Review Resume

Review Resume

Save one improved version of a base resume as a Suggested rewrite variant. The user accepts or discards it in the dashboard. Never write to the base resume.

Runs after extract-resume on upload: extraction is faithful to the PDF, this pass makes the document better.

Setup

Follow ../_shared/setup.md, then:

curl -fsS -H "authorization: Bearer $JOBPILOT_API_TOKEN" "$JOBPILOT_API/api/resumes/$RESUME_ID"

content: null → extraction hasn't run; say so and stop. Also Read the source PDF (path per ../_shared/setup.md) - extraction flattens two-column layouts and drops emphasis.

What to improve

For a human screener skimming, and the ATS parsing:

• summary - what they do, at what level, two strongest specifics. Cut anything true of every candidate.
• basics.headline - a role title people search for, not a slogan.
• Bullets - outcome first, consistent tense, no "Responsible for" / "Worked on" / "Helped with". Remove phrasing repeated across entries - one stock phrase in three roles flattens all three.
• Skill groups - consolidate. Past ~5 groups it reads as a keyword dump.
• Ordering - most relevant experience and projects first.

Then run the humanizer skill in embedded mode on the summary and bullets.

Rules

The user sees a diff and clicks accept, so the diff is the guard - not a server check:

1. Wording, ordering, emphasis, grouping. Never facts. No employer, date, title, degree, school, or number absent from the extracted content or the source PDF. Not a rounded metric, not an inferred date, not a "Senior" added to a title.
2. diffNotes lists every change, one per line, specific enough to check: Summary: rewritten to lead with the HIPAA platform. A change not in the notes is one the user can't decline - if you can't list it, don't make it.
3. Keep every entry. Dropping or merging roles is tailor-resume, which has server-side guards.
4. Don't touch basics contact fields. At onboarding the resume fills the profile, so it's the source of truth.
5. If the resume is already good, save nothing and say so. A suggestion the user rejects teaches them to ignore the next one.

Save

label must be exactly Suggested rewrite - the dashboard finds it by that label and the retention sweep skips it.

curl -fsS -H "authorization: Bearer $JOBPILOT_API_TOKEN" -X POST "$JOBPILOT_API/api/resumes/$RESUME_ID/variants" \
  -H 'content-type: application/json' \
  -d "$(jq -n --argjson content "$IMPROVED_CONTENT" --arg notes "$DIFF_NOTES" \
    '{label:"Suggested rewrite", content:$content, diffNotes:$notes}')"

content is the full ResumeData - same shape extract-resume saves, every field carried over. A 400 means it doesn't match the schema; fix and resend.

Then:

Suggested a rewrite of {label}: {one-line summary}. Review and accept at $JOBPILOT_WEB/resumes/$RESUME_ID

Don't open the browser or wait for an answer - the cycle ends here.