agentleFS
ebartiebarti/skills/resume-fit-scorer/SKILL.md

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.

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
  1. Very specific:

    Read guidelines.md — it routes from your task/symptom to the right files.

    line 55

≈ “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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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)

DimensionWeight
JD match30%
Achievement strength25%
Targeting & focus15%
ATS parseability10%
Red flags10%
Language10%

Verdicts use threshold comparisons on the real-valued overall, not integer-rounded bands.

OverallVerdict
< 3.0Trash
>= 3.0 and < 5.0Weak
>= 5.0 and < 7.0OK
>= 7.0 and < 9.0Strong
>= 9.0Excellent

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

CategoryFilesPurpose
references/scoring-rubric/knowledge, rules, examplesThe 6 dimensions, weights, 0–10 bands, weighted formula, calibration
references/jd-match/knowledge, rules, examplesThe 30% dimension: ATS + glance + decision-maker screening, coverage
references/red-flags/smells, checklistRed-flag catalog + fast scan / auto-reject criteria

Workflows

TaskWorkflow
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.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.