Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add gabrielmoreira/agent-skills-mirror --skill karaoke-captionsgit clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirrorWrote 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/gabrielmoreira/agent-skills-mirror/karaoke-captions)<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/karaoke-captions"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/karaoke-captions/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/gabrielmoreira/agent-skills-mirror/karaoke-captions"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/karaoke-captions.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 | $0.00064 | $0.00844 |
| Opus 5.5 | $0.00026 | $0.00338 |
| Sonnet 5.5 | $0.00013 | $0.00169 |
| Haiku 4.5 | $0.00006 | $0.00084 |
Grade A, and why
karaoke-captions 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Karaoke Captions Skill
Generate dynamic, TikTok/Shorts-style karaoke captions with word-level highlight sweeps using ASS subtitles and FFmpeg libass. Supports style matching from a reference screenshot.
Scripts, presets, and references live next to this skill. Run the commands from the skill directory (or pass absolute paths).
Requirements
- macOS with Apple Silicon (MLX Whisper)
- Python 3.10+
- FFmpeg with
libass(brew install ffmpeg)
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
reference.png --------(match_style_from_image.py)--------> style.json --+
+--(gen_ass.py)--> captions.ass --(render.sh)--> output.mp4
input.mp4 ---------------------------------->(extract_words.py)--> words.json --+
File Architecture
| File | Purpose | Role |
|---|---|---|
input.mp4 |
Source video | Input |
reference.png |
Style reference image (optional) | Visual Prompt |
words.json |
Word-level timestamps [{"word": ..., "start": ..., "end": ...}] |
Persistent Raw Data |
style.json |
Font, size, highlight color, outline, soft shadow, margin, words per line | Style Config |
captions.ass |
ASS subtitle script with two-layer blurred drop shadow and inline color overrides | Generated Intermediate |
output.mp4 |
Final video with burned-in subtitles | Output Deliverable |
Standard Workflow
Step 1. Extract Word Timestamps
python scripts/extract_words.py \
input.mp4 words.json \
--model mlx-community/whisper-large-v3-turbo
(For Chinese videos, add --language zh).
Step 2. Select Style or Auto-match from Reference Image
- From Reference Image:
python scripts/match_style_from_image.py \ reference.png style.json --video input.mp4 - From Presets:
presets/style.json: Default neon green highlight (#00FF00), Arial Black, all-caps, 4 words/line.presets/yellow.json: Yellow highlight (#FFFF00), Arial Black, all-caps.
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- .gitignore 269 B
- presets/style.json 369 B
- presets/yellow.json 369 B
- README.md 1.7 KB
- references/style-guide.md 2.7 KB
- requirements.txt 25 B
- scripts/extract_words.py 2.0 KB runs code
- scripts/gen_ass.py 7.3 KB runs code
- scripts/match_style_from_image.py 4.2 KB runs code
- scripts/render.sh 1.3 KB runs code
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.
- 1mo ago First seen · 111 lines · 64 tokens per session scan A af11b1ce69ca
karaoke-captions is a skill published in the GitHub repository gabrielmoreira/agent-skills-mirror (19 stars, last pushed yesterday), licensed MIT. It adds 64 tokens to every session and 844 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-17.
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