c09c13f295
The #1279 node-test machine-proof confirmed a known-bad subject drives the negative test RED, but could not distinguish a genuine content-violation from a deceptive test that reds merely because GSD_PROHIB_SUBJECT is set. Add an optional fifth flat scalar `check_clean_fixture` (-> CheckDescriptor.cleanFixture) threading a KNOWN-CLEAN control subject through projectProhibitions + descriptorFromProjection. When present, the prover also runs the check against the clean subject and requires GREEN, so fail-first is proven only when the check is RED on the violation AND GREEN on the clean subject (content-dependent). Opt-in and additive: absent a clean fixture the prover behaves exactly as post-#1314 (no control, documented residual), preserving the zero-authoring compose path; the lint-rule kind needs no analog (its subject IS the linted file, no env indirection). Coverage: RED-first deceptive case, positive, missing-clean fail-closed, round-trip read-back/emit, fast-check property extended to the 5th scalar, and an end-to-end COMPOSE capstone (honest vs deceptive). Docs: ADR-550 dated addendum, prohibition-probe reference, spec-phase + verify-phase workflows. Closes #1346 Claude-Session: https://claude.ai/code/session_01GsPRb8zvpcT7Eat6vZw8PX
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.
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:
- 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, 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
License
MIT License. See LICENSE for details.
Claude Code is powerful. GSD Core makes it reliable.