clip-maker-crop-analyzer

clip-maker-crop-analyzer is a skill for Claude Code from IvanLutsenko/awac-ai-agent-plugins. It costs 36 tokens per session (646 once invoked), scanned A, original, MIT.

A video-frame analysis tool that finds a speaker's position and calculates how to crop a horizontal video into a vertical 9:16 clip.

In plain words
What is it for?
Reading extracted frame images, checking whether the speaker moves, and writing crop coordinates for each clip moment.
Why use it?
It helps keep the speaker in view when converting ordinary widescreen footage for vertical video.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions Claude Code; mentions Codex.

Part of the clip-maker plugin — 6 skills, 3 commands, 3 agents shipped together

Good fit Reading extracted frame images, checking whether the speaker moves, and writing crop coordinates for each clip moment.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ivanlutsenko/awac-ai-agent-plugins/crop-analyzer
Install

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.

Any agent
npx skills add IvanLutsenko/awac-ai-agent-plugins --skill crop-analyzer
Clone the repo
git clone --depth 1 https://github.com/IvanLutsenko/awac-ai-agent-plugins

Made for: Claude Code.

Or install clip-maker, the plugin that ships this one along with the rest of its 6 skills, 3 commands, 3 agents.

Wrote 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.

agentmods badge for clip-maker-crop-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/ivanlutsenko/awac-ai-agent-plugins/crop-analyzer/github.svg)](https://agentmods.dev/skills/ivanlutsenko/awac-ai-agent-plugins/crop-analyzer)
Your own site
<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.

agentmods 80×15 button for clip-maker-crop-analyzer

Your own site · 80×15
<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>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 646 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 1mo ago against content hash f19a3a24b70a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

plugins/clip-maker/skills/generated-from-agents/crop-analyzer/SKILL.md · 65 lines

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:

  1. Path to frames/ directory containing subdirectories moment_01/, moment_02/, etc.
  2. Each subdirectory contains 2-5 PNG frames from that moment
  3. Source video dimensions (typically 1920x1080)
  4. Path to output crop_coords.json

Process

For each moment:

  1. Read all frames in the moment's directory using the Read tool (it can display images)
  2. 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)
  3. 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
  4. 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 reference
  • confidence: "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

Read the full file on GitHub · 65 lines

Changes

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.

  1. 1mo ago First seen · 65 lines · 36 tokens per session scan A f19a3a24b70a

Subscribe to this mod's changes

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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