Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/S3YED/appie-kitnpx agentmods add skills/s3yed/appie-kit/srt-subtitlesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/s3yed/appie-kit/srt-subtitles)<a href="https://agentmods.dev/skills/s3yed/appie-kit/srt-subtitles"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/srt-subtitles/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/s3yed/appie-kit/srt-subtitles"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/srt-subtitles.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.00444 |
| Opus 5 | $0.00029 | $0.00222 |
| Sonnet 5 | $0.00012 | $0.00089 |
| Haiku 4.5 | $0.00006 | $0.00044 |
Grade A, and why
srt-subtitles scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
File format
1
00:00:01,500 --> 00:00:04,000
This is the subtitle text
← lege regel
2
00:00:05,000 --> 00:00:08,500
Line one
Line two ← meerdere regels toegestaan
- Sequentiële nummers (1, 2, 3...)
- Timestamps:
HH:MM:SS,mmm --> HH:MM:SS,mmm - Tekst: plain text, kan
<i>,<b>,<font>HTML-tags bevatten - Blokken gescheiden door lege regel (
\n\n)
How to read
SRT is plain text — no converter needed.
# From Drive
gog drive download <FILE_ID> --out /tmp/sub.srt && cat /tmp/sub.srt
# Local file
cat file.srt
read_file path="file.srt"
Parsed output (script)
cat file.srt | python3 scripts/parse-srt.py
Returns JSON array:
[
{"seq": 1, "start": "00:00:01,500", "end": "00:00:04,000", "text": "Hello"},
{"seq": 2, "start": "00:00:05,000", "end": "00:00:08,500", "text": "Line one\\nLine two"}
]
Use cases
- Extract text from video subtitles for search/indexing
- Translate subtitles (feed parsed text to LLM)
- Repurpose subtitle text for content
- Transcript extraction from video content in Drive===ME:srt-subtitles
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 59 lines · 58 tokens per session scan A 7ced47688967
srt-subtitles is a skill published in the GitHub repository S3YED/appie-kit (9 stars, last pushed 17d ago), licensed MIT. It adds 58 tokens to every session and 444 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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