acquire-codebase-knowl…
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like…
Check SRT or WebVTT captions and subtitles against published standards (Netflix English, BBC subtitle guidelines, DCMP Captioning Key) for reading speed, line length, line count, time on screen, gaps and overlaps, then fix failures by retiming before rewording. Use when asked to
$ npx -y skills add github/awesome-copilot --skill caption-qa --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/caption-qaContext preview
The summary Claude sees to decide when to auto-load this skill.
Check SRT or WebVTT captions and subtitles against published standards (Netflix English, BBC subtitle guidelines, DCMP Captioning Key) for reading speed, line length, line count, time on screen, gaps and overlaps, then fix failures by retiming before rewording. Use when asked to
name: caption-qa description: 'Check SRT or WebVTT captions and subtitles against published standards (Netflix English, BBC subtitle guidelines, DCMP Captioning Key) for reading speed, line length, line count, time on screen, gaps and overlaps, then fix failures by retiming before rewording. Use when asked to QA, lint or validate captions, check whether subtitles read too fast, prepare captions for Netflix, broadcast or educational delivery, or add a caption check to CI.' license: MIT
Captions fail delivery and accessibility review on numbers: characters a second, characters a line, time on screen and the gap between captions. Each standard publishes its own limits, and they differ, so "are these captions OK?" has no answer until you know where they are going. This skill picks the right set of limits, measures every cue the same way the published limits are written, and fixes failures without cutting the speaker's words.
If the user names no target, use Netflix English (adult) and say that you did.
| Standard | Reading speed | Line length | Lines | Time on screen | Gap between captions | |---|---|---|---|---|---| | Netflix English, adult | 20 characters a second | 42 characters | 2 | 5/6 s to 7 s | At least 2 frames; close gaps under 0.5 s to 2 frames | | Netflix English, children's | 17 characters a second | 42 characters | 2 | 5/6 s to 7 s | Same as adult | | BBC subtitle guidelines | 160-180 words a minute; aim for about 0.3 s a word | 37 characters (broadcast); online, 68% of the width of a 16:9 frame | 2 | - | If you leave a gap, at least 1 s, preferably 1.5 s | | DCMP Captioning Key (US educational media) | 130 / 140 / 160 words a minute for lower / middle / upper level | - | 2 (preferred) | 40 frames (1 s 10 frames) to 6 s | - |
Sources: [Netflix English (USA) Timed Text Style Guide](https://partnerhelp.netflixstudios.com/hc/en-us/articles/217350977-English-USA-Timed-Text-Style-Guide), [Netflix subtitle timing guidelines](https://partnerhelp.netflixstudios.com/hc/en-us/articles/360051554394-Timed-Text-Style-Guide-Subtitle-Timing-Guidelines), [BBC subtitle guidelines](https://www.bbc.co.uk/accessibility/forproducts/guides/subtitles/), [DCMP Captioning Key: text](https://dcmp.org/learn/597-captioning-key---text) and [presentation rate](https://dcmp.org/learn/601-captioning-key---presentation-rate). The BBC's per-word time and minimum gap are guidance, so report them as suggestions, not failures.
1. **Find the target** (platform, broadcaster or audience level) and pick the standard from the table. 2. **Measure every cue**, or run the command-line check below and read its output. 3. **Report** with a count line first ("212 of 240 captions meet Netflix English, adult"). Then group failures by rule, with cue numbers and timecodes. Show the first few cues of each kind instead of hundreds of lines. 4. **Fix, keeping the words**, in this order: 1. Extend the out-time into the following gap, keeping the minimum gap. 2. Start the cue earlier if the previous cue ends well before it. 3. Split a long cue into two at a phrase boundary, each one meeting the minimum time on screen. 4. Merge a flash cue (under the minimum time) into its neighbor. 5. Re-break lines: break after punctuation or before a conjunction or preposition, and keep an article with its noun and a first name with a last name. 6. Edit the wording only when the user asks for edited (not verbatim) captions. 5. **Measure again** after fixing. A retime can create a new overlap or a gap under the minimum.
When the user wants a repeatable check (a folder of files, or CI), write this script, or adapt it to the chosen standard. It applies the Netflix adult limits from the table, prints each failing caption and exits with 1 when any caption fails, so it can gate a build. It needs only Python 3.
import re
import sys
# Netflix English, adult programs. Change these for another standard.
LIMITS = {"cps": 20, "cpl": 42, "lines": 2, "min_s": 5 / 6, "max_s": 7, "gap_frames": 2}
FPS = 24
T = r"(?:(\d+):)?(\d{1,2}):(\d{1,2})[,.](\d{1,3})"
TIMING = re.compile(T + r"\s*-->\s*" + T)
TAGS = re.compile(r"<[^>]+>|\{\\[^}]*\}")
def seconds(h, m, s, ms):
return int(h or 0) * 3600 + int(m) * 60 + int(s) + int((ms + "00")[:3]) / 1000
def read_cues(path):
text = open(path, encoding="utf-8-sig").read().replace("\r\n", "\n")
for block in re.split(r"\n[ \t]*\n", text):
lines = block.strip().split("\n")
for i, line in enumerate(lines[:3]):A community-created collection of custom agents, instructions, skills, hooks, workflows, and plugins to supercharge your GitHub Copilot experience.
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