Arete

Arete is a resume compiler for structured candidate information. It turns a human-authored candidate source file into a truthful, ATS-friendly, human-readable resume as both LaTeX and PDF.

The project is CLI-first and deliberately small: no web app, account system, resume database, or cloud service is required for the MVP. The core idea is a compiler pipeline with explicit validation, provenance, and STAR-style evidence gathering instead of free-form resume generation.

Status

Greenfield bootstrap in progress. The current implementation provides the initial CLI, Markdown candidate parsing, validation, deterministic resume composition, LaTeX rendering, and npm-managed PDF compilation.

Goals

• preserve candidate-provided facts as the source of truth;
• encourage STAR-style evidence: Situation, Task, Action, Result;
• generate selectable-text resumes suitable for ATS parsing;
• produce concise, professional human-readable output;
• keep the architecture maintainable, testable, and reproducible;
• make unsupported factual claims impossible to introduce silently.

Usage

corepack enable
pnpm install
pnpm build

pnpm arete init --output candidate.md
pnpm arete validate --source candidate.md
pnpm arete build --source candidate.md --out dist/resume

arete build writes resume.tex and compiles resume.pdf through the npm-managed LaTeX compiler installed by pnpm install. System latexmk or pdflatex are used only as fallbacks. English is the default locale; use --locale pt-BR for localized section labels and dates currently supported by the MVP.

Architecture

candidate Markdown
  -> STAR evidence notes
  -> parser with source references
  -> runtime validation
  -> canonical candidate model
  -> deterministic resume composition
  -> LaTeX rendering with escaping
  -> .tex and .pdf artifacts

LLM use is intentionally deferred. Future AI features must remain editorial-only and validate their output against candidate-provided facts.

Quality Gates

pnpm format:check
pnpm lint
pnpm typecheck
pnpm test:coverage
pnpm build

See docs/ for the product spec, architecture, testing strategy, security and privacy model, content policy, LaTeX constraints, and ExecPlan workflow.