9624167eec
* fix(#2810): accept the documented effortSurface axis on EoS registry entries The EoS registry schema required an exact eight-key `interactions.axes` object, while `docs/registries/README.md` and `CONTEXT.md` both documented nine keys including `effortSurface`. An entry that faithfully mirrored its upstream descriptor's `effortSurface` key was rejected outright. `effortSurface` reached the runtime-descriptor vocabulary through ADR-1239 amendment #2481 (`HOST_INTEGRATION_AXES`), but the registry's hand-maintained copy of that vocabulary never picked it up. The runtime-descriptor surface is guarded by tests/host-integration-validator-parity.test.cjs; the registry copy had no equivalent guard, which is what let the two drift. Accept `effortSurface` as an OPTIONAL ninth axis validated against the canonical ['argv','none'] rather than a required one: registry entries mirror their upstream registry/eos-entry.json byte-for-byte, so requiring it would retroactively invalidate every entry published before the amendment. Adds tests/registry-axes-parity.test.cjs, which asserts that every key shared between the registry vocabulary and HOST_INTEGRATION_AXES has an identical enum array, plus limit-1/limit/limit+1 boundary coverage on the axes key set. Closes #2810 * test(#2810): fail when a canonical axis is added but never mirrored The enum-equality assertion compares only keys the registry and HOST_INTEGRATION_AXES already share, so it is blind to the exact drift that produced #2810: a new canonical axis appears and the registry copy is never told. Verified by simulation — mutating an enum is caught, adding a new canonical key is not. Assert instead that every HOST_INTEGRATION_AXES key is either modeled by the registry or named in an explicit NOT_MODELLED allowlist (subagentToolkit and isolation, both dispatch sub-fields the registry collapses into its free-form dispatch summary). Adding a canonical axis now fails until someone decides which bucket it belongs in. The allowlist is itself guarded against going stale. Refs #2810 * fix(#2810): harden the axis value lookup with the CodeQL barrier pattern Both orthogonal reviews flagged the same line: `AXES[key] !== undefined` is not an own-property test, and the bracket reads are shaped like a prototype-pollution sink even though the unknown-key gate above provably makes them unreachable. Switch the presence test to `Object.hasOwn` and add the repo's inline literal guards (`capability-state.cts:146-155`, "Prototype-pollution guard (inline literal, CodeQL barrier)"), which CodeQL can follow where it cannot follow the `.includes()` filter that actually does the work. Behavior is unchanged — re-verified all five axes key-count shapes plus a genuine own `__proto__` property built through JSON.parse (the shape a third-party registry PR would submit): it is rejected as an unknown key and Object.prototype is untouched. Refs #2810 * chore(#2810): backfill changeset PR number
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.