Review render

Skill jain777/jobclaw-skills/skills/review-render

Visually QA a rendered resume PDF and auto-fix layout/content defects in a bounded loop: render → screenshot → deterministic gate → vision rubric → apply one fix → re-render, until it passes or hits a pass cap. Catches widows, under-fill, overflow, orphaned headers, and imbalance that text-only logic can't see.From its SKILL.md

Install

npx -y skills add jain777/jobclaw-skills --skill review-render

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

5 stars5 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

5.0 KB, as published. Nobody here has run it

review-render

A rendered resume has defects that are invisible in the JSON and only show up on the page — a bullet wrapping with two dangling words, a half-empty page, content spilling one line onto page 2, an orphaned section header. This skill closes the loop the way a human does: make it, look at it, fix it, repeat — bounded so it always terminates.

Architecture split (see ../../_shared/RULES.md): rendercv renders; this skill (the brain) judges and decides the fix. Rendering levers live in render-resume; the visual judgment and content edits live here.

render-resume hands off to this skill as its mandatory final step (its §6 Self-QA) — so every resume is visually QA'd, not just ones where someone remembers to ask. You can also invoke it standalone on any existing rendered resume.

Inputs

The JSON-Resume intermediate: resumes/<name>.json (the editable source of content fixes).
The output PDF path: resumes/<name>.pdf.
Optional: target --max-pages, --theme (else from meta.theme).

The loop (max 3 passes — never loop forever)

1. Render with page PNGs

python3 skills/render-resume/scripts/render.py \
    --data resumes/<name>.json --out resumes/<name>.pdf --emit-png \
    [--max-pages 1|2] [--theme T] [--date-col 3.3cm] [--density snug|compact|dense|tight]

This writes the PDF plus resumes/<name>.p1.png, .p2.png, ….

2. Deterministic gate (cheap — no vision tokens)

skills/render-resume/.venv/bin/python skills/render-resume/scripts/qa_report.py resumes/<name>.p*.png

Returns {pages, page_fills, last_page_fill, flags}. Flags: underfilled, sparse_last_page, overflow_risk.

3. Vision rubric — Read each .pN.png and score it against reference/rubric.md. Record each issue as {dimension, severity (critical/major/minor), where, suggested fix}.

4. Decide

PASS when the deterministic flags are empty and the rubric has no critical/major issue (score ≥ 90). Report and stop.
Otherwise pick the single highest-severity issue, apply exactly one fix from the vocabulary below, and go back to step 1.
After 3 passes, stop regardless; report the best version + any residual issues and a recommendation.

5. Clean up the .pN.png files (and any .rendercv.yaml) unless the caller asked to keep them.

Fix vocabulary (issue → lever)

Apply ONE per pass, then re-render and re-judge — never stack blind changes.

Issue	Fix (try in this order)
Widow / overflow line (bullet wraps, 1–2 words dangle)	`--date-col 3.3cm` (more bullet width). If it persists, tighten that specific bullet in the JSON by 3–6 words — preserve meaning and keep the metric.
Underfilled single page (`underfilled`, bottom whitespace)	Restore a previously-cut bullet/section to the JSON (preferred — recovers lost context), or force a lighter density (`--density snug`/`compact`).
Spills to 2 pages, sparse last page (`sparse_last_page` / `overflow_risk`)	If content is ~1 page: trim the lowest-value bullet(s) per `tailor-resume`'s rubric, or `--max-pages 1` to densify. If genuinely 1.5+ pages: `--max-pages 2` and rebalance so the last page is >50% full.
Orphaned section header at page bottom	Step density one notch, or trim/restore one line to shift the break.
Inconsistent dates / bullet glyphs / tense	Fix in the JSON (formatting) — not a renderer concern.
Section imbalance or wrong order	Reorder/rebalance sections in the JSON.

Rules

One fix per pass. Re-render and re-evaluate before the next change.
No fabrication. "Tighten" = cut words, never invent. Content edits obey tailor-resume's rubric and _shared/RULES.md (incl. never quoting context.*).
Always terminates. Hard cap of 3 passes; if still failing, stop and recommend (e.g., "content is genuinely two pages — use --max-pages 2").
Layout first, content second. Prefer a rendering lever (date-col, density) before editing real content, so context isn't lost to cosmetics.

Output

A concise QA report: PASS/FAIL, final score, the iteration log (per pass: what the gate + rubric flagged → the one fix applied → the new result), and the final PDF path.

Next steps

Resume passed QA. Next: /write-cover-letter, then apply — or /apply-to-job to finish the package.