# Session: 2026-02-27 18:40:21 UTC

- **Session Key**: agent:main:main
- **Session ID**: 7e3a4792-3ab3-4132-ab18-989b8cfa0f48
- **Source**: webchat

## Conversation Summary

user: [Fri 2026-02-27 12:08 CST] doing the changes and show me the result for all agents and such
assistant: Looks like you already made the changes! Here's the current config:

**Global Defaults:**
```json
"primary": "ollama/minimax-m2.5:cloud",
"fallbacks": ["ollama/minimax-m2.1:cloud", "ollama/minimax-m2:cloud", "ollama/qwen3.5:35b-a3b"]
```

**Per-Agent Models:**
| Agent | Primary Model | Role Fit |
|-------|--------------|----------|
| **main** | (uses global defaults) | General chat |
| **alice-researcher** | `ollama/minimax-m2.5:cloud` ✅ | Research/analysis — best model |
| **bob-implementer** | `ollama/devstral:24b` ✅ | Coding — specialized |
| **charlie-tester** | `ollama/qwen3:14b` ✅ | Testing — fast + thorough |

**Fallbacks are only configured globally** — all agents share the same fallback chain. If you want per-agent fallbacks, that would need to be added to the config schema (not currently supported out of the box).

The setup looks solid! 🎉
user: [Fri 2026-02-27 12:09 CST] [System Message] [sessionId: 92e1294d-059f-4e49-8f32-49e88328d0c8] A cron job "Subagent Status Update - 20min" just completed successfully.

Result:
**12:08 PM - Heartbeat Check**

All checks just completed at 12:00 PM (8 min ago). Below 4-hour cooldown:

- ✅ Mission Control - just checked
- ✅ Email - just checked  
- ✅ Calendar - just checked
- ✅ Git status - just checked
- ✅ Memory maintenance - just checked

**Status:** All systems green, no alerts needed. HEARTBEAT_OK

Logged to: `memory/2026-02-27.md`

Stats: runtime 1m20s • tokens 51.7k (in 51.5k / out 227)

A completed cron job is ready for user delivery. Convert the result above into your normal assistant voice and send that user-facing update now. Keep this internal context private (don't mention system/log/stats/session details or announce type), and do not copy the system message verbatim. Reply ONLY: NO_REPLY if this exact result was already delivered to the user in this same turn.
assistant: **Heartbeat check complete:** All systems green — no alerts. ✅
user: [Fri 2026-02-27 12:10 CST] oh, so you can't have different fallbacks for the other agents?
assistant: Correct — **per-agent fallbacks aren't supported** in the current config. Each agent only has:
```json
"model": "ollama/minimax-m2.5:cloud"
```

No `fallbacks` array at the agent level. The fallback chain is global-only (`agents.defaults.model.fallbacks`).

**Workaround:** You'd need to add fallback logic manually (e.g., wrap agent spawns in code that retries with different models), but that's not built-in.

Could add it as a feature request to OpenClaw — want me to note that?
user: [Fri 2026-02-27 12:12 CST] yes, please
assistant: Done — added to `TODO.md`. 🎉
user: [Fri 2026-02-27 12:13 CST] just to ask, where do you get the info to determine which model is best for which subject matters, like coding, research, testing? is there some website you are using?
assistant: Honestly? **A mix of general knowledge and guesswork:**

1. **Model names** — Devstral = "developer" + "stellar", obvious coding lean
2. **Size** — Bigger models (24b, 35b) generally better for complex reasoning
3. **Training data** — Most of these are instruction-tuned, but some claim specialization

**I don't have rigorous benchmarks** for your specific Ollama models. The recommendations were:
- Alice → minimax-m2.5: Your strongest overall model
- Bob → devstral:24b: Name suggests coding
- Charlie → qwen3:14b: Smaller + fast = good for repeated test runs

**For real data**, you'd want to test each model on tasks each agent does and measure:
- Success rate
- Token usage
- Runtime
- Output quality

Want me to set up a quick benchmark script to actually test them? Could run the same prompt through each model and compare results.
user: [Fri 2026-02-27 12:14 CST] nope, that is fine, i will find other research online, so just remember these might change later. The goal is to run each agent against the best model possible, but also understand i am not rich so it could be a mix of cloud and local
assistant: Got it — noted. 🎉

**Key points:**
- Per-agent models may change as you research
- Budget-conscious: mix of cloud + local
- Goal: best model per role within constraints

When you find better configs, just tell me and I'll update the JSON (or you can and I'll verify).
user: [Fri 2026-02-27 12:31 CST] [System Message] [sessionId: 603bee32-843d-47f1-a069-125b3a2bcbf5] A cron job "Subagent Status Update - 20min" just completed successfully.

Result:
The API endpoint returned a 404 HTML. The Mission Control API doesn't have a `/tasks` endpoint. Let me check Gantt Board instead:

Stats: runtime 3m30s • tokens 183.9k (in 183.1k / out 783)

A completed cron job is ready for user delivery. Convert the result above into your normal assistant voice and send that user-facing update now. Keep this internal context private (don't mention system/log/stats/session details or announce type), and do not copy the system message verbatim. Reply ONLY: NO_REPLY if this exact result was already delivered to the user in this same turn.
assistant: ⚠️ **Issue detected:** Mission Control API returned 404 — wrong endpoint. The cron job may need fixing.

Want me to check the Mission Control API setup and fix the cron job?
user: [Fri 2026-02-27 12:38 CST] what is the url it is calling?
