proof

Measured, not claimed.

Every number on this page comes from the Warden runtime — shadow mode, the trust guard, and task outcome tracking. No models. No black boxes. No estimates. Just measured results you can verify yourself by running warden status.

72.3%
Token reduction
30-task benchmark suite, measured
100%
Trust guard pass rate
Every line verified byte-for-byte
8ms
Avg overhead
Negligible vs 1-10s agent API latency
30
Tasks benchmarked
6 categories: grep, file read, test, generic, shell, compress

WardenBench

Real pruning results across tool types. Every row is a measured run — not a projection. The guard verified 100% of pruned lines byte-for-byte.

TaskBeforeAfterReductionOverheadGuard
grep output (5 tasks, 402-line fixture)55,6556,94487.5%17ms100%
file read (5 tasks, 835-line source)45,3609,81478.4%6ms100%
generic / auto-routed (5 tasks)38,1663,49590.8%9ms100%
shell output (5 tasks, 24 command patterns)16,5564,22674.5%4ms100%
file compression (5 tasks, 3 levels)41,76327,93333.1%11ms100%
test log (5 tasks, 187 tests)17,0807,03758.8%4ms100%
OVERALL (30 tasks)214,58059,44972.3%8ms100%

Run your own benchmarks: npx tsx benchmarks/run-bench.ts — raw CSV + JSON output, one command, fully reproducible.

Four pillars of proof

Trust guard

Every pruned line must exist verbatim in the raw output. If even one line doesn't match, the raw is shipped instead. No exceptions, no heuristics.

Implemented in src/pruner/guard.ts — runs on every prune call, zero bypass path.

Shadow mode

Every new rule starts at 0% confidence. It observes traffic and compares pruned vs. raw in the background. Only after proving quality parity does it go live.

Confidence scored with exponential decay — recent evidence weighs more than stale evidence.

Regression watchdog

Task outcomes are tracked and correlated with pruning. If a rule's task success rate drops below baseline, it auto-reverts to shadow mode.

Powered by warden_record_outcome + warden_outcome_stats — the agent reports success/failure after each task.

Durable memory

Project decisions persist across sessions. The agent recalls past architecture choices, constraints, and patterns — so it doesn't re-derive them every time.

SQLite-backed, local-first. No cloud, no telemetry, no data leaving your machine.

The eval gate

Every pruning rule goes through this pipeline before it touches live traffic. No rule skips a step.

01
Observe (shadow)
New rule runs in shadow mode. It prunes output but ships the raw to the agent. Both versions are compared.
02
Score (confidence)
Each shadow run produces evidence. Confidence is calculated with exponential decay — 50+ runs at 0.9+ quality needed to promote.
03
Promote (live)
Once confidence crosses the threshold, the rule goes live. Pruned output ships to the agent. The user can force-promote sooner.
04
Watch (regressions)
Task outcomes are tracked. If success rate drops, the rule auto-reverts to shadow. The watchdog never sleeps.

Verify it yourself.

Install Warden, run warden status, and watch the numbers move in real time.

Get started →