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/sacredvoid/skillkit/video-audio-processornpx skills add sacredvoid/skillkit --skill video-audio-processorgit clone --depth 1 https://github.com/sacredvoid/skillkitWhat 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 | $0.00064 | $0.03120 |
| Opus 5 | $0.00032 | $0.01560 |
| Sonnet 5 | $0.00013 | $0.00624 |
| Haiku 4.5 | $0.00006 | $0.00312 |
Grade B, and why
video-audio-processor scanned grade B 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 yesterday.
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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
| Ubuntu/Debian | `sudo apt update && sudo apt install -y ffmpeg` | How it starts
The opening of the file, as written. The whole thing — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video/Audio Processor
Process video and audio recordings into text transcripts and visual frame captures for analysis. Auto-detects your hardware and picks the optimal transcription model, device, and settings.
Phase 0: Detect Compute Environment
Run this at the start of every invocation. It determines everything downstream.
python3 -c "
import platform, shutil, subprocess, json
info = {'os': platform.system(), 'arch': platform.machine(), 'ram_gb': 0, 'gpu': 'none', 'vram_gb': 0, 'device': 'cpu', 'dtype': 'float32'}
# RAM
try:
if platform.system() == 'Darwin':
import os; info['ram_gb'] = round(os.sysconf('SC_PAGE_SIZE') * os.sysconf('SC_PHYS_PAGES') / (1024**3))
elif platform.system() == 'Linux':
with open('/proc/meminfo') as f:
for line in f:
if line.startswith('MemTotal'):
info['ram_gb'] = round(int(line.split()[1]) / (1024**2))
break
else:
import ctypes
mem = ctypes.c_ulonglong(0)
ctypes.windll.kernel32.GetPhysicallyInstalledMemory(ctypes.byref(mem))
info['ram_gb'] = round(mem.value / (1024**2))
except: pass
# GPU detection
try:
import torch
if torch.cuda.is_available():
info['gpu'] = torch.cuda.get_device_name(0)
info['vram_gb'] = round(torch.cuda.get_device_properties(0).total_mem / (1024**3))
info['device'] = 'cuda'
info['dtype'] = 'float16'
elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
info['gpu'] = 'Apple Silicon (MPS)'
info['vram_gb'] = info['ram_gb'] # unified memory
info['device'] = 'mps'
info['dtype'] = 'float16'
elif hasattr(torch, 'hip') or 'AMD' in str(getattr(torch, '_C', '')):
info['gpu'] = 'AMD (ROCm)'
info['device'] = 'cuda' # ROCm uses cuda API
info['dtype'] = 'float16'
except ImportError:
pass
# ffmpeg detection
info['ffmpeg'] = shutil.which('ffmpeg') is not None
info['ffprobe'] = shutil.which('ffprobe') is not None
print(json.dumps(info))
"
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.
- yesterday First seen · 318 lines · 64 tokens per session scan B e367e328985e
video-audio-processor is a skill published in the GitHub repository sacredvoid/skillkit (10 stars, last pushed 5mo ago), licensed MIT. It adds 64 tokens to every session and 3,120 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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