models

Manage Ollama Models

Discover, list, and manage ollama models for the agent pipeline.

Usage: /models [action] [target]

Actions:

• discover: Scan and register all installed ollama models
• list: Show all registered models and capabilities
• check <model>: Verify specific model availability
• defaults: Show default models for each task type

Examples:

• /models discover - Scan for new models
• /models list - Show all models
• /models check kimi-k2-thinking:cloud - Check if model available
• /models defaults - Show default selections

---

You are managing the ollama model registry.

Action: ${1:-list} Target: $2

Your Process:

1. Execute Action:

   Discover:

   # Scan ollama and update registry
   ~/.claude/scripts/discover-models.sh
   
   # Show results
   cat ~/.claude/model-capabilities.json | python3 -c "
   import json, sys
   data = json.load(sys.stdin)
   print(f'Discovered {len(data[\"models\"])} models:')
   for model, info in data['models'].items():
       caps = ', '.join(set(info['capabilities']))
       print(f'  - {model}: {caps}')
   "
   

   List:

   # Show all models with capabilities
   cat ~/.claude/model-capabilities.json | python3 -c "
   import json, sys
   from pathlib import Path
   
   registry_file = Path.home() / '.claude' / 'model-capabilities.json'
   with open(registry_file, 'r', encoding='utf-8') as f:
       data = json.load(f)
   
   print('## Registered Models\n')
   for model, info in sorted(data['models'].items()):
       caps = ', '.join(set(info['capabilities']))
       family = info.get('family', 'unknown')
       context = info.get('context_window', 'unknown')
       cost = info.get('cost', 'unknown')
   
       print(f'### {model}')
       print(f'  - Family: {family}')
       print(f'  - Capabilities: {caps}')
       if isinstance(context, int):
           print(f'  - Context: {context:,} tokens')
       else:
           print(f'  - Context: {context}')
       print(f'  - Cost: {cost}')
       print()
   "
   

   Check:

   # Check if specific model is available
   ~/.claude/scripts/check-model.sh $2
   

   Defaults:

   # Show default model selections
   cat ~/.claude/model-capabilities.json | python3 -c "
   import json, sys
   from pathlib import Path
   
   registry_file = Path.home() / '.claude' / 'model-capabilities.json'
   with open(registry_file, 'r', encoding='utf-8') as f:
       data = json.load(f)
   
   print('## Default Models by Task\n')
   defaults = data.get('user_defaults', {})
   for task, model in sorted(defaults.items()):
       print(f'- **{task}**: {model}')
   
   print('\n## Task Preferences with Fallbacks\n')
   prefs = data.get('task_preferences', {})
   for task, config in sorted(prefs.items()):
       if config.get('preferred'):
           print(f'### {task}')
           print(f'  Preferred: {config[\"preferred\"][0]}')
           if config.get('fallback'):
               fallbacks = config['fallback'][:3]
               print(f'  Fallbacks: {\" -> \".join(fallbacks)}')
           print()
   "
   

2. Model Capability Reference:

   Vision Models:

   • qwen3-vl:235b-instruct-cloud (best vision, 262K context)
   • qwen3:1.7b (lightweight, has vision)

   Code Models:

   • kimi-k2-thinking:cloud (reasoning + code, 262K context)
   • deepseek-v3.1:671b-cloud (strong code, 163K context)
   • qwen2.5-coder:3b (lightweight coder)

   Reasoning Models:

   • kimi-k2-thinking:cloud (explicit thinking)
   • deepseek-v3.1:671b-cloud (strong reasoning)

   General Purpose:

   • All models have general capability
   • Prefer larger models for complex tasks

3. Registry Location:

   • File: ~/.claude/model-capabilities.json
   • Contains: Models, capabilities, defaults, task preferences
   • Auto-updated: By discover-models.sh

4. Capability Taxonomy:

   • vision: Image analysis, OCR, screenshots
   • code: Code review, refactoring, security
   • reasoning: Multi-step logic, complex analysis
   • general: General purpose tasks