World Monitor
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 104 tools.
Check, fix, convert and retime SRT and WebVTT captions against Netflix, BBC and DCMP limits.
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Passed 3/3 checks · Runs on your computer
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Works with Claude, with some setup first
No key, nothing to install · Only the Claude desktop app (Windows or Mac), not the web or phone
Download the maker’s .mcpb file
The .mcpb file comes straight from the maker; we do not change it
Use Caption Checker and tell me what you can do for me, then show me one thing✓ If Claude says it is using Caption Checker or shows a Caption Checker tool in the answer, you are connected
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ChatGPT cannot connect Caption Checker yet
Caption Checker runs on your computer, but ChatGPT can only connect servers that run on the web
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B · Others in Other that work with ChatGPT
Picked from the most used in the same category, only ones that connect by address with no key
Claude Code cannot connect Caption Checker yet
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Cursor cannot connect Caption Checker yet
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A · Use an app that can connect Caption Checker
VS Code cannot connect Caption Checker yet
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A · Use an app that can connect Caption Checker
mcpb: …/caption-checker-1.3.3.mcpbBased on how this server connects and on each app’s own docs, checked Nov 10, 2026.
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We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 13, 2026
The registry name was verified with the GitHub account markksantos, which owns the repo
Code last changed 12 days ago
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The GitHub repo last changed 12 days ago, and the latest version (1.3.3) reached the registry 12 days ago.
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In the same category: World Monitor, Claude Flow, Windmill
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Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 104 tools.
AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
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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.