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Get Started Free →Write or translate subtitles/captions that respect reading speed and timing rules. Use when asked to write subtitles, captions, SRT/VTT content, or to translate subtitles for a video. Produces properly-formatted, readable subtitles — line-length and reading-speed compliant, well-segmented, with translation that fits the time available, plus SDH/caption guidance where relevant.
.claude/skills/mohitagw15856-subtitle-caption/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-06 | ✗→✓ | ▲ Improved | 40% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 354% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 265% | 0% |
| case-18 | ✗→✓ | ▲ Improved | 310% | 0% |
| case-20 | ✗→✓ | ▲ Improved | 761% | 0% |
Subtitles fail when they're too long to read before they vanish, badly segmented, or a literal translation that overruns the timing. Good subtitling obeys real constraints: reading speed (≈17 chars/sec / ~160–180 wpm), line length (~42 chars), max 2 lines, and sentence-aware segmentation. This skill writes or translates captions to those rules — readable, well-timed, and condensed to fit.
Ask for these only if they aren't already provided:
The subtitles in the requested format (SRT/VTT), each cue:
[sound cues] (e.g. [door slams], [tense music]).Notes — where you condensed/cut and why, any cue that's tight on reading speed (a 🔴 flag to adjust timing), and segmentation choices.
Subtitling standards — reading-speed (CPS) limits, ~42-char lines, 2-line max, phrase-boundary segmentation, SDH conventions.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-02 | fail→fail | 7,879 | 12,424 | +58% | 1 | 1 | 0% | 289 | 1,766 | +511% | 0 | 0 | — |
case-01 | fail→fail | 36,085 | 8,741 | -76% | 1 | 1 | 0% | 4,919 | 1,300 | -74% | 0 | 0 | — |
case-03 | pass→pass | 18,844 | 18,716 | -1% | 1 | 1 | 0% | 2,489 | 2,999 | +20% | 0 | 0 | — |
case-04 | fail→fail | 12,412 | 10,432 | -16% | 1 | 1 | 0% | 869 | 1,451 | +67% | 0 | 0 | — |
case-05 | fail→fail | 11,499 | 31,400 | +173% | 1 | 1 | 0% | 1,298 | 4,721 | +264% | 0 | 0 | — |
case-06 | fail→pass | 17,468 | 15,661 | -10% | 1 | 1 | 0% | 1,919 | 2,688 | +40% | 0 | 0 | — |
case-07 | pass→pass | 55,036 | 26,926 | -51% | 1 | 1 | 0% | 7,959 | 4,940 | -38% | 0 | 0 | — |
case-08 | fail→fail | 4,652 | 6,162 | +32% | 1 | 1 | 0% | 623 | 1,937 | +211% | 0 | 0 | — |
case-09 | pass→pass | 13,484 | 6,873 | -49% | 1 | 1 | 0% | 1,310 | 1,775 | +35% | 0 | 0 | — |
case-10 | fail→fail | 21,502 | 37,084 | +72% | 1 | 1 | 0% | 3,409 | 7,320 | +115% | 0 | 0 | — |
case-11 | fail→pass | 3,862 | 12,784 | +231% | 1 | 1 | 0% | 463 | 2,100 | +354% | 0 | 0 | — |
case-12 | fail→fail | 13,076 | 17,231 | +32% | 1 | 1 | 0% | 1,908 | 2,845 | +49% | 0 | 0 | — |
case-13 | fail→fail | 13,254 | 14,705 | +11% | 1 | 1 | 0% | 1,299 | 2,145 | +65% | 0 | 0 | — |
case-14 | fail→pass | 3,950 | 4,723 | +20% | 1 | 1 | 0% | 408 | 1,489 | +265% | 0 | 0 | — |
case-15 | fail→fail | 2,367 | 5,326 | +125% | 1 | 1 | 0% | 249 | 1,546 | +521% | 0 | 0 | — |
case-16 | pass→pass | 6,889 | 8,261 | +20% | 1 | 1 | 0% | 1,278 | 1,967 | +54% | 0 | 0 | — |
case-17 | pass→pass | 14,700 | 16,798 | +14% | 1 | 1 | 0% | 1,728 | 2,892 | +67% | 0 | 0 | — |
case-18 | fail→pass | 3,679 | 13,732 | +273% | 1 | 1 | 0% | 528 | 2,166 | +310% | 0 | 0 | — |
case-19 | fail→fail | 2,241 | 9,054 | +304% | 1 | 1 | 0% | 333 | 1,417 | +326% | 0 | 0 | — |
case-20 | fail→pass | 2,307 | 9,889 | +329% | 1 | 1 | 0% | 290 | 2,498 | +761% | 0 | 0 | — |
case-21 | fail→fail | 3,930 | 9,404 | +139% | 1 | 1 | 0% | 628 | 2,086 | +232% | 0 | 0 | — |
case-22 | fail→fail | 1,595 | 4,415 | +177% | 1 | 1 | 0% | 237 | 1,470 | +520% | 0 | 0 | — |
case-23 | fail→pass | 15,760 | 9,446 | -40% | 1 | 1 | 0% | 1,469 | 2,377 | +62% | 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 +26 percentage points is the difference between those two pass rates over the 23 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.