auto-mdp-solver — the harness

The Python toolchain behind the auto-mdp-solver Claude Code plugin: a pipeline that turns a verbal dynamic-decision problem into a trained, deployable RL policy. This package is the executable half — the IR schema and interpreter, the gates, and the tuning driver. The plugin (skills, spec, examples) ships separately and installs this package into the workspace venv on first run.

package	what it is	entry point
`mdp_ir`	MDP-IR schema (pydantic), reference interpreter, catalog ⊕ selection layering, execution laws, bit-exact differential runner	`python -m mdp_ir <schema>`, `python -m mdp_ir.laws <dir>`, `python -m mdp_ir.differential <schema>`
`mdp_conformance`	spec-conformance checks on a generated domain	`python -m mdp_conformance <dir>`
`mdp_gates`	eval-gate comparison of a candidate against baselines under the shared seed protocol	`python -m mdp_gates`
`mdp_tuning`	Optuna tuning driver over a domain's training script	`python -m mdp_tuning <dir> ...`
`mdp_stage`	the pipeline's entry gates — where a domain folder stands, and whether an op may start	`python -m mdp_stage <dir> [--for <op>]`

Install

pip install "auto-mdp-solver[domain]"   # everything a generated domain needs (SB3 + torch + pandas + plotly + pytest)
pip install auto-mdp-solver             # harness only, torch-free: IR, conformance, gates, tuning
pip install "auto-mdp-solver[dev]"      # harness + pytest
# the same, straight from the repo at a release tag (no PyPI needed):
pip install "auto-mdp-solver[domain] @ git+https://github.com/tong-wang/auto-mdp-solver@v0.10.17#subdirectory=harness"

Requires Python ≥ 3.12. The version number tracks the plugin release it was cut from (v0.10.17 ↔ plugin 0.10.17), so the skills and the harness a workspace holds are comparable by one number.

Documentation, the per-domain spec, the frozen example domains and the test cases live in the repository. MIT license.

Metadata

Release files for auto-mdp-solver 0.11.9

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