Shared benchmark service

This package implements the SIM server protocol. New integrations follow the RoboDojo-derived conventions. Each benchmark's server.py selects its native adapter; these shared modules provide strict JSON transport, single-attempt sessions and artifact transfer. They do not generate actions, call a model or run a separate scheduling service.

server.py owns the administrative RPC lifecycle and serialized native calls.
wire.py serializes the declared observations and evaluator-private transitions.
launch.py supplies common launch mechanics to benchmark-owned entrypoints.
client.py is an administrative client for a trusted run driver, not a model-facing tool. It can read schedules, deployment information, native metrics and finalized artifacts. Never give it, its endpoint or its bearer credential to the model actor.

An agent-owned trusted driver may use this client and pass only the declared observation to its model. Returning an action does not give the model native simulator access. The model owns target selection, memory and voluntary stopping; the benchmark owns native control conversion, termination and scoring. Results and videos belong under AgentPolicies/<profile>/results/<benchmark>/.

Reward and transition information are evaluator-private, not policy inputs. The trusted driver may obtain cached metrics before closing the episode; artifact downloads require finalized, closed-file inventory. Idle service time does not step physics, lost acknowledgements do not replay controls, and a failed attempt is not automatically replaced.

This is an ownership/protocol boundary, not OS-enforced isolation. A trusted driver's administrative permissions are not safe capabilities for an untrusted actor. If the actor itself must access a service, an independently reviewed episode-scoped public control interface is required; this client does not implement that interface. The selected Codex integration filters its model request and child environment, but does not claim hard filesystem isolation.

Ownership and source capture

benchkit/sim_server/ is the sole implementation, not an import alias. Reusable communication belongs here; task catalogs, native adapters and scoring belong under benchmarks/simBenchmarks/<benchmark>/; decisions belong under AgentPolicies/. This is a library used by the two control ends, not a third scheduling process. The temporary benchmarks/simBenchmarks/service/ package is removed, without changing RPC version, fields, schedules, scoring, actions or artifact limits. Old frozen campaigns and source bundles retain their original bytes and verification rules. Generic contracts remain in benchkit/contracts.py and benchkit/interfaces.py.

python -B -m benchkit.sim_server starts only the dependency-free synthetic diagnostic service. It is not a native robot benchmark or capability evidence. For a native benchmark, use its own benchmarks.simBenchmarks.<benchmark>.server entrypoint.

New service snapshots capture the explicit shared-service runtime inventory and the selected wrapper's supplemental files. Starting one service does not require other benchmarks or model drivers. The agent/campaign evaluation snapshot remains broader and separate; existing frozen inventories are unchanged. Run only from a stable versioned source snapshot; never update files inside an active or historical frozen run.

The standard CPU runner includes this package's cross-benchmark acceptance tests as the benchmark_service group:

python -B -m benchkit.checks.run_regressions --group benchmark_service \
  --output /absolute/new-regression-report

These checks prohibit native initialization/model calls. They do not replace the benchmark's own contract tests or native readiness and model-sample gates.