Tom Boucher d671171698 feat(#1575): complete agent-converter descriptor cutover for copilot/antigravity + surface path parity
- Teach applySurface to build agentCtx (pathPrefix + attribution) and pass it
  to kind.stage() for agents kind, mirroring createRuntimeArtifactInstallPlan
  (ADR-1235 §1). Surface-path agents now receive path-rewrite + attribution +
  converter + normalize, matching install output byte-for-byte.

- Pass skills:'*' sentinel for agents staging when no surface state modifications
  exist, so ALL agents are staged (not just those referenced by _calls_agents_).

- Declare converted agents kind in copilot and antigravity capability.json;
  add to _DESCRIPTOR_AGENTS_RUNTIMES in bin/install.js.

- Handle copilot .agent.md filename rename in both _copyStaged (install path)
  and _syncGsdDir (surface path).

- Ship golden-parity harness (ADR-1235 §0): tests/issue-1575-agent-descriptor-
  parity.test.cjs asserts applySurface output is byte-identical to
  installRuntimeArtifacts for all 7 descriptor-driven runtimes, plus stale-
  cleanup convergence and prune data-loss coverage.

- Update ADR-1235 with cutover progress.

Cline remains deferred (rules-only local branch + local/global complication).
2026-07-06 11:34:32 -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 your first project:

/gsd-new-project

New here? Follow Your first project for a guided walkthrough from install to first shipped phase.


Documentation

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 80 MiB
Languages
JavaScript 82.2%
TypeScript 17.5%
Shell 0.3%