7f2af28639
Third failure on this feature, and this one broke everything rather than just the diagnostic: 43 failures across every run-tests.cjs invocation. Error: EINVAL: invalid argument, fsync Emitted 'error' event on WriteStream instance Node opens a WriteStream for a --test-reporter-destination and FSYNCS it on close. fsync on /dev/null is EINVAL — it is a character device, not a regular file. So os.devNull is not a usable reporter destination at all, and every chunk crashed on exit. The sink only ever needed to be a regular file that stays empty, since the reporter writes its real output through appendFileSync to the path in GSD_RUN_TESTS_EVENTS_FILE. It is now one fixed file inside the existing events dir, pre-created rather than relying on the stream's create-on-open, and left empty by design. One sink for the whole run, not per chunk, so its path length stays constant — reporterOverhead feeds FIXED_OVERHEAD, which is computed once before chunking, and a variable-length path would silently mis-account the Windows argv ceiling. The comment that named devNull now says why the destination must be a regular file, so this does not get re-optimized back into the same crash. Reaching for devNull was the mistake: it looks like the obviously correct way to discard output, and it is, for a pipe or an fd — but not for something Node is going to fsync. Each of the three failures on this feature was a different edge of the same assumption, that a reporter destination behaves like ordinary output. The regression test asserts the closest externally observable consequence — a normal run must not surface the EINVAL/fsync text. The argv construction lives inside main() with no exported seam, and the sink is swept before a test could stat it; adding a seam purely to assert that is left out rather than reshaping production code for the test. Stated plainly rather than implied. The failing T1 is untouched and still red. 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.