Live Transparency Report

The System
Getting Better

Every agent output is evaluated. Every pattern is logged. Every week, the system publishes what it learned. This is the improvement loop in public.

Quality Score Trajectory

Average LLM-as-judge score across all agent outputs, by week.

Overall System

Average Output Quality — All Time

Knowledge Base

Lessons Learned Over Time

Per Agent

Agent Score Comparison (This Week)

Lessons in the System

Patterns extracted by meta-analysis every 50 evaluations. These are injected as improvement directives into future agent prompts.

How the Loop Works

Every output scored. Every pattern surfaced. Every week, a public report.

Step 1

Every Output Evaluated

Each agent output is scored by a local LLM judge on accuracy, usefulness, clarity, and completeness — scored 1–10 on each dimension.

Step 2

Patterns Extracted

Every 50 evaluations, a meta-analysis run synthesizes patterns from scores and feedback into concrete, named lessons.

Step 3

Directives Injected

Lessons become improvement directives that are automatically injected into agent system prompts — teaching every future run.

Step 4

Weekly Report Published

Every Sunday, this dashboard and a full improvement report are auto-generated. You're looking at the output of that loop right now.

Get the full improvement report

Signals subscribers get the uncut weekly report: strategy optimization details, Sharpe ratio changes from A/B testing, and model routing decisions.

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