chore: add CLAUDE.md project instructions + exclude .chat/ from git

Adds CLAUDE.md with session startup checklist, autonomy instructions,
and long-running task workflow patterns (condition-based and time-based
wakeups). Excludes .chat/ chat history from git.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Paul Huliganga 2026-05-14 15:32:04 -04:00
parent dbc09d12d1
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# Claude Code — Donkeycar RL Project Instructions
## Session Startup — Do This First
At the start of every session:
1. Read `agent/SESSION_HANDOFF.md`
2. Check if an experiment is running: `ss -tnp | grep 9091`
3. If running, **immediately arm a background monitor** on the experiment log before anything else
4. Report current status to the user
Do not wait for the user to ask. Arming the monitor is the first action.
---
## Autonomy Instruction
Continue the Donkeycar RL/sim work autonomously. Rebuild, sync, relaunch, run
diagnostics, patch code, and restart experiments as needed. Keep going until you
either have a verified fix and a running experiment, or a concrete blocker that
truly requires the user. Only pause for: risk of data loss, destructive actions,
missing credentials, or major strategy tradeoffs.
If the user says only `continue`, use the instruction above.
---
## Long-Running Task Workflow
A common failure mode: model starts a long-running task, returns to the prompt,
and waits — defeating the purpose. Claude Code has two mechanisms to avoid this.
### 1. Condition-based wakeup (background Bash task)
Use when you want to be woken when something happens (log line appears, file
changes, process exits).
```python
# Pattern: until <condition>; do sleep N; done && <show results>
Bash(
command="until grep -q 'Checkpoint saved' /path/to/run.log; do sleep 15; done "
"&& tail -20 /path/to/run.log",
run_in_background=True
)
```
When the shell command exits, the runtime delivers a `<task-notification>` into
the conversation. This wakes Claude up automatically — no polling needed on the
model side. The model then reads the output and continues work.
**Key rules:**
- Use `until <check>; do sleep N; done` — never `sleep 120 && check` (blocked)
- The notification arrives as a message in the conversation context
- Multiple background tasks can run in parallel and each fires independently
### 2. Time-based wakeup (ScheduleWakeup tool)
Use when you want to be woken after a fixed delay (e.g. "check back in 20 min").
```python
ScheduleWakeup(
delaySeconds=1200, # 20 minutes
reason="checking 100k checkpoint results",
prompt="<<autonomous-loop-dynamic>>" # or the original /loop prompt
)
```
The runtime fires the wakeup after the delay, re-entering the conversation so
the model can continue. Use this for idle waits (waiting for a build, a slow
process, etc.) when there's no clear log-file signal to watch.
**Cache timing guidance:**
- Under 270s: prompt cache stays warm (cheap)
- Over 300s: cache miss on wakeup (more expensive but fine for long waits)
- Default idle: 12001800s (2030 min)
### 3. Combining both
For long experiments, use condition-based tasks for each checkpoint, and
ScheduleWakeup as a fallback heartbeat:
```python
# Fire when checkpoint N arrives
Bash(command="until [ $(grep -c 'Checkpoint' log) -ge 5 ]; do sleep 15; done && tail log",
run_in_background=True)
# Also wake in 30 min regardless, to check for errors
ScheduleWakeup(delaySeconds=1800, reason="exp27 progress check", prompt="continue")
```
---
## Experiment Monitoring Commands
```bash
# Watch live training log
tail -f agent/models/exp27-random-roads/run_*.log
# Check all checkpoints and evals
grep "Checkpoint\|Eval\|NEW BEST" agent/models/exp27-random-roads/run_*.log
# Verify sim is up
python3 -c "import socket; s=socket.socket(); s.settimeout(3); s.connect(('127.0.0.1',9091)); print('OK'); s.close()"
# Check what's connected to sim
ss -tnp | grep 9091
```
## Session Handoff
Full experiment history, current state, and important paths:
`agent/SESSION_HANDOFF.md`