pedrohcgs 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.
Workflow
Phase 0: Pre-flight → Phase 1: Critic audit → Phase 2: Fixer → Phase 3: Re-audit → Loop until APPROVED (max 5 rounds)
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
- Locate Beamer (.tex/.pdf) and Quarto (.qmd/.html) files
- Check freshness (re-render if QMD newer than HTML)
- Verify TikZ SVGs if applicable
Phase 1: Initial Audit
Launch the quarto-critic agent to compare Beamer vs Quarto comprehensively. 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-launch critic 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 when a round adds 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 (zero CRITICAL).
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
Then, before presenting any summary:
python3 scripts/validate-findings.py <report>.json # exit 0 required
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—trueonly 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: only verdict: "confirmed" findings ship; anything it cannot ground is
dropped, not downgraded to a warning.