Use this skill for Affinity reasoning before automation. It helps choose the right Affinity concept, object type, workflow, and verification method. It is complementary to balise-affinity-mcp, which executes changes through the MCP.
Core Posture
Treat Affinity as a unified creative environment with vector, pixel, and layout capabilities in one document. Before recommending an action, identify the user's intent:
- create or edit vector artwork
- retouch or manipulate pixels
- structure a layout or publication
- build reusable design systems
- prepare exportable assets
- diagnose a visual or UI-state issue
- automate through MCP
Do not reduce Affinity work to poster recreation. Posters are only one possible composition use case.
Reference Routing
- Read
references/affinity-mental-model.mdfor architecture, Studios, object model, and workflow decisions. - Read
references/affinity-decision-matrix.mdfor concrete object and verification choices. - If the answer requires live document manipulation, switch to
balise-affinity-mcpand follow its SDK-first workflow.
Reasoning Rules
- Separate what is artwork from what is Affinity UI state.
- Prefer non-destructive workflows unless final flattening is explicitly requested.
- Prefer reusable systems for repeated design elements: symbols, text styles, global colors, assets, and named groups.
- Choose text mode deliberately: Artistic Text for display fragments, Frame Text for layout containers.
- Use artboards/pages/spreads for variants, screen states, and multi-page work instead of separate files when a shared system matters.
- Treat exact feature names, AI tools, shortcuts, and version-specific behavior as verify-first details.
- When the user wants a detailed synthesis, prefer HTML over long Markdown.
Output Expectations
For audits or strategy:
- classify findings by concept area
- explain practical impact
- recommend the safest Affinity-native approach
- identify what should be verified through MCP or visual render
For automation planning:
- name the relevant Affinity concepts
- describe the object model to inspect
- identify the narrowest safe edit
- state the visual verification method
For learning capture:
- extract durable lessons
- mark volatile claims
- suggest which reference file should absorb the lesson