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Get Started Free →Route a video-production brief to generation, deterministic composition, supplied-footage editing, or an automatic cross-modal plan before production begins.
.claude/skills/sickn33-video-router/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 46% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 78% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 51% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 49% | 0% |
| case-05 | ✗→✓ | ▲ Improved | 51% | 0% |
Knowledge for picking a video production line and locking it before work begins. This skill is read for guidance; it describes what to decide, not any tool mechanics.
This AAS-ready adaptation preserves the routing rules from the official OrkasVideoStudio video-router skill at upstream commit dd4a0f40b2bc6c6b0fe6f2e732c9540ffffefe08. It adds catalog metadata, examples, and limitations; it does not bundle or install the OrkasVideoStudio runtime. The immutable license_source above points to the upstream MIT license reviewed for this import.
If production, rendering, or paid tools are explicitly unavailable, still select the line and return a complete unexecuted production package for a clear brief: assumptions, script/narration, timed storyboard/shotlist, exact visible copy and captions, visual/audio direction, rights-safe asset provenance/fallbacks, export target, preview checklist, and final encoding/playback QA. Clearly distinguish planned from produced media and do not withhold the package behind a direction form.
A finished video is built from one or more of three orthogonal axes. Decide which dominate, then lock them.
operation:"edit" segment is required.reproduce, edit, or guide before choosing execution. Apply the same classification regardless of origin. Images can control content/identity/composition/structure/style; videos can additionally control motion/timing/audio through temporal anchors.Pick a single line when one axis cleanly dominates (just trim a clip; just an explainer; just generate a scene). Route to AUTO end-to-end when the deliverable genuinely needs MORE THAN ONE axis woven together — most often the user supplies their own material AND wants finished framing/voice/motion around it:
AUTO does not abandon the axes — it sequences them through one cross-modal plan (stage-plan builds the EDL, stage-assemble walks it), delegating each segment back to the generate / compose / edit lines. Choosing AUTO is itself the lock: the primary still gets named via the plan's delivery_promise (source_led / motion_led / compose_led / hybrid).
Request: "Make a 60-second vertical explainer about vector databases with kinetic text and captions."
Route: lock Compose (B) primary at 1080×1920. Add Generate (A) only if the approved concept needs original b-roll.
Request: "Turn my one-hour interview into three captioned highlight clips."
Route: lock Edit (C) primary because supplied footage is the dominant work object. Preserve evidence for selections and cleanup.
Request: "Use my product footage, generate a five-second opener, compose the feature stats, and add one voiceover."
Route: lock AUTO, name the delivery promise, and plan the edit, generate, compose, and narration segments in one cross-modal EDL.
stage-plan and stage-assemble refer to the upstream OrkasVideoStudio workflow and may be unavailable unless the user separately installs or supplies a compatible runtime.This skill only routes and locks. Semantic editing is not a silent switch to GENERATE: it remains an EDIT/AUTO job with a signed billable video edit segment and explicit original/preservation boundary.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 19,869 | 27,629 | +39% | 1 | 1 | 0% | 3,400 | 4,972 | +46% | 0 | 0 | — |
case-02 | fail→pass | 14,930 | 15,744 | +5% | 1 | 1 | 0% | 2,274 | 4,044 | +78% | 0 | 0 | — |
case-03 | fail→pass | 16,310 | 14,978 | -8% | 1 | 1 | 0% | 2,756 | 4,154 | +51% | 0 | 0 | — |
case-04 | fail→pass | 15,933 | 14,311 | -10% | 1 | 1 | 0% | 2,548 | 3,808 | +49% | 0 | 0 | — |
case-05 | fail→pass | 17,671 | 16,329 | -8% | 1 | 1 | 0% | 2,714 | 4,102 | +51% | 0 | 0 | — |
case-06 | fail→pass | 12,545 | 6,746 | -46% | 1 | 1 | 0% | 1,855 | 2,503 | +35% | 0 | 0 | — |
case-07 | fail→pass | 9,439 | 4,677 | -50% | 1 | 1 | 0% | 1,430 | 2,315 | +62% | 0 | 0 | — |
case-08 | fail→pass | 11,567 | 5,229 | -55% | 1 | 1 | 0% | 1,776 | 2,400 | +35% | 0 | 0 | — |
case-09 | fail→pass | 12,229 | 12,656 | +3% | 1 | 1 | 0% | 2,072 | 3,562 | +72% | 0 | 0 | — |
case-10 | fail→pass | 13,016 | 7,939 | -39% | 1 | 1 | 0% | 1,979 | 2,928 | +48% | 0 | 0 | — |
case-11 | pass→pass | 13,806 | 16,754 | +21% | 1 | 1 | 0% | 2,161 | 4,341 | +101% | 0 | 0 | — |
case-12 | pass→pass | 8,813 | 5,182 | -41% | 1 | 1 | 0% | 1,462 | 2,376 | +63% | 0 | 0 | — |
case-13 | fail→pass | 6,598 | 5,376 | -19% | 1 | 1 | 0% | 1,039 | 2,397 | +131% | 0 | 0 | — |
case-14 | fail→pass | 8,901 | 3,813 | -57% | 1 | 1 | 0% | 1,414 | 2,201 | +56% | 0 | 0 | — |
case-15 | pass→pass | 6,749 | 5,058 | -25% | 1 | 1 | 0% | 1,060 | 2,421 | +128% | 0 | 0 | — |
case-16 | fail→pass | 13,623 | 5,114 | -62% | 1 | 1 | 0% | 2,095 | 2,356 | +12% | 0 | 0 | — |
case-17 | fail→pass | 9,961 | 6,426 | -35% | 1 | 1 | 0% | 1,578 | 2,617 | +66% | 0 | 0 | — |
case-18 | pass→pass | 16,928 | 22,199 | +31% | 1 | 1 | 0% | 2,806 | 5,190 | +85% | 0 | 0 | — |
case-19 | pass→pass | 10,383 | 3,668 | -65% | 1 | 1 | 0% | 1,596 | 2,142 | +34% | 0 | 0 | — |
case-20 | fail→pass | 5,231 | 6,054 | +16% | 1 | 1 | 0% | 907 | 2,534 | +179% | 0 | 0 | — |
case-21 | fail→fail | 38,751 | 24,439 | -37% | 1 | 1 | 0% | 8,229 | 7,165 | -13% | 0 | 0 | — |
case-22 | fail→fail | 7,833 | 8,629 | +10% | 1 | 1 | 0% | 1,602 | 3,288 | +105% | 0 | 0 | — |
case-23 | pass→fail | 7,398 | 11,131 | +50% | 1 | 1 | 0% | 1,363 | 3,456 | +154% | 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. 23 cases were attempted. The headline lift of +61 percentage points is the difference between those two pass rates over the 23 comparable cases. 2 cases got worse with the skill loaded, and they are 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.