bf8905fcc9
The init marker settled it. The diagnostic reported "THE REPORTER LOADED BUT RECORDED NO TEST EVENTS — the events file contains only the reporter's own reporter:init marker", which refutes the reporter-never-loaded hypothesis and leaves exactly one explanation. The runner spawns a child process per test file and surfaces a subtest's test:start / test:pass / test:fail to the parent's reporter only once the child REPORTS that test — which happens when it completes. The fixture hangs forever, so it never completes, so it never reports. I had recorded exactly those three event types: the precise set that a hang guarantees you will never see. The feature could not have worked for the case it was built for. test:enqueue and test:dequeue are emitted by the runner as it queues and begins each file, independent of anything inside finishing. test:dequeue is what actually means "in flight", and it is now the primary signal, with test:start kept as a secondary one. A file is in flight when it has been dequeued and has no terminal event. The four branches now describe states that are all real: the events file absent (reporter never loaded); the init marker alone (the runner dequeued nothing at all — genuinely surprising now rather than the expected outcome); everything dequeued and terminated (the files finished and the process hung afterwards, a handle leak); and one or more dequeued-but-unterminated files, named, which is the case this whole feature exists to report. Verified against the exact shape the real hang produces, by executing analyzeChunkEvents on a synthetic events file: init + enqueue + dequeue with no terminal event reports hangs.test.cjs as in flight, and appending a test:pass clears it. Four more unit tests cover the ordering and multi-file cases with no subprocess, so this logic is now checkable without a runner round-trip — which matters, because every defect in this feature so far was visible only remotely. T1 is untouched and should now pass for the right reason. Verification runs on the remote runner. Refs #4012
GSD Core
Git. Ship. Done.
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A light-weight meta-prompting, context engineering, and spec-driven development system for Claude Code, OpenCode, Antigravity CLI, Kimi CLI, Kilo, Codex, Copilot, Cursor, Windsurf, and more.
What is GSD Core
GSD Core is a context-engineering and spec-driven development framework that drives AI coding agents (Claude Code, Codex, Antigravity CLI, Kimi CLI, Copilot, Cursor, and more) through a disciplined phase loop. It solves context rot — the quality degradation that accumulates as an AI fills its context window — by running all heavy research, planning, and execution work in fresh-context subagents while keeping your main session lean.
How it works
Each milestone repeats the same five-step loop, one phase at a time:
- Discuss — capture implementation decisions before anything is planned
- Plan — research, decompose, and verify the plan fits a fresh context window
- Execute — run plans in parallel waves; each executor starts with a clean 200k-token context
- Verify — walk through what was built; diagnose and fix before declaring done
- Ship — create the PR, archive the phase, repeat for the next one
Quickstart
npx @opengsd/gsd-core@latest
The installer prompts for your runtime (Claude Code, OpenCode, Antigravity CLI, Kimi CLI, Kilo, Codex, Copilot, Cursor, Windsurf, and more) and whether to install globally or locally. The installer is required for cross-runtime compatibility — do not copy files from agents/ or commands/ directly.
On another runtime or without Node.js? See Install on your runtime.
Once installed, start a new project or onboard an existing repo:
/gsd-new-project # greenfield project
/gsd-onboard # existing codebase
New here? Follow Your first project for a guided walkthrough from install to first shipped phase, or Onboarding an existing codebase for brownfield setup.
Documentation
What's new in 1.7.0 → docs/whats-new-1.7.0.md
Tutorials — learning by doing:
How-to guides — task-focused recipes:
Reference — authoritative facts:
Explanation — concepts and design decisions:
Full index: docs/README.md. Other languages: 日本語 · 한국어 · Português · 简体中文.
Why it works
Most AI-coding setups fail at scale because context bloat silently degrades output quality, there is no shared memory between sessions, and nothing verifies that code actually works. GSD Core solves all three: heavy work runs in fresh subagents, structured artifacts like STATE.md and CONTEXT.md survive session boundaries, and the verify step walks through what was built and generates fix plans before a phase is declared done. See docs/explanation/context-engineering.md for the full reasoning.
Troubleshooting? See docs/how-to/recover-and-troubleshoot.md.
Community
| Project | Platform |
|---|---|
| gsd-opencode | Original OpenCode port |
| Discord | Community support |
Star History
License
MIT License. See LICENSE for details.
Claude Code is powerful. GSD Core makes it reliable.