhen resume evidence is available. - Identify the likely evidence needed from
resume.md. - Mark gaps where the resume evidence appears weak or missing.
- Keep inference conservative. Label inferred criteria as inferred.
Output
Use this structure:
## JD Analysis
- Company:
- Source:
- Accessed Date:
- Role:
- Career Level:
- Main Responsibilities:
- Must-Have:
- Nice-To-Have:
- Hidden Evaluation Criteria:
- Resume Keywords:
- Cover Letter Angles:
- Risk/Gaps:
- Unknown Or Unverified Fields:
- Questions To Ask:
New Grad vs Experienced
- For new grads, look for learning ability, project relevance, tool familiarity, collaboration, and job motivation.
- For experienced candidates, look for role scope, measurable impact, domain depth, stakeholder work, and repeatable contribution.
Fallback
If the JD is vague, ask for the target role, company, and any available posting text. Do not create requirements that are not in the JD or reasonably inferable from the role.