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name: qa-quarto description: Adversarial Quarto-vs-Beamer parity QA. A critic agent compares the Quarto HTML render to the Beamer PDF benchmark for content/visual parity; a fixer agent applies fixes; loops until APPROVED or two consecutive rounds turn up nothing new (fallback cap 5 rounds). Use when user says "qa the quarto", "check parity", "does the html match the pdf?", "quarto matches beamer?", or after a translate-to-quarto run. Requires both the .qmd rendered and a .pdf benchmark. argument-hint: "[LectureN]" allowed-tools: ["Read", "Grep", "Glob", "Write", "Edit", "Bash", "Agent", "Task"] context: fork

Adversarial Quarto vs Beamer QA Workflow

Compare Quarto HTML slides against their Beamer PDF benchmark using an iterative critic/fixer loop.

Philosophy: The Beamer PDF is the gold standard. The Quarto translation must be at least as good in every dimension.

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Workflow

Phase 0: Pre-flight → Phase 1: Critic audit → Phase 2: Fixer → Phase 3: Re-audit → Loop until APPROVED or dry (2 consecutive dry rounds; fallback cap 5)

Hard Gates (Non-Negotiable)

Gate	Condition
Overflow	NO content cut off
Plot Quality	Interactive charts >= static plots
Content Parity	No missing slides/equations/text
Visual Regression	Quarto >= Beamer in all dimensions
Slide Centering	Content centered, no jumping
Notation Fidelity	All math verbatim from Beamer

Phase 0: Pre-flight

1. Locate Beamer (.tex/.pdf) and Quarto (.qmd/.html) files
2. Check freshness (re-render if QMD newer than HTML)
3. Verify TikZ SVGs if applicable
4. Measure the render: "${SLIDE_QA_PYTHON:-python3}" scripts/slide-qa.py Quarto/[Lecture].html. It loads the deck in headless Chrome and writes quality_reports/audits/slide-qa/[Lecture]/report.md with per-slide overflow in pixels, plus one screenshot per slide. Exit 1 means it found something — overflow, clipped content, a broken image, or a missing or wrong-case file; exit 2 means it could not run (usually Playwright is missing — the script prints the one-time venv install and the SLIDE_QA_PYTHON line to set) — say so, and the critic falls back to reading the source.

Phase 1: Initial Audit

Launch the quarto-critic agent to compare Beamer vs Quarto comprehensively, passing the slide-qa report path from Phase 0 for the Overflow gate. Report saved to quality_reports/[Lecture]_qa_critic_round1.md.

Phase 2: Fix Cycle

If not APPROVED, launch quarto-fixer agent to apply fixes (Critical → Major → Minor), re-render, and verify.

Phase 3: Re-Audit

Re-run scripts/slide-qa.py on the fixer's re-render, then re-launch the critic with the fresh report to verify fixes. Loop back to Phase 2 if needed.

Iteration Limits — loop-until-dry

This is the loop-until-dry primitive from orchestrator-protocol.md: the critic returns FINDINGs (the hard-gate table is the CRITICAL roll-up, per orchestration-schemas.md); the loop converges after 2 consecutive dry rounds — rounds that add 0 new CRITICAL/MAJOR findings (deduped on id = sha1(file:line:locus)) — not at a fixed round count.

• Fallback cap: 5 rounds bounds a non-converging loop, then escalate to the user with remaining issues.
• Two-strikes: the same gate failing in rounds N and N+2 is flagged for the user, not patched again (summary-parity.md).
• APPROVED iff every hard gate passes and no CRITICAL or MAJOR finding remains (minor ones are listed for the user).

Final Report

Save to quality_reports/[Lecture]_qa_final.md with hard gate status, iteration summary, and remaining issues.

Findings are validated, not just written (v2.5)

This skill's reviewers emit findings under the machine-checked contract in finding-schema.json. Reports are JSON arrays.

Smoke-test the harness before spending review effort — a run that fans out reviewers and then cannot write a valid report has wasted the whole pass:

echo '[]' | python3 scripts/validate-findings.py

Reviewer agents are read-only, so this skill writes the files. For each reviewer's final response: save the prose report to this skill's report path for that reviewer, copy its closing fenced json block to a scratch file, and fill the ids while validating:

python3 scripts/validate-findings.py --fill-ids block.json > <report>.json.tmp \
  && mv <report>.json.tmp <report>.json || rm -f <report>.json.tmp   # exit 0 required; a failed run keeps no file
python3 scripts/validate-findings.py --check-quotes <report>.json   # each quote must be the file's own text (orchestration-schemas.md §1)

A reviewer that returned no json block, or a block that does not validate, has not reviewed: re-dispatch it once with the validator's error text, then report the lens as missing rather than reducing without it.

What the contract forces, and why:

• rule — the documented rule or standard violated. A finding citing no rule is an opinion, and opinions do not gate a commit.
• failing_case — a concrete configuration under which the claim breaks, or the exact missing hypothesis. "This could be clearer" does not validate.
• id = sha1("<file>:<line>:<locus>") — deterministic, so dedup across rounds is exact and the two-strikes rule is checkable rather than eyeballed.
• mechanical — true only for fixes that cannot change a result (typo, cross-reference, formatting, label). Never for an estimand, assumption, specification, inference procedure, sample definition, or reporting language: those return to the researcher.

Apply the per-lens evidence burdens and the "does NOT count" filters in orchestration-schemas.md §7 before verification, so known false alarms never reach the judge. The verifier pass is refute-biased and sets each finding's verdict (reviewers leave it unset): only verdict: "confirmed" findings ship; anything it cannot ground is dropped, not downgraded to a warning.