Jd analyzer
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. 한국어 요청도 포함합니다 - 채용공고 분석, 공고 분석, JD 분석, 직무기술서 분석, 자격요건, 우대사항, 이 공고 뭘 원하는지, 공고랑 내 경력 비교.From its SKILL.md
npx -y skills add kyoungbinkim/give-me-job --skill jd-analyzerAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 5 stars5 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
3.2 KB, as published. Nobody here has run it
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.
What ships with it: 1 file
1.0 KB alongside SKILL.md
examples/
- jd-analysis.md1.0 KB
Gives 0 of the 12 instructions most research analysis skills give
Counted across 1,213 of the 2,113 authors here whose files we hold, read 2026-09-06
- Cite sources for every important claimin 47 of 1213, across 38 files
- Separate facts from inferences and recommendationsin 21 of 1213, across 12 files
- Write findings to a markdown filein 19 of 1213
- Label every insight with a confidence levelin 18 of 1213, across 8 files
- Read product marketing context before asking questionsin 18 of 1213, across 8 files
- Rank themes by frequency and intensityin 16 of 1213, across 6 files
- Establish research mode before proceedingin 16 of 1213, across 6 files
- Segment survey responses by customer tier or tenurein 16 of 1213, across 6 files
- Categorize support tickets before analyzingin 16 of 1213, across 6 files
- Weight research sources from the last twelve monthsin 16 of 1213, across 6 files
- Use at least five data points per segmentin 15 of 1213, across 5 files
- Extract verbatim quotes for all research findingsin 15 of 1213, across 5 files
Said here and by no other author read
- Parse deterministic facts from the job description
- Separate explicit requirements from inferred evaluation criteria
- Label all inferred criteria as inferred
- Map resume gaps against job requirements
- Identify evidence needed from the resume
- Ask for missing details if the description is vague
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once.