# Build brief — a focused alternative to CVMatchScore

> **Verdict:** Partly, if you narrow it · **Buildability:** 55/100 · **Category:** Career
> **Source:** https://www.canitbevibecoded.com/cvmatchscore
> Independent editorial assessment from Can It Be Vibe Coded? Not affiliated with, endorsed by, or derived from CVMatchScore. Verify current pricing and capabilities before acting.

## Context

**CVMatchScore** — Scores your resume against a job description across 19 parameters before you hit apply. It currently costs $4.08/mo.

The core loop, resume plus job posting into an LLM holding a scoring rubric, is one prompt and an afternoon, and for improving one resume against one posting it genuinely works. The honest gap is calibration: a rubric you wrote today measures today's mood, two runs of the same resume can disagree, and a 72 means nothing without a baseline of scored applications behind it. Fine as a mirror, thin as a measuring stick.

This brief describes a focused, single-operator replacement for the part of CVMatchScore that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest.

## What you are building

Extract text from the resume PDF, send it with the job description to an LLM holding a fixed scoring rubric, get structured JSON scores per criterion with quoted evidence, render a Markdown report.

- Tailor resumes, track applications, and rehearse answers from your own history.
- A responsive interface with real empty, loading, success, and error states.

## Requirements

### Functional

- Pdf-parse or pdfplumber for resume text extraction.
- A written rubric with a 0-10 definition per criterion.
- A few real resume and posting pairs to sanity-check the scores.

### Data and integrations

- OpenAI or Anthropic API key.

Each of these needs a real account, credential, or quota. Set them up before writing feature code.

### Non-functional

- Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support.
- Security: server-side secrets, validated input, and no credentials in the client bundle.
- Reliability: retries with backoff on external calls, and a clear failure state when a provider is down.
- Portability: the operator can export their data and leave without losing it.

## Implementation brief

Build me a local resume match scorer to replace CVMatchScore. Requirements:

- A Node 22 CLI: `match score resume.pdf job.txt` prints a score table and writes
  a Markdown report to reports/YYYY-MM-DD-<company>.md.
- Extract resume text with pdf-parse; accept .txt and .md for the job posting.
- Keep the rubric in rubric.json: 10 criteria (skills overlap, seniority fit,
  domain experience, quantified achievements, education, keyword coverage,
  employment gaps, clarity, length, ATS-safety), each with a 0-10 definition
  and a weight.
- One Anthropic structured-outputs call scores all criteria at once and must
  quote the resume line that justifies each score, no unquoted claims.
- A second cheap pass lists the 10 most important posting keywords missing from
  the resume and where each could honestly fit.
- Weighted total out of 100, computed in code from rubric.json, not by the model.
- Store every run in SQLite via better-sqlite3: date, company, total, and the
  per-criterion JSON, so `match history` shows my scores over time.
- API key from .env. No accounts, no telemetry, the resume never leaves my
  machine except the API call.
- Out of scope: cover letter generation, DOC/DOCX parsing, multi-language
  support, and recruiter-style bulk ranking.
- README: setup, cost per run, and a warning that scores are only comparable
  within one rubric version, so bump a version field in rubric.json when I edit it.

## Delivery standard

- Inspect the repository first, then write a short implementation plan before writing code.
- Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data.
- Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations.
- Include responsive layouts plus genuine empty, loading, success, validation, and failure states.
- Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data.
- Add structured logs around every external call and return actionable errors without leaking sensitive details.
- Write unit tests for the core logic and one automated test of the main user journey.
- Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations.

## Acceptance criteria

- [ ] A clean install starts the app using only the README and .env.example.
- [ ] The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable.
- [ ] Invalid input, missing configuration, provider failure, and an empty database each have a usable state.
- [ ] The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control.
- [ ] Tests, type checking, linting, and a production build all pass with no ignored failures.
- [ ] No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified.

## Non-goals

Do not build these, and do not claim to have replaced them:

- A calibrated rubric that scores the same resume the same way twice.
- 50+ language support tested per parameter.
- DOC, DOCX, and RTF parsing beyond PDF.
- Improvement plans and tailored cover letters built from the same analysis.
- Scores comparable across weeks of applications.

## What you still own after launch

- Secure credentials, rotate secrets, and handle provider rate limits.
- Run migrations, backups, restores, and dependency updates.
- Test the critical journey after every model, API, or hosting change.
- Monitor failures and fix the edge cases a first prompt will miss.

## Risk

**Operational risk.** The code is achievable; dependable data, integrations, and ongoing operations are the real cost.

Editorial confidence in this assessment: medium. No reviewed project implementation is linked yet.

## Existing alternatives

Before building, compare these checked options:

- [Resume-Matcher](https://www.resumematcher.fyi/) — A local resume-vs-posting matcher that runs against Ollama, so the scoring stays on your machine; you install it, it does the job, and nobody bills you

## Prior art

Working open-source software you can read, fork, or borrow from before starting:

- [pdfplumber](https://github.com/jsvine/pdfplumber) — reliable PDF text extraction, the unglamorous half of every resume tool
- [Resume-Matcher (repo)](https://github.com/srbhr/Resume-Matcher) — open-source resume vs job description matcher, a working reference for the whole loop

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Generated by [Can It Be Vibe Coded?](https://www.canitbevibecoded.com) · Full report: https://www.canitbevibecoded.com/cvmatchscore