imagekit-developer/skills

ai-tasks

Apply AI-powered analysis to images for business-specific tagging, metadata extraction, and quality checks using controlled vocabularies. Use when user wants to analyze images and apply structured metadata in ImageKit.

First seen Jun 1, 2026

Installation

$ npx skills add imagekit-developer/skills --skill ai-tasks

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 2
License LICENSE
Default branch main
Open issues 0
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,517 B
  • docs SUMMARY.md 2,456 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 393 installs

SKILL.md

AI Tasks Skill

When to use

  • User wants to tag images with business-specific categories
  • User needs controlled vocabularies (predefined value lists)
  • User wants yes/no quality checks on images
  • User needs to extract metadata using natural language analysis

AI Task Structure

Each AI Task contains 1-10 sub-tasks with:

  1. Instruction (required): Natural language question about the image
  2. Action Type (required): selecttags, selectmetadata, or yes_no
  3. Vocabulary (optional): 1-30 predefined approved values

Action Types

select_tags

Adds tags from vocabulary. Supports multiple selections.

{
  "type": "select_tags",
  "instruction": "What body style is this vehicle?",
  "vocabulary": ["sedan", "suv", "hatchback"],
  "max_selections": 1
}

select_metadata

Sets custom metadata field (field must exist in DAM).

{
  "type": "select_metadata",
  "instruction": "What is the primary color?",
  "field": "primary_color",
  "vocabulary": ["red", "blue", "white", "black"],
  "max_selections": 1
}

yes_no

Binary quality check with conditional actions.

{
  "type": "yes_no",
  "instruction": "Is the product completely visible?",
  "on_yes": { "add_tags": ["framing_ok"] },
  "on_no": { "add_tags": ["needs_reshot"] }
}

Gotchas

  • Instruction clarity: Be specific ("What is the collar type?" not "Describe the image")
  • Vocabulary design: Use business terminology, non-overlapping, 1-30 items max
  • Field requirements: For select_metadata, field must exist in DAM first
  • Tag values: Cannot contain % character
  • yesno tasks: Must have at least one of onyes or on_no
  • Vocabulary length: Max 500 characters combined (select_tags only)
  • Scope: Works on visual content only (images/videos)

Applying AI Tasks

  • Via Saved Extensions: Create and apply via dashboard/API
  • Via API at Upload: Include in extensions array
  • Via Path Policies: Auto-apply to files in specific folders

Full examples

For complete, copy-ready ai-tasks configurations organized by industry (fashion e-commerce, travel, automotive) and detailed per-task-type parameter references, read [resources/EXAMPLES.md](resources/EXAMPLES.md).