World Monitor
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 97 tools.
Check, fix, convert and retime SRT and WebVTT captions against Netflix, BBC and DCMP limits.
选择你使用的 AI 应用,然后复制设置。
通过 3/3 项检查 · 在你的电脑上运行
第一步:你用哪个 AI?
选择你用的应用,步骤会显示在下方。
可连接 Claude,但需要先准备
不需要密钥,不用安装程序 · 仅限电脑上的 Claude 应用(Windows 或 Mac),网页和手机不可用
用 Caption Checker 告诉我你能帮我做什么,然后做一件给我看✓ 如果 Claude 说正在使用 Caption Checker,或回答中出现 Caption Checker 的工具名称,就表示连接成功
菜单名称已于 2026年11月11日 对照 Anthropic 帮助页面核实 · 你的界面可能因版本略有不同
ChatGPT 暂时无法连接 Caption Checker
Caption Checker 需要安装在你的电脑上,而 ChatGPT 只能连接在网上运行的服务器
A · 使用能连接 Caption Checker 的应用
B · 其他 类中能连接 ChatGPT 的其他服务器
从同类中使用较多的里挑选,仅限用地址即可连接、无需密钥的
Claude Code 暂时无法连接 Caption Checker
开发者只提供了电脑版 Claude 应用的安装文件
A · 使用能连接 Caption Checker 的应用
Cursor 暂时无法连接 Caption Checker
开发者只提供了电脑版 Claude 应用的安装文件
A · 使用能连接 Caption Checker 的应用
VS Code 暂时无法连接 Caption Checker
开发者只提供了电脑版 Claude 应用的安装文件
A · 使用能连接 Caption Checker 的应用
依据这个服务器的连接方式和各应用自己的文档,检查于 2026年11月10日。
在你的电脑上运行,适用于
ClaudeGooseLM StudioMsty StudioCherry StudioVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月14日
注册名称已通过 GitHub 账户 markksantos 验证,该账户拥有此仓库
代码最后更新于13天前
使用 MIT
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
提问、分享技巧或报告无法使用。按“有帮助”数量排序。
还没有评价
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 3 项适用的基础检查中通过了 3 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于13天前,最新版本(1.3.3)于13天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 MCPB。
同一分类中有:World Monitor, Claude Flow, Windmill
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 97 tools.
AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Check SRT and WebVTT captions against a published caption standard: Netflix English, the BBC subtitle guidelines or the DCMP Captioning Key. It flags captions that read too fast, lines that are too long, too many lines, captions that stay on screen too short or too long, gaps under the minimum, overlaps and broken timestamps. It can also fix those, convert SRT to WebVTT and back, and retime a file that's out of sync.
No dependencies. Node 18+. The same checker runs in the browser, with no install and no upload, at [markstudios.com/tools/caption-checker](https://www.markstudios.com/tools/caption-checker).
$ caption-check examples/travel-vlog.srt
travel-vlog.srt: 2 of 8 captions meet Netflix English, adult programs #1 0:00.500 -> 0:03.000 Welcome back to the channel. ✗ Gap to the next caption is 0 frames at 24 fps (minimum 2) #3 0:06.600 -> 0:07.100 First, ✗ On screen 0.50 s (minimum 5/6 of a second) #4 0:07.200 -> 0:09.000 we packed water, snacks, a rain jacket and a spare battery for the cam ✗ Reading speed 41.1 characters a second (limit 20) ✗ Line 1 is 74 characters (limit 42) ...
Each limit was read on the standard's own page on 2026-10-15.
| Netflix (English) | BBC | DCMP Captioning Key | |
|---|---|---|---|
| Reading speed | Up to 20 characters a second (adult), 17 (children’s) | 160–180 words a minute | Up to 130 / 140 / 160 words a minute (lower / middle / upper level) |
| Characters a line | 42 | 37 on broadcast (Teletext) | No character count |
| Lines a caption | 2 | 2; 3 for vertical 9:16 video | No more than 2 preferred |
| Shortest time on screen | 5/6 of a second | About 0.3 s a word (advice) | 40 frames (1 second and 10 frames) |
| Longest time on screen | 7 seconds | No number | 6 seconds |
| Gap between captions | 2 frames minimum; gaps under 0.5 s closed to 2 frames | If you leave a gap, at least 1 second (advice) | No rule |
Sources: Netflix English (USA) Timed Text Style Guide · Netflix General Requirements · Netflix Subtitle Timing Guidelines · BBC Subtitle Guidelines · DCMP Captioning Key: Text · DCMP Captioning Key: Presentation Rate
How it counts. Characters include letters, spaces and punctuation, but not line breaks or formatting ( tags, {\an8} codes, WebVTT voice spans). Reading speed is characters ÷ (out-time − in-time). Words are runs of characters that hold a letter or a digit, so speaker labels and sound tags count, as DCMP asks. Gaps run from one caption's out-time to the next caption's in-time, in frames at the frame rate you give. Anything a standard words as a recommendation is reported as advice, not as a failure.
npx github:markksantos/caption-checker#v1.3.3 captions.srt
caption-check [more files] [options] -s, --standard netflix | netflix-kids | bbc | dcmp-upper | dcmp-middle | dcmp-lower (default: netflix) -f, --fps frame rate for frame-gap checks (default: 24) --vertical 9:16 video (the BBC allows three lines) --json JSON output --advice also print advice-only notes --fix write a fixed copy to (one input file) --mcp run as an MCP server on stdio
caption-check --to vtt|srt [--speakers] [--crlf] [--out ] convert caption-check --shift [--from ] | --start-at | --rate | --sync [--to vtt|srt] [--out ] retime
It exits with 1 when any caption breaks a limit, so it works as a CI check before captions ship.
--fix writes a copy with every fix that doesn't need a person: it never changes a word or an in-time.
$ caption-check examples/travel-vlog.srt --fix fixed.srt
travel-vlog.srt: 8 changes in 7 captions, written to fixed.srt #1 Out-time 0:03.000 -> 0:02.916 (to leave 2 frames before the next caption) #4 Rewrapped to 2 lines (38 + 35 characters) #5 Out-time 0:17.000 -> 0:16.100 (off an overlap, to the 7 s maximum) ... Left for a person (2): #3 Still on screen only 0.52 s (minimum 5/6 of a second) with no free time after it: merge it with a neighbor or move the next caption #4 Still reads at 40.2 characters a second (limit 20) with no free time after it: split it, condense it or move the next caption fixed.srt: 6 of 8 captions meet Netflix English, adult programs (before: 2 of 8)
Run against 300 caption files with all six standards, it never changed a word, an in-time or the number of captions, and never left more captions failing than it started with.
--to converts SubRip to WebVTT or back; the retiming flags fix captions that are out of sync with the video. Without --out, the file goes to stdout and the summary to stderr.
$ caption-check examples/travel-vlog.srt --to vtt --out travel-vlog.vtt
travel-vlog.srt: 8 captions converted from SubRip (.srt) to WebVTT (.vtt). Written to travel-vlog.vtt $ caption-check episode.srt --shift -2.5 --from 120 --out episode.synced.srt # late by 2.5 s from caption 120 on $ caption-check film.srt --rate 23.976:25 --out film.25fps.srt # timed for 23.976 fps, video is 25 fps $ caption-check film.srt --sync 1=0:04.200,640=41:12.5 --out film.synced.srt # pin two captions, stretch the rest
{\an8}-style position codes become WebVTT line/align settings and back; & and < are escaped for WebVTT and unescaped for SubRip; voice tags become "Name: " with --speakers. Whatever the other format can't hold (font colours, NOTE blocks, WebVTT position or size) is listed, not silently dropped.It uses the same reader and writer as the online SRT to VTT converter and subtitle time shifter (subtitles.js is that code, unchanged). Run on 300 caption files (34,836 captions), SRT to WebVTT and back kept every caption's timing, and a shift there and back restored every time.
const { parse, check, fix } = require('caption-checker');
const result = check(parse(fs.readFileSync('captions.vtt', 'utf8')), 'bbc', { vertical: true }); console.log(result.flagged, 'of', result.cues.length, 'captions break a limit'); for (const cue of result.cues) for (const issue of cue.issues) console.log(cue.n, issue.severity, issue.message);
const fixed = fix(fs.readFileSync('captions.srt', 'utf8'), 'netflix', { fps: 25 }); fs.writeFileSync('captions.fixed.srt', fixed.text); // also: fixed.changes, fixed.unresolved, fixed.before, fixed.after
const { convert, retime } = require('caption-checker/convert.js'); const vtt = convert(srtText, 'vtt'); // { text, from, to, captions, notes } const synced = retime(srtText, { rate: { from: 23.976, to: 25 } }); // or { offset: '-2.5', from: 120 }, { startAt: { caption, time } }, { sync: [a, b] }
check() accepts a standard id or your own standard object with the same fields as STANDARDS in index.js.
The same checks run as an MCP server, so Claude, Cursor, VS Code and other MCP clients can check a caption file mid-task. Five tools: check_captions (a file path or pasted SRT/VTT text, a standard, fps, vertical), fix_captions (the same arguments; returns the fixed file and what changed), convert_captions (SRT to WebVTT or back), retime_captions (offset, start at, frame-rate change or two-point sync) and list_standards (each limit and the page it comes from). It runs locally: no key, no network.
# Claude Code plugin (MCP server + a caption QA skill)
/plugin marketplace add markksantos/caption-checker /plugin install caption-checker@caption-checker
claude mcp add caption-checker -- npx -y github:markksantos/caption-checker#v1.3.3 --mcp
Other clients:
{ "mcpServers": { "caption-checker": { "command": "npx", "args": ["-y", "github:markksantos/caption-checker#v1.3.3", "--mcp"] } } }
The skill in skills/caption-checker/SKILL.md tells an agent which standard to pick, how to report results and how to fix a caption without changing its words. skills/caption-fixer/SKILL.md covers fixing a file: what fix_captions changes, and what to do with the captions it leaves for a person. skills/caption-converter/SKILL.md covers converting between SRT and WebVTT and working out which kind of timing fix an out-of-sync file needs.
study/ holds the code and data behind the caption reading speed study: 339,521 captions in 387 NASA videos and MIT OpenCourseWare lectures, measured with this library.
study-auto-captions/ holds the YouTube auto-caption accuracy study: automatic vs human captions on 299 videos, plus caption coverage of the most-subscribed channels.
study-dubbing/ holds the YouTube dubbing study: every audio track on 485 videos from the 97 most-subscribed channels, split into the channels' own dubs and YouTube's automatic ones.
study-video-length/ holds the YouTube video length study: durations of 2,859 latest videos and the Shorts share of 1,484 recent uploads on the most-subscribed channels.