# Resume Fit Scorer

> 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. Use this skill when: - Gating whether a tailored resume is good enough to submit - Producing a 0–10 fit score with per-dimension sub-scores - Generating an actionable critique + prioritized fixes for revision - Ranking multiple resume variants against one JD - Auditing a resume for ATS or red-flag risk before applying - Checking which JD must-haves a resume fails to cover

- Skill: `ebarti/resume-fit-scorer` (Agent Skill, multi-file: 11 files)
- Install (CLI): `npx skillmds@latest add ebarti/resume-fit-scorer`
- Raw SKILL.md: https://api.skillmd.com/api/skills/ebarti/resume-fit-scorer/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: ebarti (https://skillmd.com/u/ebarti)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/ebarti/resume-fit-scorer

---


# 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

1. Read `guidelines.md` — it routes from your task/symptom to the right files.
2. For an end-to-end score, follow `workflows/score-resume-against-jd.md`.
3. Load only the reference files the guidelines point to.
4. 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.