sim 147856040b fix(#2873): close review findings across fences, sanitizer and docs
Isolated security review found resolveSpecRootReference's fence tracker
toggled on any delimiter, so a backtick fence could be closed by a tilde
one and an include in the gap was rewritten inside a code block. Fixed by
reusing scanFencedBlocks - the canonical engine already behind
stripFencedCode and extractFencedBlock - rather than carrying a fourth
copy of fence detection, which also closes the duplication the standards
review flagged.

sanitizeForRender now strips combining marks and zero-width characters
alongside the ANSI, control and bidi classes it already handled.

Adds the C, E and F matrix rows the spec review found missing, including
installer-level coverage that spawns the real install rather than calling
the report builder. Ships the how-to, the reference and command docs in
five locales, the changeset, the inventory and glossary entries, and
regenerates health.md for the new W028 rule.

Refs #2873
2026-08-14 23:48:39 -04:00

GSD Core

Git. Ship. Done.

English · Português · 简体中文 · 日本語 · 한국어

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.

npm version npm downloads Tests Discord GitHub stars License


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:

  1. Discuss — capture implementation decisions before anything is planned
  2. Plan — research, decompose, and verify the plan fits a fresh context window
  3. Execute — run plans in parallel waves; each executor starts with a clean 200k-token context
  4. Verify — walk through what was built; diagnose and fix before declaring done
  5. 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

Star History Chart

License

MIT License. See LICENSE for details.


Claude Code is powerful. GSD Core makes it reliable.

Description
No description provided
Readme MIT 77 MiB
Languages
JavaScript 82.3%
TypeScript 17.4%
Shell 0.3%