resume-fit-scorer
Skill1 starsChanged 6 months agoMITView on GitHub
Scores how well a resume fits a specific job description on a 0–10 scale across 6 weighted dimensions (JD match, achievement strength, targeting, ATS-parseability, red flags, language), returns a brutally honest critique, and emits structured prioritized fixes. Distilled from "Resumes For Dummies" (AI-era ed.). Built for automated pipelines (e.g. JobHunter) as the verifier in a write→score→revise loop.
In this repository21 other files it gives its agents.
- ai-context-engineeringSkill
- ai-context-engine-productionSkill
- ai-context-engineSkill
- ai-dataset-engineeringSkill
- ai-evaluationSkill
- ai-finetuningSkill
- ai-foundation-modelsSkill
- ai-inference-optimizationSkill
- ai-multi-agent-mcpSkill
- ai-production-architectureSkill
- ai-prompt-engineeringSkill
- ai-rag-and-agentsSkill
- ai-rag-defenseSkill
- ddia-architectureSkill
- ddia-batch-stream-processingSkill
- ddia-data-ethicsSkill
- ddia-data-modelingSkill
- ddia-replication-shardingSkill
- ddia-transactions-consistencySkill
- job-description-analyzerSkill
- resume-content-writerSkill
The file
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 0 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 55
Read guidelines.md — it routes from your task/symptom to the right files.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
resume-fit-scorer
Judges a resume against one job — harshly, on a 0–10 scale — and explains exactly why. It scores 6 weighted dimensions, detects red flags, computes must-have coverage, and returns a critique plus impact-ordered fixes that the writer can act on. Built from "Resumes For Dummies" (AI-era ed.), chapters 1, 2, 3, 5, 6, 10, 15, 16, 18.
Role in the JobHunter pipeline
job-description-analyzer → resume-content-writer → [resume-fit-scorer] → (revise loop)
TargetProfile ResumeContent FitScore ──┐
▲ │ prioritized_fixes
└──────────────────────────────┘It accepts a resume (plain text or resume-content-writer output) + a TargetProfile, and returns a FitScore. See workflows/score-resume-against-jd.md for the full I/O contract and the rubric.
Default rubric (overridable via weights)
| Dimension | Weight |
| JD match | 30% |
| Achievement strength | 25% |
| Targeting & focus | 15% |
| ATS parseability | 10% |
| Red flags | 10% |
| Language | 10% |
Verdicts use threshold comparisons on the real-valued overall, not integer-rounded bands.
| Overall | Verdict |
< 3.0 | Trash |
>= 3.0 and < 5.0 | Weak |
>= 5.0 and < 7.0 | OK |
>= 7.0 and < 9.0 | Strong |
>= 9.0 | Excellent |
Calibrated harshly: a generic, untargeted resume should land 3–5, not 7.
Quick Start
- Read
guidelines.md— it routes from your task/symptom to the right files. - For an end-to-end score, follow
workflows/score-resume-against-jd.md. - Load only the reference files the guidelines point to.
- Compute the weighted overall, apply red-flag/missing-must-have ceilings, and return actionable fixes.
Contents
References
| Category | Files | Purpose |
references/scoring-rubric/ | knowledge, rules, examples | The 6 dimensions, weights, 0–10 bands, weighted formula, calibration |
references/jd-match/ | knowledge, rules, examples | The 30% dimension: ATS + glance + decision-maker screening, coverage |
references/red-flags/ | smells, checklist | Red-flag catalog + fast scan / auto-reject criteria |
Workflows
| Task | Workflow |
| Score a resume against a JD (0–10 + critique + fixes) | workflows/score-resume-against-jd.md |
Guidelines
See guidelines.md for task/symptom-based file selection, a decision tree, the full file index, and common combinations.
Does it work?
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Your trail
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Now do this for your own.
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