扫描现有项目的代码与配置,生成涵盖技术栈、结构、架构、规范、集成、测试和风险的七份文档。为结论标注文件依据和未知项,并指出计划描述与实际实现的差异。
- 了解陌生代码库
- 准备项目交接文档
- 对照设计资料与实际实现
按 Netflix、BBC 或 DCMP 标准检查 SRT 和 WebVTT 字幕的阅读速度、行长、显示时长、间隔及重叠,并报告问题并协助调整时间和换行。
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.
实测评分 未实测
查看安装方法按照 Netflix English、BBC 字幕指南或 DCMP Captioning Key 检查 SRT 和 WebVTT 字幕。根据显示文字和持续时间测算阅读速度,并逐条报告行长、行数、屏幕显示时长、字幕间隔及重叠。未指定目标时,采用面向成人内容的 Netflix English 标准,并说明这一前提。发现问题后,优先保留说出的原话,再依次考虑延长显示时间、调整开始时间、在语义片段处拆分字幕或重新换行。修改后可以再次测量,也可编写可重复运行的 Python 3 检查程序并用于 CI。
字幕交付前需要确认是否符合标准、查明平台拒收原因,或为 Netflix、电视广播和美国教育媒体准备字幕时,可以使用此技能。它也适合定期检查多个文件,或在 CI 中发现不合格字幕。
支持的格式是 SRT 和 WebVTT。按帧判断字幕间隔需要帧率;未提供时假定为 24 fps。ASS 文件需先转换为 SRT。数值指标合格并不保证能通过字幕风格审核。
本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。
AI 根据 SKILL.md 的内容检查了需要注意的操作和使用前提。评分只依据实际运行的结果(实测对比)。
不计入评分。 由 AI(OpenAI Codex)于 2026年10月27日 评估。仅供参考,安装前请同时查看原文。
安装前可以查看交给 AI 代理的指令内容。
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.
.srt or .vtt file and asks whether it is ready to ship, or why a platform rejected it.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, Netflix subtitle timing guidelines, BBC subtitle guidelines, DCMP Captioning Key: text and presentation rate. The BBC's per-word time and minimum gap are guidance, so report them as suggestions, not failures.
<i>, <b>, {\an8}) or the cue number.00:00:01,000 (SRT) and 00:00:01.000 or 01.000 (WebVTT). Skip WebVTT NOTE, STYLE and REGION blocks, and treat cue settings after the timestamps (align:start) as part of the timing line.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]):
m = TIMING.search(line)
if m:
body = [TAGS.sub("", t).rstrip() for t in lines[i + 1:]]
g = m.groups()
yield seconds(*g[:4]), seconds(*g[4:]), [t for t in body if t.strip()]
break
def check(path, lim=LIMITS, fps=FPS):
cues, failed = list(read_cues(path)), 0
for n, (start, end, text) in enumerate(cues, 1):
dur, chars, issues = end - start, sum(len(t) for t in text), []
if dur > 0 and chars / dur > lim["cps"]:
issues.append(f"{chars / dur:.1f} characters a second")
issues += [f"line {j} is {len(t)} characters"
for j, t in enumerate(text, 1) if len(t) > lim["cpl"]]
if len(text) > lim["lines"]:
issues.append(f"{len(text)} lines")
if dur < lim["min_s"] or dur > lim["max_s"]:
issues.append(f"on screen {dur:.2f} s")
if n < len(cues):
gap = cues[n][0] - end
if gap < 0:
issues.append(f"overlaps the next caption by {-gap:.2f} s")
elif gap * fps < lim["gap_frames"] - 0.01:
issues.append(f"gap of {gap * fps:.0f} frames at {fps} fps")
if issues:
failed += 1
print(f"{path} #{n} {start:.3f} -> {end:.3f}: " + "; ".join(issues))
print(f"{path}: {len(cues) - failed} of {len(cues)} captions pass")
return failed == 0
if __name__ == "__main__":
results = [check(p) for p in sys.argv[1:]]
sys.exit(0 if results and all(results) else 1)
Run it as python3 check_captions.py captions/*.srt. For another standard, change LIMITS, and add a words-a-minute check (words divided by duration, times 60) for the BBC and DCMP. The script doesn't check the advice-level rules (chaining short gaps, the BBC's per-word time); report those separately.
In GitHub Actions:
- run: python3 check_captions.py captions/*.srt
ffmpeg -i subs.ass subs.srt, which keeps the timing and wraps the text in font tags that the character count ignores.还没有评价。欢迎分享你的使用感受。
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还没有评论。来写第一条吧。
扫描现有项目的代码与配置,生成涵盖技术栈、结构、架构、规范、集成、测试和风险的七份文档。为结论标注文件依据和未知项,并指出计划描述与实际实现的差异。
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