Commit ·
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Parent(s): 65b799e
add agents.md
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AGENTS.md
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# AGENTS.md
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This repository is for the Fusion Design Lab hackathon submission. Treat it as a clean, public-facing artifact repository, not a general research sandbox.
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## Mission
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Build and ship one clear, reproducible OpenEnv environment for budget-constrained stellarator design.
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The core product is the environment:
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- narrow task
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- legible observation space
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- discrete action space
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- explicit constraints
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- reward function that can be explained and iterated
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Training is supporting evidence. Do not let the repo drift into training-first work.
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## Source of Truth
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Use these docs as the planning SSOT:
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- `docs/FUSION_DESIGN_LAB_PLAN_V2.md`
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- `docs/FUSION_DELIVERABLES_MAP.md`
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- `docs/FUSION_NEXT_12_HOURS_CHECKLIST.md`
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If code and docs disagree, either:
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1. update code to match the docs, or
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2. deliberately update the docs in the same change
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Do not leave silent divergence.
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## Project Priorities
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1. Freeze the environment contract before heavy iteration.
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2. Keep scope to one stable task.
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3. Treat reward as iterative: `Reward V0`, then `Reward V1`, etc.
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4. Manual-playtest before investing heavily in training.
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5. Prefer behavior traces and baselines over reward-curve-only storytelling.
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6. Keep claims conservative and evidence-backed.
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## Working Rules
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- Do not broaden the task family beyond the single stellarator environment unless explicitly requested.
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- Do not add broad “other sciences” claims to docs or demo copy unless there is real supporting evidence.
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- Do not narrate hypotheses as validated facts.
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- Do not add complicated reward shaping until the simpler version has been tested against actual trajectories.
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- Do not optimize notebook/training work ahead of local environment stability, remote environment stability, and baseline comparisons.
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## Environment Contract Rules
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Any change to the environment should preserve or deliberately update:
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- observation schema
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- action schema
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- episode flow
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- terminal conditions
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- reward semantics
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If you change one of these, update the corresponding documentation and tests in the same task.
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## Reward Design Rules
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When changing reward logic:
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- document the previous behavior
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- identify the pathology or exploit
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- describe the change in plain language
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- preserve a readable mapping from behavior to incentive
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Avoid opaque reward changes that improve a metric without making the environment easier to reason about.
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## Manual Playtesting
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Before calling a reward design “good,” verify that a human can:
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- read the observation
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- choose a plausible next action
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- understand why the reward changed
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If a human cannot act coherently from the observation, fix the environment contract before doing more training work.
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## Repo Layout
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- `fusion_lab/`: shared typed models and client code
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- `server/`: environment server, task contract, physics loop
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- `baselines/`: random and heuristic baselines
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- `training/`: evaluation or training notebooks
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- `demo/`: demo assets and scripts
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- `tests/`: focused tests for environment contract and repo behavior
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- `docs/`: public-facing planning and submission docs
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## Validation
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For scoped changes, prefer the smallest relevant checks first.
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Current useful commands:
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```bash
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python3 -m py_compile fusion_lab/models.py fusion_lab/client.py server/environment.py server/app.py server/physics.py
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python3 -m pytest -q tests/test_repo_scaffold.py
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```
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As the repo grows, add more targeted tests instead of depending only on broad end-to-end runs.
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## Git and Change Discipline
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- Keep commits scoped to the task.
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- Do not mix environment-contract edits with unrelated cleanup.
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- Prefer small, reviewable increments.
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- Branch names created for new work should use the `codex/` prefix.
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## What Good Looks Like
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A strong change in this repo usually does at least one of these:
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- makes the environment contract clearer
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- improves reproducibility
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- adds or fixes a meaningful baseline
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- strengthens the reward-iteration story
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- makes the demo evidence easier to trust
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If a change does not help one of those, question whether it belongs in this hackathon repo.
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CLAUDE.md
ADDED
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Read AGENTS.md
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