Testing

Claude Code Agent Runner

A harness that hands an AI coding agent real build tasks and measures what it can ship end-to-end — with the feedback loops that keep it honest.

GitHubUpdated Aug 6, 2026

Stack

TypeScriptClaude APIMCPNode

Problem

AI coding demos are cherry-picked. I wanted a repeatable way to measure what an agent can actually complete on real tasks, and where it fails.

Idea

A runner that gives the agent a task, a sandbox, and real checks (typecheck, lint, build, tests), then logs every attempt and failure mode.

Why I'm building it

This grew directly out of I Gave Claude Code an App to Build. The one-off experiment was interesting; a repeatable harness that scores it is useful.

Current state

  • ✅ Task spec format + sandboxed workspace per run
  • ✅ Feedback loop: typecheck / lint / build wired as tools
  • 🔬 Failure-mode logging (what broke, how it "fixed" it)
  • ⏳ Eval suite across a fixed task set
  • ⏳ Cost + wall-clock accounting per task

Development log

2026-08-06 — Added a dry-run mode after an early version made real network calls it shouldn't have. Guardrails first.

2026-07-29 — First fully-autonomous task completed end to end: a validated API endpoint with tests, no human edits.

Lessons so far

The agent optimizes to whatever check you give it. A weak test suite produces confident, wrong code that passes CI — so the eval design is the product.

Follow the builds

I email when a project ships a meaningful update, and when I start something new. Roughly monthly, never spam.

✶ No spam, promise! Unsubscribe anytime ✶