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Get Started Free →Use this plugin when the user wants a "Decision Tree" HyperFrames motion video — Animated flowchart with branching paths
.claude/skills/nexu-io-video-template-frame-decision-tree/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | -59% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 3% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 101% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -46% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -61% | 0% |
Animated flowchart with branching paths
A HyperFrames-ready HTML + CSS + GSAP motion composition, bundled under source/. It renders deterministically to MP4 / WEBM at 16:9, default 15s, 30fps.
Best for: How-to flow · Decision branching · Process diagram
source/index.html to understand the named layers and the animation timeline.source/; do not introduce external network assets that would break a headless render.Source: html-video templates/frame-decision-tree (license Apache-2.0). Forked from heygen-com / Hyperframes — https://github.com/heygen-com/hyperframes/tree/main/registry/examples/decision-tree.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-07 | fail→pass | 11,364 | 2,976 | -74% | 1 | 1 | 0% | 1,834 | 755 | -59% | 0 | 0 | — |
case-01 | fail→fail | 12,310 | 25,371 | +106% | 1 | 1 | 0% | 2,376 | 3,871 | +63% | 0 | 0 | — |
case-02 | fail→pass | 37,367 | 37,019 | -1% | 1 | 1 | 0% | 8,243 | 8,485 | +3% | 0 | 0 | — |
case-03 | fail→pass | 21,561 | 39,608 | +84% | 1 | 1 | 0% | 4,223 | 8,469 | +101% | 0 | 0 | — |
case-04 | fail→pass | 14,351 | 6,242 | -57% | 1 | 1 | 0% | 2,273 | 1,227 | -46% | 0 | 0 | — |
case-05 | fail→pass | 8,943 | 2,267 | -75% | 1 | 1 | 0% | 1,484 | 579 | -61% | 0 | 0 | — |
case-06 | fail→pass | 11,770 | 8,603 | -27% | 1 | 1 | 0% | 1,785 | 1,573 | -12% | 0 | 0 | — |
case-08 | pass→pass | 14,233 | 5,981 | -58% | 1 | 1 | 0% | 2,062 | 1,126 | -45% | 0 | 0 | — |
case-09 | fail→pass | 7,911 | 1,804 | -77% | 1 | 1 | 0% | 1,218 | 485 | -60% | 0 | 0 | — |
case-10 | pass→pass | 12,940 | 2,224 | -83% | 1 | 1 | 0% | 2,000 | 599 | -70% | 0 | 0 | — |
case-11 | pass→pass | 7,623 | 3,049 | -60% | 1 | 1 | 0% | 1,097 | 656 | -40% | 0 | 0 | — |
case-12 | fail→pass | 11,961 | 1,542 | -87% | 1 | 1 | 0% | 1,985 | 421 | -79% | 0 | 0 | — |
case-13 | pass→pass | 15,496 | 7,197 | -54% | 1 | 1 | 0% | 2,450 | 1,419 | -42% | 0 | 0 | — |
case-14 | fail→pass | 4,812 | 1,512 | -69% | 1 | 1 | 0% | 711 | 444 | -38% | 0 | 0 | — |
case-15 | pass→pass | 14,404 | 10,007 | -31% | 1 | 1 | 0% | 2,214 | 1,790 | -19% | 0 | 0 | — |
case-16 | pass→pass | 8,075 | 1,633 | -80% | 1 | 1 | 0% | 1,303 | 446 | -66% | 0 | 0 | — |
case-17 | fail→pass | 12,444 | 3,912 | -69% | 1 | 1 | 0% | 1,868 | 870 | -53% | 0 | 0 | — |
case-18 | fail→pass | 3,474 | 2,159 | -38% | 1 | 1 | 0% | 455 | 561 | +23% | 0 | 0 | — |
case-19 | pass→pass | 13,741 | 6,587 | -52% | 1 | 1 | 0% | 2,280 | 1,292 | -43% | 0 | 0 | — |
case-20 | pass→pass | 11,464 | 2,236 | -80% | 1 | 1 | 0% | 1,718 | 571 | -67% | 0 | 0 | — |
case-21 | fail→pass | 16,666 | 12,713 | -24% | 1 | 1 | 0% | 2,491 | 2,099 | -16% | 0 | 0 | — |
case-22 | pass→fail | 8,823 | 22,852 | +159% | 1 | 1 | 0% | 1,657 | 4,897 | +196% | 0 | 0 | — |
case-23 | pass→pass | 11,000 | 10,519 | -4% | 1 | 1 | 0% | 2,124 | 2,274 | +7% | 0 | 0 | — |
case-24 | pass→pass | 15,580 | 37,668 | +142% | 1 | 1 | 0% | 2,642 | 8,469 | +221% | 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. 24 cases were attempted. The headline lift of +46 percentage points is the difference between those two pass rates over the 24 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
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.