Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/garrytan/gstack/agents-mdgit clone --depth 1 https://github.com/garrytan/gstackWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.01962 | $0.01962 |
| Opus 5 | $0.00981 | $0.00981 |
| Sonnet 5 | $0.00392 | $0.00392 |
| Haiku 4.5 | $0.00196 | $0.00196 |
Grade C, and why
gstack AGENTS.md scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
| `/careful` | Warn before destructive commands (rm -rf, DROP TABLE, force-push). | How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gstack — AI Engineering Workflow
gstack is a collection of SKILL.md files that give AI agents structured roles for software development. Each skill is a specialist: CEO reviewer, eng manager, designer, QA lead, release engineer, debugger, and more.
Available skills
Skills live in .agents/skills/ (or ~/.claude/skills/gstack/ on Claude Code).
Invoke them by name (e.g., /office-hours).
Plan-mode reviews
| Skill | What it does |
|---|---|
/office-hours |
Start here. Reframes your product idea before you write code. |
/plan-ceo-review |
CEO-level review: find the 10-star product in the request. |
/plan-eng-review |
Lock architecture, data flow, edge cases, and tests. |
/plan-design-review |
Rate each design dimension 0-10, explain what a 10 looks like. |
/plan-devex-review |
DX-mode review: TTHW, magical moments, friction points, persona traces. |
/plan-tune |
Self-tune AskUserQuestion sensitivity per question. |
/autoplan |
One command runs CEO → design → DX → eng review (eng always last). |
/design-consultation |
Build a complete design system from scratch. |
/spec |
Turn vague intent into a precise, executable spec in five phases. Files a GitHub issue, optionally spawns a Claude Code agent in a fresh worktree, and lets /ship close the source issue on merge. |
Implementation + review
| Skill | What it does |
|---|---|
/review |
Pre-landing PR review. Finds bugs that pass CI but break in prod. |
/codex |
Second opinion via OpenAI Codex. Review, challenge, or consult modes. |
/investigate |
Systematic root-cause debugging. No fixes without investigation. |
/design-review |
Live-site visual audit + fix loop with atomic commits. |
/design-shotgun |
Generate multiple AI design variants, comparison board, iterate. |
/design-html |
Generate production-quality Pretext-native HTML/CSS. |
/devex-review |
Live developer experience audit (TTHW measured against the real flow). |
/qa |
Open a real browser, find bugs, fix them, re-verify. |
/qa-only |
Same methodology as /qa but report only — no code changes. |
/scrape |
Pull data from a web page. First call prototypes; codified call runs in ~200ms. |
/skillify |
Codify the most recent successful /scrape flow into a permanent browser-skill. |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 138 lines · 1,962 tokens per session scan C d5f1261f5332
gstack AGENTS.md is an instructions file published in the GitHub repository garrytan/gstack (130,427 stars, last pushed 2d ago), licensed MIT. It adds 1,962 tokens to every session, about $0.0098 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
buildNext
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
spec-kit AGENTS.md
Instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
langchain AGENTS.md
Instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.