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On this page

  • The thesis
  • The skill map (at a glance)
  • How you install it
  • Design, browser automation, and security
  • Parallel sprints, CLIs, and ecosystem
  • Privacy and telemetry (per README)
  • A minimal “try it” path
  • Read next (explainx.ai)
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explainx / blog

gstack: Garry Tan’s open-source “software factory” for Claude Code (and nine other agents)

gstack packages YC-style slash skills—office hours, plan reviews, /review, /qa in a real browser, /cso, /ship—plus power tools, OpenClaw integration, and optional CLIs. Here is a detailed map of the repo, multi-host install, and how it fits explainx.ai’s view of agent skills.

Apr 24, 2026·4 min read·Yash Thakker
Claude CodeAgent skillsY CombinatorOpen sourceAI agentsOpenClaw
go deep
gstack: Garry Tan’s open-source “software factory” for Claude Code (and nine other agents)

gstack is Garry Tan’s public release of a large, Claude Code-centric, multi-host skill stack: on the order of 23 specialist slash workflows, eight “power” tools, MIT license, no paywall. The README leads with a reproducible take on “logical” change and line counts (On the LOC Controversy) and with GitHub contribution density (2026 vs 2013) on the author’s own repositories—then argues for gstack as the sprint process he uses in the open.

This explainx.ai note is a map, not a replacement for upstream docs. github.com/garrytan/gstack is canonical for install commands, slash names, and per-release features (for example the v0.19 CLIs mentioned in the README). Browse gstack on explainx.ai: explainx.ai/skills/gstack (pre-filtered skills registry view).

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The thesis

Turn a long chat into a repeatable sprint where the output of one slash skill feeds the next: think → plan → build → review → test → ship → reflect.

Upstream frames that as a process, not a grab bag of prompts. It overlaps the “skills compound if you chain them” idea in our agent skills guide, at YC-style cadence.


The skill map (at a glance)

ArchetypeExamples (see latest README)
Product and planning/office-hours, /plan-ceo-review, /plan-eng-review, /plan-design-review, /plan-devex-review, /autoplan
Design/design-consultation, /design-shotgun → /design-html (Pretext-style responsive layout, framework detection—see docs)
Code quality/review (Claude), /codex (OpenAI Codex CLI “second opinion” with multiple modes), /investigate
Runtime truth/qa / /qa-only, /browse, /open-gstack-browser, /setup-browser-cookies
Security/cso (OWASP + STRIDE, per upstream copy)
Release/ship, /land-and-deploy, /canary, /benchmark, /document-release
Meta/retro, /learn, optional checkpoint mode with /context-restore, /gstack-upgrade
Safety/careful, /freeze, /guard, /unfreeze
Multi-agent/pair-agent (shared GStack Browser with tab isolation, optional remote use—see docs)

Philosophy per skill: docs/skills.md. Builder framing: ETHOS.md.


How you install it

  1. Solo — shallow clone into ~/.claude/skills/gstack, run ./setup, add a CLAUDE.md gstack block that (a) routes web work through /browse and (b) lists slash commands. The long canonical list is only in the upstream README; do not copy stale lists from blogs.
  2. Team — gstack-team-init in required or optional mode commits .claude/ metadata so peers auto-install; setup --team plus silent hourly update checks.
  3. OpenClaw — spawn Claude Code with gstack loaded, or use ClawHub “native” skills for a subset. See docs/OPENCLAW.md.
  4. Other coding agents — ./setup --host <name> to install under paths such as ~/.codex/skills/, ~/.cursor/skills/, and others listed in the README. Extending a host: docs/ADDING_A_HOST.md.

Requirements (per README): Claude Code, Git, Bun 1+; Windows also Node (Playwright + Bun pipe issue—upstream documents fallback to Node).


Design, browser automation, and security

  • Shotgun → HTML — variant mockups (the README cites GPT Image-class generation in places), a browser comparison board, and gstack-taste-update to persist what you keep vs reject.
  • Browse stack — GStack Browser with a sidebar mini-agent, $B handoff for MFA or CAPTCHAs, and a substantial prompt-injection story (classifiers, canary tokens, optional heavier ensemble, kill-switch env vars).

Before you aim this at untrusted pages or a compliance boundary, read ARCHITECTURE.md and BROWSER.md. This post is not a security audit.


Parallel sprints, CLIs, and ecosystem

  • Conductor and the README’s “10–15 parallel sprints” are presented as a human coordination layer on many isolated Claude Code sessions: process tames agent proliferation, not the reverse.
  • CLIs (the README cites v0.19+): gstack-model-benchmark (Claude, GPT, Gemini; --dry-run to validate), gstack-taste-update (persist design shotgun taste).
  • /codex is a cross-model second opinion on the same diffs as /review, with overlap/unique-finding analysis when both have run.
  • Checkpoint mode (opt-in) auto-commits WIP with structured [gstack-context]; /ship is documented to squash or filter WIP commits in a bisect-safe way (see the README).

Privacy and telemetry (per README)

  • Default off; first run asks. If enabled, only skill name, duration, success, version, OS.
  • Never (claimed in README): code, file paths, prompts, branch names.
  • Supabase + edge functions; schema in supabase/migrations/. Local gstack-analytics on JSONL.

A minimal “try it” path

  1. Install per Install — 30 seconds.
  2. Run /office-hours on a real user pain, not a feature wish list.
  3. Run /review on a real branch.
  4. If it clicks, add /qa on a staging URL, then /ship.

Hiring (upstream README): Y Combinator — software (not affiliated with explainx.ai; listed for completeness).


Read next (explainx.ai)

  • What are agent skills? Complete guide
  • MCP: Model Context Protocol
  • Caveman: token economics for agents
  • Claude Code, Pro, and the April 2026 pricing test
  • Naval podcast roundtable: Gary Tan, Daniel & Farbood on AI compute, jobs, and ASI — Gary Tan describes building GStack in this July 2026 founder conversation.

The GitHub default branch README and CHANGELOG are the canonical feature and version sources; star counts and social screenshots go stale in hours.

Yash Thakker

Written by

Yash Thakker

Yash is an AI expert with over 300K learners. Join his workshops →

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