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 BlackBeltTechnology/pi-agent-dashboard --skill video-transcriptiongit clone --depth 1 https://github.com/BlackBeltTechnology/pi-agent-dashboardWrote 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/blackbelttechnology/pi-agent-dashboard/video-transcription)<a href="https://agentmods.dev/skills/blackbelttechnology/pi-agent-dashboard/video-transcription"><img src="https://agentmods.dev/badge/skills/blackbelttechnology/pi-agent-dashboard/video-transcription/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/blackbelttechnology/pi-agent-dashboard/video-transcription"><img src="https://agentmods.dev/badge/skills/blackbelttechnology/pi-agent-dashboard/video-transcription.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Output Handling · line 69 Output size or generation rate is not bounded. Unbounded output enables denial-of-service through resource exhaustion, log flooding, or context-window stuffing.Fix: Set explicit limits on output length, generation count, and rate. Use max_tokens and truncation to prevent unbounded output.
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 | $0.00093 | $0.01685 |
| Opus 5 | $0.00046 | $0.00843 |
| Sonnet 5 | $0.00019 | $0.00337 |
| Haiku 4.5 | $0.00009 | $0.00169 |
Grade A, and why
video-transcription 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 7d 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Transcription
Transcribe video and audio files in-place to SRT subtitle format with speaker
diarization. Backed by the pi-transcribe CLI (a TypeScript port of the
original standalone skill — no Python).
Two backends. Soniox is the default and writes <name>.srt. AssemblyAI is
opt-in via TRANSCRIBE_BACKEND=assemblyai, uses the EU endpoint, and writes
<name>.diarize.srt — a different suffix, so both can transcribe the same file
and you can compare diarization side by side.
TRANSCRIBE_BACKEND=both runs them in one pass: audio is extracted once and
fed to both APIs, producing <name>.srt and <name>.diarize.srt together. Use
this when the user asks to compare diarization or wants both transcripts.
Usage
Run the pi-transcribe bin, optionally passing a directory or file paths.
Output .mp3 (extracted audio) and .srt (subtitles) files are placed
alongside the source files.
pi-transcribe [directory | file ...]
- No argument: scans
~/Movies(default) - Single directory: scans the specified directory (e.g. a Google Recorder
.m4aexport folder) - One or more file paths: transcribes exactly those files
Examples:
/transcribe— transcribe all untranscribed files in~/Movies/transcribe /path/to/recordings— transcribe files in a specific directorypi-transcribe "~/Movies/May 28 at 4-04 PM.m4a" "~/Movies/Feb 2 at 5-05 PM.m4a"— transcribe specific filesTRANSCRIBE_BACKEND=assemblyai pi-transcribe ~/Movies— use AssemblyAI instead of Soniox (writes.diarize.srt, needsASSEMBLY_AI_KEY)TRANSCRIBE_BACKEND=both pi-transcribe ~/Movies— run BOTH backends in one pass (writes.srt+.diarize.srt; needs both keys)TRANSCRIBE_BACKEND=assemblyai TRANSCRIBE_LANGUAGE=hu pi-transcribe file.m4a— pin Hungarian instead of auto-detectingMAX_CHUNK_HOURS=4 pi-transcribe ~/Movies— change the long-recording chunk size (default 4.5h Soniox / 9h AssemblyAI)TRANSCRIBE_CONCURRENCY=4 pi-transcribe ~/Movies— change how many files transcribe in parallel (default 8)
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.
- 7d ago Changed · +29 lines · -4 tokens per session 4e73ab5921e3
- 9d ago First seen · 84 lines · 97 tokens per session scan A 081dc2015b0b
video-transcription is a skill published in the GitHub repository BlackBeltTechnology/pi-agent-dashboard (280 stars, last pushed today), licensed MIT. It adds 93 tokens to every session and 1,685 once invoked, about $0.0005 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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