processing-computer-vision-tasks
tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill processing-computer-vision-tasksProcess images using object detection, classification, and segmentation. Use when requesting "analyze image", "object detection", "image classification", or "computer vision". Trigger with relevant phrases based on skill purpose.
Validation
81%| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 13 / 16 Passed | |
Implementation
7%This skill is largely boilerplate with minimal actionable content. It describes what computer vision processing is rather than providing concrete instructions on how to use the computer-vision-processor plugin. The examples are abstract descriptions rather than executable code, and critical details like the actual API/command syntax, supported image formats, and expected output schemas are completely missing.
Suggestions
Replace abstract examples with actual executable code showing the '/process-vision' command syntax, required parameters, and expected JSON output format
Remove redundant overview text and generic sections (Prerequisites, Instructions, Error Handling) that provide no skill-specific value
Add concrete code examples for each use case (object detection, classification, segmentation) with actual input/output examples
Document the specific API interface: what parameters does '/process-vision' accept, what formats are supported, what does the response look like
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with redundant explanations (overview repeated twice), explains concepts Claude already knows (what object detection is, basic error handling principles), and includes generic boilerplate sections that add no value. | 1 / 3 |
Actionability | No executable code provided despite claiming to 'generate code'. Examples describe what the skill 'will do' abstractly rather than showing actual commands, API calls, or code snippets. The '/process-vision' command is mentioned but never demonstrated. | 1 / 3 |
Workflow Clarity | The 'How It Works' section describes abstract steps without concrete implementation. No validation checkpoints, no error recovery flows, and the 'Instructions' section is completely generic boilerplate with no task-specific guidance. | 1 / 3 |
Progressive Disclosure | Content is organized into sections with headers, but it's a monolithic document with no references to external files. The structure exists but contains mostly filler content that could be dramatically condensed. | 2 / 3 |
Total | 5 / 12 Passed |
Activation
67%The description adequately covers the basics with a clear 'Use when' clause and relevant domain terminology. However, it relies on technical jargon rather than natural user language, and the final sentence ('Trigger with relevant phrases based on skill purpose') is meaningless filler that adds no value. The capabilities listed are category-level rather than concrete actions.
Suggestions
Replace technical terms with natural user phrases users would actually say, such as 'what's in this picture', 'find objects', 'identify items in photo', 'label this image'
Remove the vague filler sentence 'Trigger with relevant phrases based on skill purpose' and instead add more specific trigger examples
Add concrete action examples like 'identify objects in photos, classify image content, segment regions' instead of just listing technique names
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (images) and lists some actions (object detection, classification, segmentation), but these are fairly high-level categories rather than concrete specific actions like 'identify objects in photos' or 'label image regions'. | 2 / 3 |
Completeness | Clearly answers both what (process images using detection, classification, segmentation) and when (explicit 'Use when' clause with trigger phrases). The final sentence 'Trigger with relevant phrases based on skill purpose' is vague filler but doesn't negate the explicit triggers provided. | 3 / 3 |
Trigger Term Quality | Includes some relevant keywords like 'analyze image', 'object detection', 'image classification', 'computer vision', but misses common natural variations users might say like 'what's in this image', 'identify objects', 'detect faces', 'segment photo', or file extensions like '.jpg', '.png'. | 2 / 3 |
Distinctiveness Conflict Risk | Reasonably specific to computer vision tasks, but 'analyze image' is generic enough to potentially conflict with other image-related skills (e.g., image editing, OCR, image generation). Could be more distinctive with specific use cases. | 2 / 3 |
Total | 9 / 12 Passed |
Reviewed
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