7dd9e59f6b
An allow-test-rule annotation citing a category that does not apply is worse than no annotation, because it reads as reviewed. Eight were confirmed by reading the assertions each one covered, and auditing the rest found five more plus one refutation — a converter test whose wording described the wrong mechanism while the covered assertion genuinely was deployed-text. The instructive one used the CANONICAL string for the same mistake: STATE.md command output labelled as a deployed artifact. A canonical string is not evidence the category fits, which is why normalising strings alone would have laundered the problem rather than fixed it. Every mapping the audit had inferred rather than code-verified was spot-checked before rewriting, and the ones that turned out not to fit were re-annotated rather than relabelled. Fourteen STATE.md assertions had a typed extractor available all along and now use it; their annotations came out because nothing needs exempting. Eight assertions genuinely need a production change first — CLI stdout and stderr with no structured mode — and are tagged pending-migration-to-typed-ir citing #3090, which is what that category is for. It had zero real uses before this, while one file carried a real citation to migration issue #2974 under a non-canonical tag. Six annotations covered assertions that do no text matching at all. An exemption for a violation that does not exist is noise that makes the real ones harder to audit; those are removed. atomic-write-coverage gains the annotation it always warranted — its own docstring describes a structural-regression-guard while the file carried none. Fifty-nine non-canonical strings across roughly thirty files are normalised, and the allow-test-rule allowlist is regenerated to match. 472 annotations became 463: every one now uses a canonical category, and the two remaining non-canonical strings are ESLint RuleTester fixtures, not annotations. Refs #3057 Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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.