badlogic/pi-skills is a collection of reusable skills that extend pi-coding-agent and work with several other coding agents. Developers use it to give agents capabilities such as web search, browser automation, Google service access, transcription, VS Code integration, and YouTube transcript retrieval.
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 badlogic/pi-skills --skill transcribegit clone --depth 1 https://github.com/badlogic/pi-skillsWrote 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/badlogic/pi-skills/transcribe)<a href="https://agentmods.dev/skills/badlogic/pi-skills/transcribe"><img src="https://agentmods.dev/badge/skills/badlogic/pi-skills/transcribe/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/badlogic/pi-skills/transcribe"><img src="https://agentmods.dev/badge/skills/badlogic/pi-skills/transcribe.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00025 | $0.00275 |
| Opus 5 | $0.00013 | $0.00138 |
| Sonnet 5 | $0.00005 | $0.00055 |
| Haiku 4.5 | $0.00003 | $0.00028 |
Grade A, and why
transcribe scanned grade A with 1 finding 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 10d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- `curl` and `tar` What it actually says
Transcribe
Local speech-to-text using parakeet-cpp-transcribe on Apple Silicon macOS.
Usage
{baseDir}/transcribe.sh <audio-file>
The first run downloads the macOS arm64 binary from the latest badlogic/pibot GitHub release into the extension's ignored bin directory:
{extensionDir}/bin/parakeet-cpp-transcribe
({extensionDir} is the parent directory of this skill's {baseDir}.) The binary downloads its GGUF model automatically if missing.
Output
Plain text timestamped in 15 second chunks is written to stdout:
[00:00-00:15] transcript text
[00:15-00:30] more transcript text
Model/GGML diagnostic logs are written to stderr. Redirect stderr to hide them:
{baseDir}/transcribe.sh <audio-file> 2>/dev/null
Requirements
- Apple Silicon macOS only
curlandtarffmpegfor non-WAV input:brew install ffmpeg
What ships with it
2 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.
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.
- 10d ago First seen · 44 lines · 25 tokens per session scan A 45a996d4621a
transcribe is a skill published in the GitHub repository badlogic/pi-skills (2,508 stars, last pushed 3mo ago), licensed MIT. It adds 25 tokens to every session and 275 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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