yacht-eval 0.4.0

Yet Another Coding Harness Testbed

YACHT

Yet Another Coding Harness Testbed.

YACHT is an evaluation control plane for agentic coding systems. It runs the same coding course across different agents, models, tools, prompts, memory systems, and runtime environments, then records the evidence needed to decide whether a change actually helped.

The goal is not only to produce benchmark scores. A useful YACHT run should also answer:

• Did the setup solve the task?
• Was the runtime available, isolated, and configured as claimed?
• Which tools were actually used?
• How many tokens did the run spend?
• What did it cost?
• How long did it take?
• Which artifacts prove the result?

YACHT is designed as open-source infrastructure for reproducible, inspectable coding-agent evaluation.

Current Status

YACHT runs real end-to-end benchmark comparisons:

• two real harness adapters: containerized Pi and containerized Claude Code
• rigging for tools under test: agent extensions, config files, pinned npm packages, and MCP servers rendered into the harness's own configuration
• explicit secret injection, runtime and rigging preflight before tokens are spent
• SWE-bench Lite task context loading, per-task repository checkout, agent task attempts and transcripts, candidate patch extraction, and native SWE-bench Docker grading
• a Terminal-Bench 2.0 course that delegates rollout and verification to the official Harbor harness: YACHT-owned agents install the pinned harness and rigging inside each task container, orchestrated from a pinned launcher image, with install-only preflight before tokens are spent
• benchmark scorecards with outcome, token, cost, duration, and tool-use metrics, plus run provenance (harness, model, and tool versions resolved from evidence)
• self-contained HTML reports with verdict banners and variance badges, and a local read-only dashboard (yacht serve) that filters and groups runs by provenance

See the Validating a Tool Claim tutorial for the core workflow: turn a tool's claim into a pinned, preflighted comparison and read the verdict.

Core Concepts

Concept	Meaning
Course	A benchmark suite, task set, or evaluation route.
Vessel	An agent, model, runtime, or full coding setup being evaluated.
Rigging	Tools, prompts, skills, MCP servers, memory systems, and policies added to a vessel.
Runtime	The reproducible environment used to run a vessel.
Preflight	Machine evidence that a runtime and its rigging are available, configured, and isolated before spending task tokens.
Wake	The artifacts left by a run: transcripts, metrics, logs, tool calls, patches, reports.
Logbook	The persisted directory containing a run's wake and scorecards.
Scorecard	The final comparison view across vessels.

The nautical vocabulary is part of the project identity, but the artifacts stay plain JSON so other tools can consume them.

First Real Benchmark

Prerequisites:

• Python 3.12 or newer available to uv
• uv
• Git on PATH
• Docker installed, running, and usable by the current user
• network access for the first uv dependency sync, SWE-bench metadata, and Docker image build
• no manual SWE-bench install: uv resolves the swebench harness on demand for native benchmark launches, and yacht doctor performs and verifies the first resolution
• an Anthropic API key exported as ANTHROPIC_API_KEY
• the repo-local Pi runtime image built with the command below

Build the Pi runtime image:

docker build -t yacht/pi-agent-runtime:pi-0.74.0 containers/pi-agent-runtime

Run the benchmark smoke:

LOGBOOK=/private/tmp/yacht-real-benchmark-$(date +%Y%m%d-%H%M%S)

uv run yacht doctor examples/container-pi-fff-real-benchmark-smoke.toml

uv run yacht run examples/container-pi-fff-real-benchmark-smoke.toml \
  --logbook "$LOGBOOK" \
  --workspace . \
  --secret anthropic=@env:ANTHROPIC_API_KEY

uv run yacht status --logbook "$LOGBOOK"
uv run yacht report --logbook "$LOGBOOK"
uv run yacht report --logbook "$LOGBOOK" --vessel pi-container-fff

The default smoke config runs one SWE-bench Lite instance to keep iteration cheap. For a slightly broader two-instance check, use examples/container-pi-fff-real-benchmark-small.toml with the same commands.

Fish shell:

set -x LOGBOOK /private/tmp/yacht-real-benchmark-(date +%Y%m%d-%H%M%S)

uv run yacht doctor examples/container-pi-fff-real-benchmark-smoke.toml

uv run yacht run examples/container-pi-fff-real-benchmark-smoke.toml \
  --logbook "$LOGBOOK" \
  --workspace . \
  --secret anthropic=@env:ANTHROPIC_API_KEY

uv run yacht status --logbook "$LOGBOOK"
uv run yacht report --logbook "$LOGBOOK"

The status report is the first thing to inspect after a run. It shows which benchmark artifacts exist, what is missing, and the next recommended command. The benchmark report then summarizes benchmark outcome, agent usage metrics, notable deltas, per-task outcomes, per-task usage, and the relevant per-vessel artifact paths. Use --vessel and --task to narrow the detailed sections when inspecting a specific run. After a scorecard exists, yacht status recommends a filtered inspection command for the first challenger/task outcome. For example:

Benchmark scorecard: container-pi-fff-real-benchmark-small / swe-bench-lite
Status: complete
Comparisons: 1 | Vessels: 2 | Measured: 2 | Missing: 0
Usage: Attempts: 4 | Failed: 0 | Tool calls: 15 | Tokens: 63084 | Cost: 0.020688 | Duration: 210.332s
Artifacts: logbook=/private/tmp/yacht-real-benchmark-... | scorecard=/private/tmp/yacht-real-benchmark-.../benchmark-scorecard.json | attempts=/private/tmp/yacht-real-benchmark-.../task-attempt-scorecard.json | launch=/private/tmp/yacht-real-benchmark-.../benchmark-launch-result.json | grading=/private/tmp/yacht-real-benchmark-.../benchmark-grading-collection.json

Notable deltas:
container-pi-vs-pi-fff-benchmark-small: pi-container-fff vs pi-container-baseline | resolved +0 | rate +0.000 | tokens +10988 | cost +0.001650 | duration +7.792s | tool_calls +3

comparison | baseline | challenger | resolved_delta | rate_delta | measured | missing | eligible | preflight
container-pi-vs-pi-fff-benchmark-small | pi-container-baseline | pi-container-fff | +0 | +0.000 | 2/2 | 0 | 2 | preflight-passed:2

Agent usage by task:
comparison | vessel | task | tools | tokens | cost | duration | attempt_artifact
container-pi-vs-pi-fff-benchmark-small | pi-container-fff | django__django-11179 | fffind:1, read:1, bash:1, edit:1 | 25492 | 0.006795 | 75.793s | /private/tmp/yacht-real-benchmark-.../task-attempts/.../django__django-11179.json

Development Smoke

For a no-token local harness check:

uv run yacht validate examples/local-agent-preflight-smoke.toml
uv run yacht run examples/local-agent-preflight-smoke.toml --logbook logbook
uv run yacht status --logbook logbook
uv run yacht report --logbook logbook

This validates the control-plane path without Pi, SWE-bench, Docker grading, or provider credentials.

Documentation

• Project vision
• Roadmap
• Audit-backed plan
• Codebase structure
• Validating a tool claim
• Command reference
• Terminal-Bench course
• Release checklist
• Schema contract
• Architecture decisions
• Changelog

License

YACHT is licensed under the Apache License 2.0.

Design Principles

• Prefer reproducible, inspectable evidence over agent attestation.
• Keep runtime provisioning separate from benchmark task grading.
• Make secrets explicit and never copy user-home auth state implicitly.
• Treat benchmarks, smoke tests, and future evaluators as adapters.
• Keep public artifacts language-neutral and stable enough for other tools to consume.
• Report success together with cost, tokens, time, tool use, and failure modes.