Tom Boucher d101daff30 fix(#1516): expose adaptive model_profile in /gsd-new-project AI Models prompt (#1654)
* fix(#1516): expose adaptive model_profile in /gsd-new-project AI Models prompt

Both onboarding paths (Step 2a auto-mode + Step 5 interactive) enumerated only
4 profiles (Balanced/Quality/Budget/Inherit), omitting 'adaptive' even though the
model catalog (model-catalog.json profiles) and docs/CONFIGURATION.md register 5.
Mirrors the proven /gsd:settings two-question split (#3784): Q1 routes between
Adaptive/Standard-tier/Inherit; Q2 (conditional on Q1=Standard) picks
Quality/Balanced/Budget — keeping every AskUserQuestion within the 4-option cap.
Both config-new-project example payloads now list adaptive. Regression cases
folded into the owning tests/new-project-mvp-prompt.test.cjs (per the
lint-regression-test-names ban on new top-level bug-NNNN files): each AI Models
prompt makes adaptive reachable, all 5 profiles reachable, 4-option cap honored,
both example enums include adaptive, brace balance. Workflow size baseline bumped
(new-project.md 62324 -> 66138 bytes; still well under the XL hard cap).

* chore(#1516): backfill changeset pr ref to 1654
2026-06-24 14:46:44 -04:00

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, Gemini CLI, Kimi CLI, Kilo, Codex, Copilot, Cursor, Windsurf, and more.

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What is GSD Core

GSD Core is a context-engineering and spec-driven development framework that drives AI coding agents (Claude Code, Codex, Gemini 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, Gemini 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.

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