Slide Excellence

Slide Excellence Review

Run a comprehensive multi-dimensional review of lecture slides. Multiple agents analyze the file independently, then results are synthesized.

Which slide-review skill do I want?

• /slide-excellence (this skill) — multi-agent fanout (visual + pedagogy + proofread, plus TikZ / parity / substance conditionally). Best for pre-teaching or pre-release checks.
• /visual-audit — single lens, layout/overflow/font/spacing only. Fast.
• /pedagogy-review — single lens, narrative/prerequisites/worked-examples/notation.
• /proofread — single lens, grammar/typos/overflow/terminology.
• /qa-quarto — adversarial Beamer ↔ Quarto parity (critic-fixer loop).
• /devils-advocate — 5-7 pointed challenges, not a full review.

Important: this orchestrator does conditional dispatch — it only spawns the subagents that can actually produce useful output for the given file. No more running tikz-reviewer on a file with zero TikZ, or quarto-critic on a deck without a counterpart.

Step 1: Identify the File

Parse $ARGUMENTS for the filename. Resolve path in Quarto/ or Slides/.

Determine the file type:

• .tex → Beamer
• .qmd → Quarto
• .md → Markdown slides

Step 2: Pre-flight — Detect Conditions

Before spawning any agent, probe the file to determine which reviews make sense:

FILE="$resolved_path"

# Has TikZ diagrams?
has_tikz=$(grep -c '\\begin{tikzpicture}' "$FILE" 2>/dev/null); has_tikz=${has_tikz:-0}

# For .qmd: is there a paired .tex in Slides/?
has_tex_pair="false"
if [[ "$FILE" == *.qmd ]]; then
  base="$(basename "$FILE" .qmd)"
  # Common Beamer suffixes: _Topic, _Lecture, exact match
  for candidate in "Slides/${base}.tex" "Slides/Lecture${base}.tex"; do
    if [ -f "$candidate" ]; then
      has_tex_pair="true"
      tex_pair="$candidate"
      break
    fi
  done
fi

# For .tex: is there a paired .qmd in Quarto/?
has_qmd_pair="false"
if [[ "$FILE" == *.tex ]]; then
  base="$(basename "$FILE" .tex)"
  for candidate in "Quarto/${base}.qmd" "Quarto/${base#Lecture}.qmd"; do
    if [ -f "$candidate" ]; then
      has_qmd_pair="true"
      qmd_pair="$candidate"
      break
    fi
  done
fi

# Has R code chunks or referenced R scripts?
has_r="false"
if grep -qE '```\{r|source\(.*\.R\)' "$FILE" 2>/dev/null; then
  has_r="true"
fi

Report the detection:

File:         path/to/file.tex
Type:         Beamer (.tex)
TikZ blocks:  3
Quarto pair:  Quarto/Lecture2.qmd (found)
R chunks:     none

Step 3: Domain-reviewer customization check (MANDATORY for .tex)

Before spawning the substance-review agent on a .tex file, verify .claude/agents/domain-reviewer.md has been customized for this project. The ship-state domain-reviewer is a template — running it unmodified produces generic "are assumptions stated?" feedback, not real domain review.

Detection heuristic (any of these → still template):

• Contains the marker token AUTO-DETECT-TEMPLATE-MARKER anywhere in the file (present in the shipped template; removed/replaced when customized). Detection is a substring match — the marker can span lines.
• Contains any <!-- Customize: ... --> or [Customize: ...] placeholder (both forms are checked).
• The five lenses are identical to the shipped template's wording (diff against .claude/agents/domain-reviewer.md on the v1.3.0 tag — if zero lines changed, it's still template).

If the template marker is present:

⚠️  domain-reviewer.md has not been customized for your field.

Running it in its shipped state produces generic checks ("are assumptions
stated?") rather than field-specific review. Options:

  1. Customize .claude/agents/domain-reviewer.md — replace the 5 lenses
     with checks for your field (the file's EXAMPLES block shows two
     disciplines to copy from).
  2. Run slide-excellence with --skip-substance to proceed without the
     substance-review agent. Other reviewers still run.
  3. Run slide-excellence with --acknowledge-template-domain-reviewer to
     proceed anyway (you'll get generic feedback from the substance agent).

What would you like to do?

Wait for user input. Do NOT silently run domain-reviewer on a template.

Step 4: Run Review Agents in Parallel

Spawn only the agents whose conditions hold:

Always-on for slides (.tex or .qmd):

• Agent A: Visual Audit (slide-auditor) Overflow, font consistency, box fatigue, spacing, images. Save: quality_reports/[FILE]_visual_audit.md.

• Agent B: Pedagogical Review (pedagogy-reviewer) 13 pedagogical patterns, narrative, pacing, notation. Save: quality_reports/[FILE]_pedagogy_report.md.

• Agent C: Proofreading (proofreader) Grammar, typos, consistency, academic quality, citations. Save: quality_reports/[FILE]_proofread_report.md.

Conditional:

• Agent D: TikZ Review (tikz-reviewer) — only if has_tikz > 0. Measurement-based collision audit (Bézier, gaps, boundaries, margins). Save: quality_reports/[FILE]_tikz_review.md.

• Agent E: Content Parity (quarto-critic) — only if the file has a counterpart (has_tex_pair or has_qmd_pair). Frame count comparison, environment parity, content drift between .tex ↔ .qmd. Save: quality_reports/[FILE]_parity_report.md.

• Agent F: R Code Review (r-reviewer) — only if has_r == true. Code correctness for any embedded R chunks or referenced scripts. Save: quality_reports/[FILE]_r_review.md.

• Agent G: Substance Review (domain-reviewer) — MANDATORY for .tex, OPTIONAL for .qmd, GATED by Step 3. Domain correctness via the 5-lens framework. Save: quality_reports/[FILE]_substance_review.md.

De-duplication: if the user has already run one of these skills on this file in the current session (e.g., ran /proofread first, now running /slide-excellence), ask whether to reuse the existing report or re-run. Default: reuse (saves tokens).

Step 5: Synthesize Combined Summary (reduce typed findings)

This is fan-out → reduce (orchestrator-protocol.md): each agent returns FINDINGs + a SCORECARD in the shared schema (orchestration-schemas.md), and this step stacks the typed scorecards rather than re-reading each report by eye. The Overall Quality Score is the gate predicate over summed CRITICAL/MAJOR/MINOR counts. (Conditional dispatch means a skipped lens contributes no findings, not zeros to average.)

Only include sections for agents that actually ran.

# Slide Excellence Review: [Filename]

**File:** [path]
**Type:** [Beamer / Quarto / Markdown]
**Detected:** TikZ=N | pair=[path or none] | R=[yes/no]
**Agents spawned:** [A, B, C, D, G] (skipped: E [no pair], F [no R])

## Overall Quality Score: [EXCELLENT / GOOD / NEEDS WORK / POOR]

| Dimension | Critical | Medium | Low |
|-----------|----------|--------|-----|
| Visual/Layout | | | |
| Pedagogical | | | |
| Proofreading | | | |
| TikZ (if ran) | | | |
| Substance (if ran) | | | |

### Critical Issues (Immediate Action Required)
### Medium Issues (Next Revision)
### Recommended Next Steps

Step 6: Report Token/Time Budget

After completion, print an estimate:

Spawned N agents; approx token usage ~XXk. Sequential fallback
(one agent at a time) would cost ~XXk but take ~5× longer. For
cost-conscious reviews, run individual subagent skills directly
(/proofread, /visual-audit, /pedagogy-review).

Flag Reference

Quality Score Rubric

Why conditional dispatch matters

The previous version of this orchestrator spawned all 6 subagents regardless of file type. Running tikz-reviewer on a TikZ-free deck produced an empty report (wasted tokens). Running quarto-critic without a counterpart file produced a "no pair to compare" report (wasted tokens). And running domain-reviewer without customization produced generic "are assumptions stated?" feedback that authors learned to ignore (eroded trust in the whole orchestrator).

Conditional dispatch cuts token cost roughly in half on typical .qmd-only files and doubles trust by never running a reviewer that can't produce useful output.

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 — 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: only verdict: "confirmed" findings ship; anything it cannot ground is dropped, not downgraded to a warning.