Observed-example context: tested adapter and frozen comparison

Adds an opt-in observed-example context adapter for #84. It supplies the six current observed integer triples through a fixed, separately seeded projection while keeping the original encoder initialization, action RNG, readout, reward and current-decision update unchanged. Fresh context is required each episode; boundary snapshots retain learning without retaining task examples. Opaque episode IDs are guards only, with an invariance regression test.

Freezes the next comparison before measurement: all six original phase orders, three seeds, five matched controls including same-run streaming, both budgets, 8,640 episodes. Protocol SHA-256: d8897dc237ceed1a8781dd2dd828b4507842bbdf53473558edffa928fe6485fb. It includes a fixed-encoder capacity diagnostic, context/diagnostic CPU costs, and independent replay. Giving the learner current examples changes its information set; no learning improvement or hardware gain is claimed before measurement.

Validation: 61 affected tests passed in 0.210 s; all 435 fast tests passed with unchanged source hashes and no skips/exclusions. The initial synthetic fixture failure is retained. An earlier 434-test run passed before CPU-scope wording and opaque-ID contract clarification. Slow/retry and local full discovery were not rerun for this additive path.

Also retains source-specific GitHub fast CI logs for f4b97fd / code-v95: 420 tests passed on Python 3.12 in 458.615 s and Python 3.13 in 476.132 s. Those results do not verify the new adapter. Existing full CI jobs remain pending. Original runtime, benchmark corpora and negative ranking/persistence results are preserved.