76ef60ba25
* enhance(#4836): prefer the graphify CLI for planner and researcher graph queries The planner gets one knowledge-graph query per phase and the researcher two or three, and that single shot decides which modules the plan treats as related — and therefore how tasks are ordered into waves. It was spent on the built-in reader, which seeds by case-insensitive substring match over a node's label and description and then expands a hardcoded two hops. The phase "User Authentication" seeds on `author`, `authoring` and `unauthorized` with the same weight as `authenticate`, and when the inflated payload exceeds `--budget` the trimmer drops edges by confidence tier — so the highest-confidence tier can be discarded to fit a payload that bad seeding inflated in the first place. The graphify CLI is already a hard dependency of /gsd-graphify build, and it ranks seeds (IDF weighting, trigram fuzzy matching) and applies context filters before traversal. Both prompts now prefer it and fall back to the built-in reader, branching on `command -v graphify` — the same degradation shape the repo already uses for Context7 to ctx7. Binary presence is a self-satisfying gate: a graph can only exist if the binary built it, so the fallback covers edge cases (a CI checkout with a committed graph, a binary since removed), not the common path. No new config key and no new tool grant — both agents already have Bash. The planner additionally runs `graphify affected`. The reference states its own goal as "which subsystems may be affected by changes in this phase", which is literally reverse traversal by relation; the built-in reader only approximates it with undirected two-hop expansion and has no equivalent verb, so `affected` is skipped on the fallback path. `graphify status` now reports `graph_path`, the resolved absolute graph location, on both the present and the missing branch. The CLI takes the graph location as `--graph`, and the prompts must not re-derive `.planning/graphs/graph.json` for it: that would point the CLI at a non-existent local mirror in exactly the umbrella multi-repo setup `graphify.graph_path` (#1825) exists to serve. For the same reason the presence gate in both prompts is now the `status` call itself rather than a bare `ls` of the default location, which was already blind to the override. Known limit, stated in both prompts rather than implied: the two paths return different shapes. `graphify query` emits prose and has no `--json` flag; the built-in emits JSON with per-edge confidence tiers and budget_met/budget_estimate. `--budget` also counts rendered output on one and estimated payload bytes on the other (#2738) — same flag name, different unit. Both are read by a model and nothing machine-parses the injected block. With graphify absent from PATH the injected context is byte-identical to before. Closes #4836 Emitted-Drift-Ack-Growth: gsd-phase-researcher.md — the CLI-first branch, the reason it is preferred, and the output-shape warning are the deliverable; a pointer to a part would not be read at the decision point. Emitted-Drift-Ack-Growth: gsd-planner.md — one sentence in the load_graph_context step pointer, so it stops naming the default graph path the reference no longer assumes. * docs(#4836): record the CLI-first graph query in the planner and researcher entries * chore(#4836): add changeset fragment * enhance(#4836): name the full domain word in the planner's query-term examples The reference's own example — phase "User Authentication" → term "auth" — is the exact collision the CLI-first path exists to avoid, and it stays a collision whenever the fallback path runs, since that path matches the term as a substring of label and description. * fix(#4836): surface graph_path on the unparseable-graph status branch graphifyStatus() returned graph_path on the exists:true and exists:false outcomes but not on the third, error, outcome (graph.json present but unparseable). The planner/researcher prompts gate CLI-first dispatch on exists, not on this outcome, so a corrupt graph file made them fall through to the CLI-first branch with the literal <graph> placeholder and no real path to substitute. * docs(#4836): note graph_path's trust boundary at the --graph interpolation graph_path is reflected verbatim into a double-quoted --graph argument the agent executes via Bash. It comes from graphify.graph_path, a config surface already trusted elsewhere, so this isn't a new trust boundary -- but it is a new injection site (no --graph flag existed on this call before). One-line caution for anyone hardening this later. --------- Co-authored-by: Tom Boucher <trekkie@nomorestars.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.