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 agentmods add skills/librefang/librefang-registry/clipnpx skills add librefang/librefang-registry --skill clipgit clone --depth 1 https://github.com/librefang/librefang-registryWhat 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 | $0.00028 | $0.04990 |
| Opus 5 | $0.00014 | $0.02495 |
| Sonnet 5 | $0.00006 | $0.00998 |
| Haiku 4.5 | $0.00003 | $0.00499 |
Grade A, and why
clip-hand-skill 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 3d 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 -s -X POST "https://api.groq.com/openai/v1/audio/transcriptions" \ This is a copy
100% identical to clip-hand-skill — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Clipping Expert Knowledge
Cross-Platform Notes
All tools (ffmpeg, ffprobe, yt-dlp, whisper) use identical CLI flags on Windows, macOS, and Linux. The differences are only in shell syntax:
| Feature | macOS / Linux | Windows (cmd.exe) |
|---|---|---|
| Suppress stderr | 2>/dev/null |
2>NUL |
| Filter output | | grep pattern |
| findstr pattern |
| Delete files | rm file1 file2 |
del file1 file2 |
| Null output device | -f null - |
-f null - (same) |
| ffmpeg subtitle paths | subtitles=clip.srt |
subtitles=clip.srt (relative OK, absolute needs C\\:/path) |
IMPORTANT: ffmpeg filter paths (-vf "subtitles=...") always need forward slashes. On Windows with absolute paths, escape the colon: subtitles=C\\:/Users/me/clip.srt
Prefer using file_write tool for creating SRT/text files instead of shell echo/heredoc.
yt-dlp Reference
Download with Format Selection
# Best video up to 1080p + best audio, merged
yt-dlp -f "bv[height<=1080]+ba/b[height<=1080]" --restrict-filenames -o "source.%(ext)s" "URL"
# 720p max (smaller, faster)
yt-dlp -f "bv[height<=720]+ba/b[height<=720]" --restrict-filenames -o "source.%(ext)s" "URL"
# Audio only (for transcription-only workflows)
yt-dlp -x --audio-format wav --restrict-filenames -o "audio.%(ext)s" "URL"
Metadata Inspection
# Get full metadata as JSON (duration, title, chapters, available subs)
yt-dlp --dump-json "URL"
# Key fields: duration, title, description, chapters, subtitles, automatic_captions
YouTube Auto-Subtitles
# Download auto-generated subtitles in json3 format (word-level timing)
yt-dlp --write-auto-subs --sub-lang en --sub-format json3 --skip-download --restrict-filenames -o "source" "URL"
# Download manual subtitles if available
yt-dlp --write-subs --sub-lang en --sub-format srt --skip-download --restrict-filenames -o "source" "URL"
# List available subtitle languages
yt-dlp --list-subs "URL"
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.
- 3d ago First seen · 475 lines · 28 tokens per session scan A 8367a34a9046
clip-hand-skill is a skill published in the GitHub repository librefang/librefang-registry (11 stars, last pushed 9d ago), licensed MIT. It adds 28 tokens to every session and 4,990 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to clip-hand-skill, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
agent-loop
Production Claude agent loop — Session/Harness/Registry/Tool abstraction, DRYRUN safety guard, APScheduler integration, dead-letter error handling, tool registry, and observability hooks for autonomous agent systems.
notion
Notion API for creating and managing pages, databases, and blocks. Use when the user wants to create a Notion page, query a Notion database, update Notion properties, search Notion, add content to Notion, manage Notion blocks, or interact with Notion data sources and workspaces via the API.
agentic-supply-chain-detection
Detect agentic supply-chain risks: compromised dependencies, malicious plugins/tools/models, and untrusted update sources.
skill-vetter
Security-first skill vetting for AI agents. Use before installing any skill from ClawdHub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns.
ondb
A logical analysis and reasoning tool for AI. Use when decomposing documents into structured knowledge, querying entities and relations, validating consistency, or indexing files. Trigger on "remember", "what do I know about", "link X to Y", "show dependencies", "analyze this document", entity CRUD, or cross-skill…
finding-protocol
Operational-tier finding template — minimal fields for sub-agent decision support. Heavyweight deliverable promotion lives in skills/decepticon/final-report.