f615eb9ef3
* fix(#1572): preserve must_haves object-lists across frontmatter set/merge spliceFrontmatter round-tripped the WHOLE frontmatter through extractFrontmatter (a scalar-only parser) then reconstructFrontmatter (a lossy serializer), so any must_haves object-list — artifacts {path, provides}, prohibitions {statement, status} — was flattened to scalar strings and re-emitted as a malformed inline array whenever an UNRELATED field changed, silently dropping every provides:/ status: value. The write now preserves the original raw text for any top-level key whose value is structurally unchanged between the original parse and the new object (generalizing the existing whole-document no-op guard to per-key fidelity), and regenerates only the key that actually changed. The key set is still defined by newObj (the cmdSet/cmdMerge flow always passes the full merged object). spliceFrontmatter's only callers are cmdFrontmatterSet/Merge — the STATE.md read-modify-write family calls reconstructFrontmatter directly and is unaffected. Regression cases folded into tests/frontmatter-cli.test.cjs: artifacts/prohibitions object-lists survive set and merge; idempotent on repeat sets. Asserted via parseMustHavesBlock (the structure-preserving parser). * chore(#1572): backfill changeset pr ref to 1656 * fix(#1572): fail-closed when set/merge would emit [object Object] (codex review) Adversarial review (codex, gpt-5.5/high) flagged that directly setting a must_haves object-list (a CHANGED key) still routed through the lossy reconstructFrontmatter, emitting literal "[object Object]" and destroying the data. The reported case (mutating an UNRELATED field) was already fixed by per-key raw-text preservation, but the changed-object-list path was still silently lossy. Add fail-closed: when a regenerated key's text contains the "[object Object]" sentinel, spliceFrontmatter throws — cmdFrontmatterSet/Merge error out WITHOUT writing, directing the user to edit the file directly. The no-frontmatter (generate-from-scratch) path is guarded the same way. Adds a test that a refused set leaves the file unchanged and the original object-list intact. Codex finding #2 (a contrived flattened-projection no-op) is a deeper limitation noted in the PR — non-destructive, and the fail-closed message already directs users to edit object-list blocks directly. * test(#1572): add spliceFrontmatter per-key preservation + fail-closed unit coverage Stryker mutates gsd-core/bin/lib/frontmatter.cjs against tests/frontmatter.{property,unit}.test.cjs (MinScore 62). The #1572 regression cases live in frontmatter-cli.test.cjs, which is NOT in Stryker's test set, so the new functions (sliceTopLevelFrontmatterSegments, the per-key preserve/regenerate/drop/append loop, regenerateFrontmatterKey's [object Object] fail-closed) had surviving mutants that dropped the module below threshold. Add unit-level coverage in frontmatter.unit.test.cjs exercising every new branch directly via spliceFrontmatter: unchanged object-list preserved (provides survives) when a scalar sibling changes; changed scalar regenerates only that key; orphan keys dropped; new keys appended; indented nested block stays attached to its parent key; whole-document no-op returns input verbatim; both fail-closed paths (changed object-list + no-frontmatter) throw.
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.