Results for agent-eval

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Shared domain types and Zod schemas for agent-eval-harness

Trajectory loading, evaluation, and comparison for agent-eval-harness

Cost tracking, budget management, and reporting for agent-eval-harness

Latency monitoring, SLA enforcement, and optimization analysis for agent-eval-harness

Golden trajectory management, comparison, and curation for agent-eval-harness

OpenTelemetry observability (tracing, metrics, logging, dashboards) for agent-eval-harness

Orchestrated evaluation suite runner with results aggregation for agent-eval-harness

Tool-use validation (selection, schema compliance, result verification) for agent-eval-harness

Provider-agnostic LLM-as-judge with calibration and consensus for agent-eval-harness

Evaluate and improve AI agents from runs, traces, judges, and feedback. Compare candidates, cluster failures, measure lift, and gate releases.

The agent eval standard for MCP. Score every agent output for quality, safety, and cost.

Web-based playground for browsing agent-eval experiment results

CI regression gates, threshold checks, and JUnit/GitHub integration for agent-eval-harness

Three-layer MCP tool server (judge, suite, gate) for agent-eval-harness

CLI interface for agent-eval-harness with eval, judge, compare, gate, golden, report, and serve commands

Framework for testing AI coding agents in isolated sandboxes

Agent evaluation framework with LLM-based grading for AI agent quality assessment

General-purpose eval harness for running trials against CLI agents

TypeScript client for the AumOS agent-eval evaluation framework — benchmarks, metrics, and run comparisons

evaluate statically-analyzable expressions

Compare coding agents head-to-head. Pass rate, cost, time, consistency — one command.

Static + schema + routing + spawn-fixture eval harness for *.md subagents (Claude Code, etc.). Catches description bloat, fence-mimicry, low routing margin, and schema regressions before they ship.

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