| name | sutro-context |
| description | Use before any research task, experiment, or PR review. Loads current project state from DISCOVERIES.md, open questions, and recent Telegram discussion. |
Sutro Research Context
Load this before doing any research work, running experiments, or reviewing PRs.
Step 1: Read core files
Read these in order. Stop and report if anything is unexpected.
- CLAUDE.md -- project context, current best methods, constraints
- DISCOVERIES.md -- what's proven, what failed, open questions (bottom of file)
- AGENT.md -- machine-executable experiment loop (if running autonomous)
- LAB.md -- experiment protocol, rules (especially rule #9: metric isolation)
Step 2: Check recent activity
Read the last 10 messages from priority Telegram topics:
import json
for f in ['chat-yad.json', 'chat-yaroslav.json', 'challenge-1-sparse-parity.json']:
path = f'src/sparse_parity/telegram_sync/{f}'
try:
msgs = json.load(open(path))
print(f'\n=== {f} (last 3) ===')
for m in msgs[:3]:
print(f" [{m['date'][:10]}] {m['sender']}: {m['text'][:150]}")
except FileNotFoundError:
print(f'{f} not found -- run: bun run sync_telegram.ts')
Check GitHub for open work:
gh pr list --repo cybertronai/SutroYaro --state open
gh issue list --repo cybertronai/SutroYaro --state open
Step 3: Know the current state
| Fact | Value |
|---|
| Best method | GF(2) Gaussian elimination, 509us, ARD ~500 |
| Best energy proxy | DMC (Data Movement Complexity, Ding et al.) |
| Experiments done | 33+ (see research/log.jsonl) |
| Open questions | Bottom of DISCOVERIES.md (Q7, Q11-Q13 still open) |
| Next milestone | Energy-efficient nanoGPT training ("final exam") |
| Meeting cadence | Mondays 18:00 at South Park Commons |
Step 4: Before writing code
- Check
research/search_space.yaml for allowed parameter ranges
- Check
research/questions.yaml for the dependency graph of open questions
- Run
checks/env_check.py to verify environment
- Run
checks/baseline_check.py if baselines may differ on your machine
For contributors using other tools
This context applies regardless of which AI tool you use. The key files are plain markdown and YAML. Read them before starting work. The experiment protocol in LAB.md and AGENT.md defines the loop: hypothesis, code, run, measure, record.