tailor-resume

name: tailor-resume description: Choose the best existing resume base/variant for a job, or create a new tailored variant when nothing fits. argument-hint: "<digest-json | job-url | pasted-jd-text>"

Tailor Resume — Reuse or Create

Choose or produce a resume for a specific job. You decide reuse vs create; the user does not pre-select.

Setup

Follow ../shared/setup.md. The profile response includes data.resumes (every base with label, hasData, variantCount, isPrimary).

Step 1: Build the JD object

Detect the argument shape:

• Starts with { → parse as digest JSON. No navigation, no snapshot.
• Starts with http → browser_navigate, then browser_snapshot the posting body (per ../shared/browser-tips.md) and build the digest from it.
• Otherwise → pasted JD text; parse the same fields manually.

From the digest (title, requirements[], responsibilities[], techStack[], yearsExperience, descriptionExcerpt), assemble:

• title, domain (fintech/healthtech/devtools/…), standouts (clearance, on-call, on-site, …).
• roleFamily ∈ frontend | backend | fullstack | mobile | data | ml | devops | qa | other — match title + descriptionExcerpt against: frontend (frontend, ui, react, vue, angular), backend (backend, api, services), fullstack (full-stack), mobile (ios, android, react native, flutter), data (data engineer/scientist, analytics, etl), ml (ml, ai engineer, mlops), devops (devops, sre, platform, infrastructure), qa (qa, sdet, test engineer).
• seniority ∈ junior | mid | senior | staff | lead — from title (junior/entry → junior; senior/sr. → senior; staff → staff; lead/principal → lead; else mid). Cross-check yearsExperience: 0–2 junior, 3–5 mid, 6–9 senior, 10+ staff/lead.
• keywords — top 10 required-tech terms from techStack ∪ extracted from requirements. Lowercase, deduped, must-have ranked above nice-to-have.
• responsibilityTerms — top 5 verbs/nouns from responsibilities (design, mentor, migrate, on-call, …).

Step 2: Pick the Base

Primary wins. If primaryResumeId is set and that resume has hasData or a sourceFilename, use it as BASE_ID (skip scoring; Step 3 extracts content if missing). Otherwise score each data.resumes entry (max 10):

Highest wins. Tie-break: primary → most recent → lowest id. If no candidate has hasData AND no sourceFilename, stop:

No usable base resume. Upload a PDF at http://localhost:8000/resumes, or fill a resume's editor manually, then re-run.

Let BASE_ID be the chosen id.

Step 3: Extract Structure if Missing

curl -fsS "$JOBPILOT_API/api/resumes/$BASE_ID"

If content is null, delegate to extract-resume so the logic stays in one place:

Run the extract-resume skill for $BASE_ID and wait for it to finish.

Refetch the base row afterward — Step 5 needs the saved content. If extract-resume stops because there's no sourceFilename, surface the same message and stop.

Skip this step when hasData: true.

Step 4: Decide Reuse vs Create

curl -fsS "$JOBPILOT_API/api/resumes/$BASE_ID/variants"

For each variant, fetch GET /api/resumes/variants/<id> and compute reuseScore (0–100). Variants failing the role-family gate (different family AND not adjacent) score 0.

Pick the highest scorer:

• ≥75 → reuse.
• 60–74 → reuse, echo a one-line caveat naming the weakest component.
• <60 or no variant passes the gate → Step 5.

On reuse:

Reusing variant {id}: {label} (score {n}/100). http://localhost:8000/api/resumes/variants/{id}/pdf

Stop.

Step 5: Create a New Variant

The server does all structural rewriting (skill ordering, bullet ranking) deterministically. You write only:

• summary — ≤3 sentences targeting this role. Plain, specific. No clichés, no "passionate"/"results-driven" filler. No fabrication of experience, scope, or numbers.
• emphasizedTech — 4–8 lowercase tech terms from JD.keywords to surface first in skill groups.
• jobKeywords — optional, ~10 terms; defaults to emphasizedTech. Ranks experience/project bullets.
• label — "{Company} — {Title}" (short).
• jobUrl — when the argument was a URL or digest carried one.
• applicationId — when the JD URL matches an existing Application (GET /api/applied/check?url=… → data.match.application.id).
• diffNotes — 1–3 sentences on what was emphasized and why.

Optional — reword recent bullets

You may rephrase bullets on the top 1–2 roles to match the JD's wording. Omit when reordering alone suffices (the safe default).

• bulletRewrites — [{ entryIndex, bullets: [{ original, tailored }] }]. Copy original verbatim from experience[entryIndex].bullets; rephrase tailored to lead with the JD-relevant outcome. Add no number, date, employer, tech, or scope not already in that bullet — it must hold up in an interview.
• rewordTopN — optional, default 2; allowed entryIndex is 0..rewordTopN-1.

Server-enforced: 422 on a new number, an unknown original, or out-of-window entryIndex; non-blocking flags for tech terms absent from the resume. On 422, read details, fix the text, resend — never drop the guardrail.

curl -fsS -X POST "$JOBPILOT_API/api/resumes/$BASE_ID/tailor" \
  -H 'content-type: application/json' \
  -d "$(jq -n --arg summary "<2-3 sentence tailored summary>" \
                --arg label "<Company> — <Title>" \
                --arg jobUrl "<job-url-or-empty>" \
                --argjson tech '["typescript","react","next.js","aws"]' \
                --argjson rewrites '[{"entryIndex":0,"bullets":[{"original":"<verbatim base bullet>","tailored":"<rephrased to JD, no new facts>"}]}]' \
    '{label:$label, jobUrl:($jobUrl|select(length>0)), emphasizedTech:$tech, jobKeywords:$tech, summary:$summary, bulletRewrites:$rewrites, diffNotes:"Surfaced React/Next.js ahead of other tech; reworded 1 recent bullet to the JD."}')"

Response { id, pdfUrl, rewordedBullets, flags }. Echo:

Created variant {id} from base {baseId} ({rewordedBullets} reworded). http://localhost:8000{pdfUrl}

If flags is non-empty, append: ⚠ verify — not elsewhere in your resume: {flags}.