Overview
The category system routes tasks to optimal models based on task type, not model name. You delegate by intent (visual work, deep logic, quick fix), and the system picks the right model automatically.The 8 Built-In Categories
File:src/tools/delegate-task/constants.ts:210
| Category | Default Model | Variant | Domain |
|---|---|---|---|
| visual-engineering | google/gemini-3.1-pro | high | Frontend, UI/UX, design, styling, animation |
| ultrabrain | openai/gpt-5.3-codex | xhigh | Hard logic, complex architecture |
| deep | openai/gpt-5.3-codex | medium | Goal-oriented autonomous problem-solving |
| artistry | google/gemini-3.1-pro | high | Creative approaches beyond standard patterns |
| quick | anthropic/claude-haiku-4-5 | - | Trivial tasks, single file changes |
| unspecified-low | anthropic/claude-sonnet-4-6 | - | Moderate effort, doesn’t fit other categories |
| unspecified-high | anthropic/claude-opus-4-6 | max | High effort, doesn’t fit other categories |
| writing | kimi-for-coding/k2p5 | - | Documentation, prose, technical writing |
How Categories Work
Category-Based Delegation
Instead of:- Category resolver looks up
visual-engineering - Finds default model:
gemini-3.1-prowith varianthigh - Checks model availability
- Falls back if unavailable (see Fallback Chain)
- Spawns Sisyphus-Junior with category prompt + skills
- Returns result
Category Resolution Pipeline
File:src/tools/delegate-task/category-resolver.ts
src/tools/delegate-task/model-selection.ts):
Category Profiles
visual-engineering
Model:google/gemini-3.1-pro (variant: high)
Use For:
- Frontend implementation
- UI/UX design
- Styling and layout
- Animations and transitions
- Component libraries
- Responsive design
src/tools/delegate-task/constants.ts:8):
ultrabrain
Model:openai/gpt-5.3-codex (variant: xhigh)
Use For:
- Deep logical reasoning
- Complex architecture
- System design
- Algorithm implementation
- Performance optimization
- Hard debugging
src/tools/delegate-task/constants.ts:22):
deep
Model:openai/gpt-5.3-codex (variant: medium)
Use For:
- Autonomous goal-driven tasks
- Hairy problems requiring deep understanding
- End-to-end feature implementation
- Research → implement workflows
src/tools/delegate-task/constants.ts:177):
- ultrabrain: Hard logic problems, architecture decisions
- deep: Goal-driven autonomous execution, less guidance needed
gpt-5.3-codex - Only activates if available.
Fallback Chain:
artistry
Model:google/gemini-3.1-pro (variant: high)
Use For:
- Highly creative tasks
- Unconventional approaches
- Novel combinations
- Artistic expression
- Content generation
src/tools/delegate-task/constants.ts:44):
gemini-3.1-pro - Only activates if available.
Fallback Chain:
quick
Model:anthropic/claude-haiku-4-5
Use For:
- Trivial tasks
- Single file changes
- Typo fixes
- Simple modifications
- No reasoning required
src/tools/delegate-task/constants.ts:61):
unspecified-low
Model:anthropic/claude-sonnet-4-6
Use For: Tasks that don’t fit other categories but require moderate effort.
Selection Gate:
unspecified-high
Model:anthropic/claude-opus-4-6 (variant: max)
Use For: Tasks that don’t fit other categories but require substantial effort.
Selection Gate:
writing
Model:kimi-for-coding/k2p5
Use For:
- Documentation
- README files
- Technical writing
- Blog posts
- API documentation
src/tools/delegate-task/constants.ts:151):
Fallback Chains
File:src/shared/model-requirements.ts:95
Every category has a fallback chain for resilience:
- Try first entry:
gemini-3.1-provia google/github-copilot/opencode - If unavailable, try second:
glm-5via zai-coding-plan/opencode - If unavailable, try third:
claude-opus-4-6via anthropic/github-copilot/opencode - If all fail, error
src/shared/model-availability.ts):
Custom Categories
You can define custom categories in config:Category Selection Guide
Decision Tree
Examples by Category
| Task | Category | Reason |
|---|---|---|
| Build responsive navbar | visual-engineering | UI component |
| Optimize database query | ultrabrain | Complex logic |
| Implement OAuth from scratch | deep | Autonomous goal-driven |
| Design 5 landing page concepts | artistry | Creative exploration |
| Fix typo in README | quick | Trivial change |
| Add logging to endpoints | unspecified-low | Moderate, doesn’t fit others |
| Migrate REST to GraphQL | unspecified-high | High effort, broad impact |
| Write API documentation | writing | Technical writing |
Model Variants
Definition: Effort level adjustment for Anthropic models. Supported Variants (from OpenCode SDK):low: Minimal reasoning effortmedium: Balanced (default)high: Increased reasoningmax: Maximum reasoning effortxhigh: Custom extended high (Oh My OpenCode specific)
chat.params hook, which sets Anthropic’s effort level.
Performance Considerations
Model Speed vs Capability
| Category | Model | Speed | Cost | Capability |
|---|---|---|---|---|
| quick | claude-haiku-4-5 | ⚡⚡⚡ | $ | Low |
| unspecified-low | claude-sonnet-4-6 | ⚡⚡ | $$ | Medium |
| visual-engineering | gemini-3.1-pro | ⚡⚡ | $$ | High |
| ultrabrain | gpt-5.3-codex | ⚡ | $$$$ | Highest |
| unspecified-high | claude-opus-4-6 | ⚡ | $$$$ | Highest |
quick for trivial tasks to save cost/time. Reserve ultrabrain/unspecified-high for genuinely complex work.
Parallel Category Execution
Background execution works across categories:Next Steps
Orchestration
Learn how agents delegate tasks using categories
Agents
Understand which agents use which categories
Configuration
Customize category model assignments
Skills
Load skills to enhance category execution