Install any skill in seconds. Free to start, no credit card required.
Get Started Free →Full-page illustrated storybook exemplar — symbolic shape-family characters, page-level raster scenes, text overlays, deterministic PDF assembly.
.claude/skills/docxology-template-storybook/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 54% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -32% | 0% |
| case-13 | ✗→✓ | ▲ Improved | -53% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -68% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -32% | 0% |
Project-scoped skill for the in-repo exemplar at projects/templates/template_storybook/. Load this when working inside the project.
template_storybook exemplar — running scripts, editing storycontent, or regenerating illustrated pages.
no-mocks testing) still hold after changes.
AGENTS.md.content/story.yaml.src/storybook/ (models.py, characters.py,story.py, illustration.py, text_layout.py, rendering.py) — never in scripts/.
bash# From the repository root uv run pytest projects/templates/template_storybook/tests --cov=projects/templates/template_storybook/src --cov-fail-under=90 uv run python scripts/pipeline/stage_02_analysis.py --project templates/template_storybook uv run python scripts/pipeline/stage_03_render.py --project templates/template_storybook uv run python scripts/pipeline/stage_04_validate.py --project templates/template_storybook uv run python scripts/pipeline/stage_05_copy.py --project templates/template_storybook
overlay, and PDF assembly belong in src/storybook/, not in scripts/.
computation.
output/ — regenerate fromcontent/story.yaml and source.
as working directory unless the child AGENTS.md states otherwise.
AGENTS.mdREADME.mdprojects/AGENTS.md| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 8,325 | 7,714 | -7% | 1 | 1 | 0% | 1,169 | 1,806 | +54% | 0 | 0 | — |
case-02 | fail→pass | 8,092 | 2,869 | -65% | 1 | 1 | 0% | 1,559 | 1,065 | -32% | 0 | 0 | — |
case-03 | fail→fail | 19,736 | 11,187 | -43% | 1 | 1 | 0% | 2,991 | 2,515 | -16% | 0 | 0 | — |
case-13 | fail→pass | 11,161 | 2,215 | -80% | 1 | 1 | 0% | 1,805 | 854 | -53% | 0 | 0 | — |
case-04 | pass→pass | 10,974 | 3,212 | -71% | 1 | 1 | 0% | 1,597 | 1,134 | -29% | 0 | 0 | — |
case-05 | fail→pass | 14,884 | 2,097 | -86% | 1 | 1 | 0% | 2,565 | 819 | -68% | 0 | 0 | — |
case-06 | fail→pass | 13,993 | 5,810 | -58% | 1 | 1 | 0% | 2,359 | 1,608 | -32% | 0 | 0 | — |
case-07 | fail→pass | 5,721 | 2,882 | -50% | 1 | 1 | 0% | 942 | 1,123 | +19% | 0 | 0 | — |
case-08 | fail→pass | 9,922 | 3,520 | -65% | 1 | 1 | 0% | 1,796 | 1,154 | -36% | 0 | 0 | — |
case-09 | pass→pass | 6,747 | 2,293 | -66% | 1 | 1 | 0% | 1,293 | 978 | -24% | 0 | 0 | — |
case-10 | fail→pass | 25,522 | 1,376 | -95% | 1 | 1 | 0% | 2,272 | 761 | -67% | 0 | 0 | — |
case-11 | fail→pass | 5,744 | 1,688 | -71% | 1 | 1 | 0% | 796 | 757 | -5% | 0 | 0 | — |
case-12 | fail→pass | 6,125 | 2,649 | -57% | 1 | 1 | 0% | 998 | 1,030 | +3% | 0 | 0 | — |
case-14 | fail→pass | 15,016 | 2,424 | -84% | 1 | 1 | 0% | 2,409 | 909 | -62% | 0 | 0 | — |
case-15 | fail→pass | 12,408 | 1,932 | -84% | 1 | 1 | 0% | 1,916 | 822 | -57% | 0 | 0 | — |
case-16 | fail→pass | 7,945 | 3,286 | -59% | 1 | 1 | 0% | 1,295 | 1,038 | -20% | 0 | 0 | — |
case-17 | pass→pass | 7,525 | 1,551 | -79% | 1 | 1 | 0% | 1,381 | 795 | -42% | 0 | 0 | — |
case-18 | fail→pass | 10,297 | 1,719 | -83% | 1 | 1 | 0% | 1,736 | 796 | -54% | 0 | 0 | — |
case-19 | fail→pass | 8,972 | 2,490 | -72% | 1 | 1 | 0% | 1,523 | 859 | -44% | 0 | 0 | — |
case-20 | pass→pass | 8,567 | 5,043 | -41% | 1 | 1 | 0% | 1,514 | 1,429 | -6% | 0 | 0 | — |
case-21 | pass→pass | 12,856 | 4,576 | -64% | 1 | 1 | 0% | 1,417 | 1,355 | -4% | 0 | 0 | — |
case-22 | pass→pass | 5,545 | 7,688 | +39% | 1 | 1 | 0% | 939 | 1,721 | +83% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +68 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.