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Score Models

score

Data models for scoring results.

This module defines the result structures returned by scorer implementations, including overall scores, detailed breakdowns, and recommendations.

Classes

ScoreBreakdown dataclass 
ScoreBreakdown(
    keyword_score=0.0,
    skills_score=0.0,
    experience_score=None,
    education_score=None,
    certification_score=None,
    location_score=None,
    job_title_score=None,
    achievements_score=None,
    summary_score=None,
)

Detailed breakdown of scores by category.

Contains individual scores for each evaluation category. Scores are represented as floats from 0.0 to 100.0. Categories not evaluated by a particular scorer will be None.

Attributes:

Name Type Description
keyword_score float

Score for keyword matching (0-100).
skills_score float

Score for skills matching (0-100).
experience_score float | None

Score for experience matching (0-100) or None.
education_score float | None

Score for education matching (0-100) or None.
certification_score float | None

Score for certification matching (0-100) or None.
location_score float | None

Score for location matching (0-100) or None.
job_title_score float | None

Score for job title relevance (0-100) or None.
achievements_score float | None

Score for achievements analysis (0-100) or None.
summary_score float | None

Score for executive summary relevance (0-100) or None.
Recommendation dataclass 
Recommendation(
    category, priority, message, actionable_items
)

Actionable recommendation for improving resume score.

Provides specific suggestions to help improve the resume's match with the job description.

Attributes:

Name Type Description
category str

Category of the recommendation (e.g., "keywords", "skills").
priority str

Priority level ("low", "medium", or "high").
message str

Human-readable recommendation message.
actionable_items list[str]

List of specific items to address (e.g., missing skills).
ScoreResult dataclass 
ScoreResult(
    overall_score,
    breakdown,
    recommendations,
    matched_keywords,
    matched_skills,
    missing_skills,
)

Complete scoring result from a resume evaluation.

This is the main result object returned by scorer implementations. It contains the overall score, detailed breakdown, recommendations, and matching information.

Attributes:

Name Type Description
overall_score int

Overall ATS score from 0-100 (integer).
breakdown ScoreBreakdown

Detailed scores for each category.
recommendations list[Recommendation]

List of actionable recommendations for improvement.
matched_keywords list[str]

Keywords from job description found in the resume.
matched_skills list[str]

Skills from job requirements found in the resume (includes both required and preferred).
missing_skills list[str]

Required skills from job description not found in the resume.
Example 
result = scorer.score(resume, job)
print(f"Score: {result.overall_score}/100")
print(f"Skills match: {result.breakdown.skills_score:.1f}%")
for rec in result.recommendations:
    print(f"{rec.priority}: {rec.message}")