db19741bee
- Use kimi-k2.5 for opus-level tasks - Use nemotron-3-super for sonnet-level tasks - Use kimi-k2-thinking for deep reasoning at flash end - Document what NOT to use (qwen, claude,) Signed: Annie Tunturi <ani@wiuf.net> 👾 Generated with [Letta Code](https://letta.com) Co-Authored-By: Letta Code <noreply@letta.com>
107 lines
3.1 KiB
Markdown
107 lines
3.1 KiB
Markdown
---
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description: Guide for running subagents effectively - model selection and troubleshooting
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limit: 2000
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---
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# Subagent Usage Guide
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## Model Selection
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When running subagents via the Task tool, always specify a valid model from the available list.
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### Available Models (as of current system)
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- `kimi-k2.5-nvfp4` - Fast, reliable
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- `kimi-k2.5` - Standard option, works well
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- `glm-4.7-flash` - Lightweight
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- `glm-4.7` - Standard GLM
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- `kimi-k2-thinking` - For reasoning tasks
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- `minimax-m2.5` - Alternative option
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- `qwen3.5` - Qwen series
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- `deepseek-v3.2` - DeepSeek
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- `deepseek-r1` - Reasoning-focused
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- `qwen3-coder` - Code-specific
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- `llama-3.3-70b` - Llama series
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- `sonnet` - Anthropic proxy (uses kimi-k2.5-nvfp4)
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- `haiku` - Lightweight proxy
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- `opus` - Heavy proxy (uses kimi-k2.5-nvfp4)
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- `nemotron-3-super` - NVIDIA model
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- `gpt-oss-120b` - OpenAI OSS
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### Tiered Model Selection
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| Task Level | Model | Purpose |
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|------------|-------|---------|
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| **Opus-level** | `kimi-k2.5` | Deep research, complex analysis, high-stakes decisions |
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| **Sonnet-level** | `nemotron-3-super` | Mid-complexity, balanced reasoning, implementation |
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| **Deep reasoning** | `kimi-k2-thinking` | Verification, synthesis, final review at end of chain |
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### What NOT to Use
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- **NO `qwen`** - User preference: "Qwen sucks"
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- **NO `claude` models** - Hardcoded to proxies, avoid confusion
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- **NO `glm-4.7-flash`** - Use `nemotron-3-super` instead for lightweight tasks
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### Preferred Models (Updated)
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- **Opus-level tasks**: `kimi-k2.5` (heavy research, architecture decisions)
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- **Sonnet-level tasks**: `nemotron-3-super` (implementation, exploration)
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- **Deep reasoning**: `kimi-k2-thinking` (verification, synthesis)
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- **Fast exploration**: `kimi-k2.5-nvfp4` (quick searches)
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## Common Errors
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### 500 Internal Server Error
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```
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InternalServerError2: 500 {"detail":"An unknown error occurred"}
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```
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**Causes:**
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- Letta server resource issue
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- Subagent creation endpoint failure
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- Transient server error
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**Resolution:**
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- Retry the same request
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- Try a different model
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- Use direct shell search as fallback
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### Unknown Model Error
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```
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Error: Unknown model "claude-sonnet-4"
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Available models: ...
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```
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**Resolution:**
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- Check available models list
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- Use a valid model name from the list
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- Do NOT use "claude" models (user preference)
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## Best Practices
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1. **Always specify model explicitly** to avoid ambiguity
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2. **Use kimi-k2.5 or kimi-k2.5-nvfp4** as safe defaults
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3. **Prefer lighter models** for simple exploration tasks
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4. **Retry on 500 errors** - often transient
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5. **Fall back to direct shell/Bash** if subagents fail repeatedly
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## Example Usage
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```typescript
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Task({
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description: "Explore codebase",
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prompt: "Find all files that...",
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subagent_type: "explore",
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model: "kimi-k2.5" // Always specify
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})
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```
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## Troubleshooting Workflow
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1. Subagent fails with 500? → Retry with same model
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2. Still failing? → Try different model (glm-4.7-flash, qwen3.5)
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3. Still failing? → Use Bash/Grep/Glob directly
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4. Document what worked for future reference
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---
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Last updated: 2026-03-21
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Discovered during: Matrix bridge formatting investigation
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Signed: Annie Tunturi <ani@wiuf.net>
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