Deliver the context you claim
The nominal target changes when the cap, envelope, and output reserve share one window.
BENCHMARK-MEASUREMENT-PLAN.md · model-context-matrix.csv · planned-run-manifest.json
The idea in plain language
The matrix uses five scenarios: 256, 128k, 256k, 500k, and ~1M. ✓ fits a known limit; △ needs proof; — exceeds it; N/A is non-textual. A harness cannot claim it tested 500k if it compacted or truncated before transmission.
Running example: send the same sealed parcel — nonce, checksum, and three needles — through all six lanes. If the harness changes the wrapping, you are measuring the lane too. The analogy breaks because context, tools, and thinking carry semantics, not size alone.
The actual target is min(nominal scenario, effective cap − observed envelope − output reserve). A full lane has 53 strict and 9 conditional cells. If all six lanes qualified, the geometric upper bound would be 1,278 requests and 238,024,602 known input tokens — a projection, not authorization.
Verifiable excerpt
actual_target = min(nominal, effective_cap - envelope - output_reserve)\nper_lane = 53 strict + 9 conditional\nall_six_lanes_upper_bound = 1278 requests
outputs/BENCHMARK-MEASUREMENT-PLAN.md · outputs/model-context-matrix.csv · outputs/planned-run-manifest.json
The path in one picture
Retrieval check
Can hidden compaction compare with the direct grid?