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 GzuPark/claude-plugin-pack --skill image-insightgit clone --depth 1 https://github.com/GzuPark/claude-plugin-packWrote 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/gzupark/claude-plugin-pack/image-insight)<a href="https://agentmods.dev/skills/gzupark/claude-plugin-pack/image-insight"><img src="https://agentmods.dev/badge/skills/gzupark/claude-plugin-pack/image-insight.svg" alt="Measured on agentmods" 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 | $0.00048 | $0.01028 |
| Opus 5 | $0.00024 | $0.00514 |
| Sonnet 5 | $0.00010 | $0.00206 |
| Haiku 4.5 | $0.00005 | $0.00103 |
Grade A, and why
image-insight 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 7d 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Insight
Overview
Analyze uploaded images and return structured JSON profiles containing composition, color, lighting, subject, and background analysis with actionable recreation parameters for AI image generation.
Triggers
image-insight- Primary trigger for image analysis- "analyze this image" - Natural language trigger
- "extract visual style" - Style extraction request
- "generate image profile" - Profile generation request
- "what's in this image" - Detailed breakdown request
Workflow
Step 1: Receive Image
Accept the uploaded image file. Verify it's a valid image format.
Step 2: Multi-Category Analysis
Analyze across all schema categories:
- metadata - Confidence, image type, purpose
- composition - Rule, layout, focal points, hierarchy
- color_profile - Dominant colors with hex, palette, temperature
- lighting - Type, direction, shadows, highlights
- technical_specs - Medium, style, texture, depth of field
- artistic_elements - Genre, influences, mood, atmosphere
- typography - Fonts, placement (if text present)
- subject_analysis - Expression, hair, hands, positioning
- background - Setting, surfaces, objects catalog
- generation_parameters - Recreation prompts, keywords
Step 3: Apply Critical Area Rules
For portraits, apply detailed analysis per references/critical-areas.md:
- Hair: exact length, cut style, natural imperfections
- Hands: each hand separately, finger positions, tension
- Background: wall material distinction (drywall vs concrete vs brick)
- Lighting: directionality, shadow characteristics
Step 4: Generate JSON Output
Return structured JSON following references/json-schema.md.
Output requirements:
- Valid JSON only - no markdown, no commentary
- All sections populated with specific values
- Hex codes for colors
- Actionable generation prompts
Quick Reference
Color Profile
What ships with it
6 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.
- 7d ago First seen · 143 lines · 48 tokens per session scan A 7e1918c1c7ac
image-insight is a skill published in the GitHub repository GzuPark/claude-plugin-pack (6 stars, last pushed 7mo ago), licensed MIT. It adds 48 tokens to every session and 1,028 once invoked, about $0.0002 per session on Opus 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 2026-08-31.
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