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cv-scorer

Score candidate CVs on a 100-point scale against a Job Description. Use this skill when the user wants to evaluate, score, rank, or screen candidate CVs/resumes against a JD. Also trigger when the user mentions 'review CV', 'screen resume', 'rate candidates', 'shortlist', or any context involving matching resumes to job requirements.

インストール方法を見る

含まれるファイル(6)

  • SKILL.md2.7 KB
  • README.md3.9 KB
  • README.vi.md5.0 KB
  • README.zh.md3.6 KB
  • references/output-format.md2.0 KB
  • references/scoring-rubric.md2.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

CV Scorer — Candidate CV Evaluation

This skill evaluates how well a candidate's CV matches a specific Job Description (JD), producing a structured score out of 100.

Workflow

Step 1: Identify Inputs

Two inputs are required:

  • Job Description (JD): The job posting with requirements, qualifications, and responsibilities
  • CV(s): One or more candidate CVs (markdown, text, or PDF)

If the user hasn't provided a JD, ask for it. If the JD is already available in context (e.g., a file on Drive or in the project directory), read it directly.

Reading PDF files: Use the /pdf skill to extract text from PDF CVs — it handles multi-page documents and formatted layouts reliably.

Step 2: Analyze the JD

Before scoring, extract from the JD:

  • Must-have skills vs nice-to-have skills
  • Experience requirements (years, seniority level, domain)
  • Education requirements
  • Special requirements (languages, certifications, travel, etc.)

Step 3: Score Against Rubric

Score each CV across 5 criteria using references/scoring-rubric.md:

CriterionWeightMax Points
JD Matching×330
Work Experience×2.525
Project & Impact×1.515
Education×1.515
CV Quality×1.515
Total100

Step 4: Output

Output JSON for each CV using the format in references/output-format.md.

Recommendation thresholds:

  • Recommend (≥ 70): Invite for interview
  • Maybe (50–69): Consider if candidate pool is thin
  • Pass (< 50): Not a fit

Step 5: Batch Processing

When scoring multiple CVs:

  1. Score each CV independently — no cross-comparison during scoring (safe to parallelize)
  2. After all CVs are scored, produce a summary ranking (highest to lowest)
  3. Use the batch summary format in references/output-format.md

Scoring Principles

  • Objective: Score based on facts in the CV, avoid over-inference
  • Fair: Apply the same standard consistently across all candidates
  • Red flag detection: Repetitive content, inflated metrics, unexplained career gaps, contradictory information
  • Output language: Match the user's language (respond in the same language the user is using)
  • No bias: Do not evaluate based on age, gender, ethnicity, or personal factors unrelated to the job

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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