a22333034b
* fix(#2310): guard Codex agent model_overrides so Anthropic aliases never leak into .toml generateCodexAgentToml embedded a per-agent `model_overrides` value verbatim as the Codex `.toml` `model`, leaking GSD/Claude tier aliases (opus/sonnet/haiku/fable) and `claude-*` ids. Codex/ChatGPT rejects those (400 "The 'sonnet' model is not supported when using Codex with a ChatGPT account"), and since spawn_agent has no inline model param, the model is baked into the .toml at install time — so the orchestrator could not recover and fell back to the non-equivalent generic-agent workaround. Translate a GSD tier alias through the Codex tier map (sonnet -> gpt-5.6-terra); drop with a deduped warning any Anthropic-flavored value with no Codex mapping (fable) or a `claude-*` id, so emission falls through to the runtime-aware resolver or Codex's default. A final safety gate blocks an Anthropic-flavored model from the runtime- resolver path too (runtime/target mismatch). Mirrors the Claude-side override guard (#2041). Real Codex/OpenAI model ids in model_overrides still pass through verbatim (#2256 preserved); runtime:"codex" tier resolution unchanged (#2517). Adds regression + fast-check property tests in tests/codex-config.test.cjs. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> * chore(#2310): backfill changeset PR number to #2312 * fix(#2310): Codex passive-model posture — omit Anthropic-flavored model (all namespacings) Adopt ADR-1239's passive/session-only posture for Codex model handling: a Codex agent .toml `model` is embedded ONLY for an explicit real-Codex model_overrides pin; any Anthropic-flavored value is omitted so the agent inherits the always- available session model (never a 400). - model_overrides tier alias (opus/sonnet/haiku/fable) or a Claude model id → omit (was: translate to gpt-*); an explicit real-Codex model id → embed verbatim (#2256 preserved). - Detect ALL Anthropic namespacings, not just `claude-*`: single-source the canonical CLAUDE_AGENT_ALIASES from model-resolver.cts and treat any id whose value contains "claude" (case-insensitive) as Anthropic-flavored — catching `anthropic/claude-*` and `us.anthropic.claude-*` (the forms the catalog assigns to opencode/hermes/kilo), which reach a Codex .toml via the runtime-resolver path on a mixed-runtime + Codex install. - The final safety gate applies to the runtime-resolver path too. The full passive posture (removing #2517's runtime-resolver per-tier embedding + a correctness health-check + a Codex TOML sync path) is tracked as the ADR-2310 epic #2313. Regression + fast-check property tests in tests/codex-config.test.cjs. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 <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.