mirror of
https://github.com/MadsLorentzen/ai-job-search.git
synced 2026-09-17 00:26:26 +00:00
Ayobami Adegoke
2551824ecb
An ATS reads the compiled PDF's embedded text layer, not the rendered page, and LaTeX can silently produce PDFs whose text extracts as garbage: icon glyphs where contact details should be, (cid:*) markers from fonts without Unicode mappings, interleaved lines from multi-column layouts. This matters more now that /add-template lets users bring arbitrary templates. The existing Step 5 loop verifies what a human sees; this adds verification of what a parser sees. New Step 5d in /apply (CV only - cover letters rarely go through keyword screening; cleanup renumbered to 5e): - Extract the CV PDF's text layer with pdftotext -layout. pdftotext (poppler) is an optional dependency: if missing, the mechanical check is skipped with a warning and keyword coverage falls back to the visual PDF read - the same graceful-skip pattern as salary_lookup.py - Parseability checks verified against a real extraction of the stock template: email/phone must survive as literal text (fontawesome icons extract as harmless glyph-name noise like MOBILE-ALT/Envelope, but a contact detail carried only by an icon or hyperlink is invisible to ATS), no (cid:*) or replacement-character garbage, reading order matching visual order, dates present - Keyword coverage reuses the required/preferred list from Step 1, matched in the posting's language, reported as covered / synonym-only / missing-have-it / missing-gap. Honesty rule enforced: keywords the profile genuinely supports get added to experience bullets; genuine gaps stay visible, never stuffed Integration: CLAUDE.md verification checklist section, ATS Parseability guidance in 05-cv-templates.md, narrow Bash(pdftotext:*) entry in the pre-approved permissions (keeping with the tightened scope from #27), cv/*.txt gitignored (extraction is personal data; also deleted by the step itself), and optional-dependency docs in README and SETUP.