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 boshi-xixixi/TraeSkill --skill automate-thisgit clone --depth 1 https://github.com/boshi-xixixi/TraeSkillWrote 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/boshi-xixixi/traeskill/automate-this)<a href="https://agentmods.dev/skills/boshi-xixixi/traeskill/automate-this"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/automate-this/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/boshi-xixixi/traeskill/automate-this"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/automate-this.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 | $0.00054 | $0.02853 |
| Opus 5 | $0.00027 | $0.01426 |
| Sonnet 5 | $0.00011 | $0.00571 |
| Haiku 4.5 | $0.00005 | $0.00285 |
Grade D, and why
automate-this scanned grade D with 3 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
chmod 700 "$WORK_DIR" Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf "$WORK_DIR" Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
echo "=== Common Tools ===" && for cmd in curl jq playwright selenium osascript automator crontab; do command -v $cmd >/dev/null 2>&1 && echo "$cmd: yes" || echo "$cmd: no"; done How it starts
The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Automate This
Analyze a screen recording of a manual process and build working automation for it.
The user records themselves doing something repetitive or tedious, hands you the video file, and you figure out what they're doing, why, and how to script it away.
Prerequisites Check
Before analyzing any recording, verify the required tools are available. Run these checks silently and only surface problems:
command -v ffmpeg >/dev/null 2>&1 && ffmpeg -version 2>/dev/null | head -1 || echo "NO_FFMPEG"
command -v whisper >/dev/null 2>&1 || command -v whisper-cpp >/dev/null 2>&1 || echo "NO_WHISPER"
- ffmpeg is required. If missing, tell the user:
brew install ffmpeg(macOS) or the equivalent for their OS. - Whisper is optional. Only needed if the recording has narration. If missing AND the recording has an audio track, suggest:
pip install openai-whisperorbrew install whisper-cpp. If the user declines, proceed with visual analysis only.
Phase 1: Extract Content from the Recording
Given a video file path (typically on ~/Desktop/), extract both visual frames and audio:
Frame Extraction
Extract frames at one frame every 2 seconds. This balances coverage with context window limits.
WORK_DIR=$(mktemp -d "${TMPDIR:-/tmp}/automate-this-XXXXXX")
chmod 700 "$WORK_DIR"
mkdir -p "$WORK_DIR/frames"
ffmpeg -y -i "<VIDEO_PATH>" -vf "fps=0.5" -q:v 2 -loglevel warning "$WORK_DIR/frames/frame_%04d.jpg"
ls "$WORK_DIR/frames/" | wc -l
Use $WORK_DIR for all subsequent temp file paths in the session. The per-run directory with mode 0700 ensures extracted frames are only readable by the current user.
If the recording is longer than 5 minutes (more than 150 frames), increase the interval to one frame every 4 seconds to stay within context limits. Tell the user you're sampling less frequently for longer recordings.
Audio Extraction and Transcription
Check if the video has an audio track:
ffprobe -i "<VIDEO_PATH>" -show_streams -select_streams a -loglevel error | head -5
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.
- 9d ago First seen · 245 lines · 54 tokens per session scan D 4f45d8a3ce3e
automate-this is a skill published in the GitHub repository boshi-xixixi/TraeSkill (262 stars, last pushed 3mo ago), licensed MIT. It adds 54 tokens to every session and 2,853 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it D with 3 findings (asks for root, recursive force delete, 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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