◆ DISCOVER
Generate hypotheses from cross-domain data. Two LLMs generate, sandbox models review for blind spots.
⊙ PREDICTION REGISTER
| ID | Prediction | Domain | Testable By | Status |
|---|
≡ CALIBRATION
⟲ SELF-IMPROVEMENT SANDBOX
Consult sandbox models for pipeline improvements. All changes require human approval.
| ID | Domain | Model | Principle | Status | Actions |
|---|
▫ DATA SOURCES
★ BENCHMARK
Run verified questions through ATLAS and grade against known answers.
| ID | Question | Mode | Score | Grade | Details |
|---|
</> CODE ENGINE
8-step pipeline: Ingest → Verify → Plan → Build (2 models) → Connect → Execute → Checklist → Prove
✎ CODE REVIEW RESULTS
Multi-model code review — issues found by 2+ models are marked high confidence.
⚙ PROJECTS
Link projects to GitHub repos. Persistent memory tracks decisions, bugs, and progress across sessions.
£ USAGE & COSTS
API call tracking and cost breakdown by provider.
| Provider | Model | Calls | Cost | Tokens In | Tokens Out |
|---|