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- Screenshot Analyzer
screenshot-analyzer_skill
- Python
278
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill notedit/happy-skills --skill screenshot-analyzer- SKILL.md5.0 KB
Overview
This skill analyzes product screenshots to extract feature lists and generate prioritized development task checklists. It coordinates specialized analysis agents to identify UI components, user interactions, and business functions, then synthesizes and reviews a consolidated task plan. The output is a checklist-style PRD-ready task file and a concise user summary.
How this skill works
The skill runs three parallel analyzers per screenshot to capture UI structure, interaction flows, and business logic. A synthesizer merges those results into a unified, checkbox-formatted task list, and a reviewer validates completeness and quality. For multiple screens it deduplicates features and highlights unique competitor gaps.
When to use it
- Extracting features from competitor product screenshots for competitive analysis
- Turning UI designs or mockups into a prioritized PRD and development checklist
- Batch-analyzing multiple app screens to produce a consolidated task plan
- Reviewing visual references to discover missing flows or business rules
- Preparing scoping documents before a discovery or sprint planning session
Best practices
- Provide clear filenames and any context (product name, target users, platform) with screenshots
- Include multiple states or flows so interaction analyzer can infer transitions
- Label screenshots from the same product to enable deduplication across screens
- Accept output as feature-level WHATs; avoid asking for implementation specifics
- Review synthesized tasks and add business priorities before assigning to engineering
Example use cases
- Analyze a competitor mobile app gallery to extract unique onboarding and monetization features
- Convert a set of Figma screens into a checklist of front-end and UX tasks for a design sprint
- Run batch analysis on 20 app screens to generate a single docs/plans/YYYY-MM-DD-<product>-features.md
- Perform a gap analysis comparing your product to a visual reference and highlight missing interactions
FAQ
The output lists feature-level WHATs broken into small executable subtasks using checkbox format, focusing on user interactions and acceptance criteria rather than implementation.
Can it handle multiple screenshots from different products?
Yes. It deduplicates features when screenshots are from the same product and treats different products separately; include product labels to improve accuracy.