# harness-evaluator

> Compare agentic coding harnesses (Claude Code, Codex, Pi, OpenCode, OMP) on token efficiency, task effectiveness, time efficiency, and cost.

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## Home

- [harness-evaluator](https://yorch.github.io/harness-evaluator): harness-evaluator — Compare agentic coding harnesses (Claude Code, Codex, Pi, OpenCode, OMP, Aider, Gemini CLI, Antigravity, Copilot, Cursor, Kiro) on token efficiency, task effectiveness, and time efficiency.

## Docs

- [Adapters](https://yorch.github.io/harness-evaluator/docs/adapters): Adapter system, registry, per-harness details, observability tiers, and how harnesses connect to the gateway proxy.
- [Architecture](https://yorch.github.io/harness-evaluator/docs/architecture): How harness-evaluator's components interact and data flows through the system from config to results.
- [CLI Reference](https://yorch.github.io/harness-evaluator/docs/cli-reference): All harness-evaluator CLI commands, flags, and options with examples.
- [Configuration](https://yorch.github.io/harness-evaluator/docs/configuration): Run YAML config, task definitions, pricing tables, environment variables, and all configurable options.
- [Development](https://yorch.github.io/harness-evaluator/docs/development): Contributing to harness_evaluator, quality gates, code style, testing, project conventions, and CI.
- [Docker Runner](https://yorch.github.io/harness-evaluator/docs/docker-runner): Container isolation, security hardening, and how harnesses execute inside Docker containers.
- [Evaluators](https://yorch.github.io/harness-evaluator/docs/evaluators): SWE-bench-style hidden-test evaluator and open-ended LLM judge track with rubric, structural checks, and calibration.
- [Gateway Proxy](https://yorch.github.io/harness-evaluator/docs/gateway-proxy): Custom HTTP/SSE proxy that intercepts provider API calls for token, cost, and latency accounting.
- [Getting Started](https://yorch.github.io/harness-evaluator/docs/getting-started): Install harness-evaluator from PyPI, pull the Docker image, set API keys, and run your first evaluation — no clone required.
- [Multi-phase Evaluation](https://yorch.github.io/harness-evaluator/docs/guides/multi-phase): Chain implementation and adversarial review models in a single task with per-phase cost attribution.
- [Subscription Auth](https://yorch.github.io/harness-evaluator/docs/guides/subscription): Run harness-evaluator with a Claude Code (OAuth) or Codex (ChatGPT) subscription instead of pay-per-token API keys.
- [Orchestrator](https://yorch.github.io/harness-evaluator/docs/orchestrator): Eval matrix building, budget caps with atomic reservation, retry logic, and cell-level resumability.
- [Reporting](https://yorch.github.io/harness-evaluator/docs/reporting): Static reports (HTML/JSON/CSV), interactive FastAPI dashboard, and REST API endpoints.
- [Statistics](https://yorch.github.io/harness-evaluator/docs/statistics): Mixed-effects models, variance decomposition, bootstrap confidence intervals, and consistency analysis for eval results.