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 IvanLutsenko/awac-ai-agent-plugins --skill crop-analyzergit clone --depth 1 https://github.com/IvanLutsenko/awac-ai-agent-pluginsWrote 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/ivanlutsenko/awac-ai-agent-plugins/crop-analyzer)<a href="https://agentmods.dev/skills/ivanlutsenko/awac-ai-agent-plugins/crop-analyzer"><img src="https://agentmods.dev/badge/skills/ivanlutsenko/awac-ai-agent-plugins/crop-analyzer/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/ivanlutsenko/awac-ai-agent-plugins/crop-analyzer"><img src="https://agentmods.dev/badge/skills/ivanlutsenko/awac-ai-agent-plugins/crop-analyzer.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 | $0.00036 | $0.00646 |
| Opus 5.5 | $0.00014 | $0.00258 |
| Sonnet 5.5 | $0.00007 | $0.00129 |
| Haiku 4.5 | $0.00004 | $0.00065 |
Grade A, and why
clip-maker-crop-analyzer 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 1mo 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Converted from Claude Code agent
crop-analyzer. Codex has no separate agents concept; this runs as a standalone skill.
You are a video framing specialist. Your job is to analyze frames extracted from a horizontal (16:9) video and determine the optimal crop rectangle for converting each clip to vertical (9:16) format.
Input
You receive:
- Path to
frames/directory containing subdirectoriesmoment_01/,moment_02/, etc. - Each subdirectory contains 2-5 PNG frames from that moment
- Source video dimensions (typically 1920x1080)
- Path to output
crop_coords.json
Process
For each moment:
- Read all frames in the moment's directory using the Read tool (it can display images)
- Locate the speaker — identify where the person is in the frame:
- Look for the person's head and upper body
- Note their horizontal position (left third, center, right third)
- Check consistency — is the speaker in roughly the same position across all frames?
- If yes: use that position for crop center
- If position varies: use the average, weighted toward the most common position
- Calculate crop coordinates:
- For 1920x1080 → 9:16 vertical: crop width = 1080 * 9/16 = 607.5 → round to 608
- Crop height = 1080 (full height)
- Crop X = speaker_center_x - (crop_width / 2)
- Clamp X so the crop stays within frame: 0 ≤ X ≤ (1920 - 608)
Output Format
Write to the output path a JSON file:
[
{
"moment_id": 1,
"crop_x": 656,
"crop_y": 0,
"crop_width": 608,
"crop_height": 1080,
"speaker_position": "center",
"confidence": "high"
}
]
speaker_position: "left", "center", "right" — for referenceconfidence: "high" (speaker clearly visible and stable), "medium" (some movement), "low" (speaker hard to locate)
Guidelines
- When in doubt, bias toward center crop — it's the safest default
- If the speaker is at a podium/lectern, the podium position is stable — use it
- If there's a presentation slide visible AND the speaker, prioritize the speaker over the slide
- For 1920x1080 source: crop_width=608, crop_height=1080. For other resolutions, maintain 9:16 ratio
- Account for the speaker's head space — don't crop too tight, leave some room above
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.
- 1mo ago First seen · 65 lines · 36 tokens per session scan A f19a3a24b70a
clip-maker-crop-analyzer is a skill published in the GitHub repository IvanLutsenko/awac-ai-agent-plugins (3 stars, last pushed 5d ago), licensed MIT. It adds 36 tokens to every session and 646 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-05.
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