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add agents.md

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  1. AGENTS.md +124 -0
  2. CLAUDE.md +1 -0
AGENTS.md ADDED
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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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+
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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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+
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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.
CLAUDE.md ADDED
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+ Read AGENTS.md