Reproducible savings methodology
Self-graded savings, with the math.
Lens computes a headline savings number for every customer. That number is the same in every report your team reads. This page publishes the math chain, the paired-trial protocol, the parity gate, and the weekly numbers corteX Lens runs on itself. The notebook reproduces the result bit-for-bit on your own audit-log export.
The math chain (Section 1) and the parity gate (Section 3) carry the trust contract. The headline below is a paired-trial median with a 95 percent CI, not a marketing roll-up.
Combined headline (weekly)
43.14%
Combined input tokens removed, token-weighted across 1 pinned benchmark, run 2026-W25.
Per-session median savings 25.26%. 95 percent CI: 0.00% to 0.00% (stratified bootstrap, dataset id is the stratum). Wilcoxon p = 0.21140 (n = 27).
real-developer-transcripts
rev claude- (n=11/42)
25.26%
Run cost: $0.00 of $50.00 budget. Generated 2026-06-18T00:00:00Z.
Run history
Every measured run, in order.
The headline above is the current run. This timeline shows the full measured progression so you can see how savings and parity moved across model and rule changes. Each row links to the document that carries its math. Forecast-only runs are excluded; this is measurements only.
- v1Narrow gate
Baseline (pre-patch)
- Median savings
- 23.07%
- Parity (judged)
- 17.84%
- Rows attempted
- 200
- Wilcoxon p
- < 0.0001
Highest savings of any run, but parity was the weakest at 17.84 percent. The gate stayed narrow because parity was the open worry.
Worker gemini-2.5-flash, judge gemini-2.5-flash, 2026-05-31. source
- v2Partial improvement
Patches A-E (model upgrade)
Per-level summary
Measured outcomes per rule profile
Sealed runs only, grouped by the Removal Catalog lever their source documents state. A run appears in a group only when its committed document names the rule configuration; nothing here is inferred.
parity-first rules2 sealed runs
- R5-off: 8.92 percent median savings, 62.87 percent parity, worker gemini-2.5-flash, 2026-06-01.
- gate: 8.85 percent median savings, 49.50 percent parity, worker gemini-3.5-flash, 2026-06-08.
savings-max rules1 sealed run
- v2: 10.91 percent median savings, 47.79 percent parity, worker gemini-3-flash-preview, 2026-06-01.
Lever not stated: v1, v3, realdata-cc. Their source documents do not name the rule configuration, so they are not grouped; absent means the document does not say, never a guess.
Same-stack caveat from the R5 ablation row, verbatim: Run on the v1 model stack, so savings is not directly comparable to v2 and v3. No two sealed runs on different levers share a worker model, so per-level savings are not directly comparable across levers.
The current published run measures Lens on real Claude Code developer transcripts, with the R7 transcript-tool-result-window rule as the savings lever. The headline is 43.14 percent of input tokens removed (token-weighted aggregate; 43.17 percent on large-context sessions), with a 25.26 percent per-session median. Quality shows no measurable change (composite quality delta 0.000), and the parity sample is indistinguishable from the baseline noise floor at this size (Wilcoxon p=0.21), so the verdict is NARROW, not GO. Raw transcript content is private and withheld. Earlier Agent-FLAN runs remain in the timeline as measured history but are no longer the published number.
Open methodology
The math chain in plain language.
Six chained steps from raw tokens to the dollar number on your dashboard. Each step has a tested implementation in TypeScript and a byte-stable Python reference. The methodology is signed per commit and the Removal Catalog version. Roughly a three-minute read.
Read the methodologyVerify on your data
Run the same math against your own audit log. The notebook prints a report that matches the dashboard headline for the same window, and the full walkthrough lives on the verify guide. Verify it yourself.
What is saving the tokens
What is saving the tokens
The proven lever, and where the saving shows up.
This run has one measured savings lever, not a stack of estimates. The bars below group the same paired trials to show where across the run the saving lands. Every figure is read from the published run cl-realdata-cc-2026-06-18, and a cohort below the privacy floor is withheld rather than shown.
Proven savings lever
R7Transcript tool-result window
Windows oversized tool-result bodies in Claude Code transcripts so the largest-context sessions carry most of the input-token saving.
Token-weighted savings
43.14%
Per-session median savings
25.26%
Where the saving shows up
By input complexity
Each bar is the measured per-cohort median input-token saving for this grouping. A cohort is a different slice of the same paired trials, so the bars show where the lever pays off, not an additive share that sums to the headline.
Trust check
Verdict, quality, and parity floor
Gate verdict
NARROW
Quality read
Inconclusive
Inconclusive at this sample size: the transform-versus-floor Wilcoxon p is 0.2114 against the 0.05 bar, so quality is neither proven to hold nor shown to move.
Parity vs noise floor
26.20%
vs 36.10% baseline noise floor. 42 paired rows, Wilcoxon p 0.2114
Parity is a two-run differential: the baseline arm is replayed against itself to set a quality noise floor, then the lens transform arm is tested against that floor with a paired Wilcoxon signed-rank test. The paired Wilcoxon p of 0.2114 does not reach the 0.05 bar, so the transform arm is not distinguishable from the baseline floor at this sample size.
Every figure on this panel is read from the published run cl-realdata-cc-2026-06-18. The savings and parity numbers come from /proof/latest-numbers.json, and the gate verdict traces to the sealed gate document. The math chain is on the methodology page. No synthetic numbers, and cohorts below the k-anonymity floor are withheld.
Rendered 2026-08-15T19:50:30.337Z. Source: docs/proof/ in the QuestoM/cortex-lens repo (methodology.md, reproduce.ipynb, weekly-numbers/). The weekly files are written by the cost-efficiency-ide benchmark harness on its Monday cron. No synthetic metrics. If a source is unreachable the panel reports it.