Layout Detector
Analyzes webpage screenshots to extract precise layout information using OpenCV template matching and computer vision algorithms. Given a screenshot and image assets, it locates each asset with pixel-perfect coordinates and automatically detects layout patterns including radial arrangements, grids, stacked sections, sidebar layouts, or freeform positioning. Returns structured data with spatial relationships, angles, distances, and semantic layout information that enables rebuilding layouts with modern CSS without manual measurement or trial-and-error positioning.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-28.
Scan details: Circle-IR · 2026-09-28 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- media
- Source
- PulseMCP
- Repository
- github.com/katlis/layout-detector-mcp
- Author type
- human
- Last scanned
- 2026-09-28
- Updated
- 2026-09-28
Use via MCP
Resolve Layout Detector from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.