gs:autoplan

gs:autoplan is a skill for Claude Code, Codex from thanh-abaii/gstack-windows-port. It costs 138 tokens per session (20,247 once invoked), scanned A, original, MIT.

An automated review process that combines executive, design, engineering, and developer-experience reviews into one plan.

In plain words
What is it for?
It runs the listed reviews in sequence, makes automatic decisions using six principles, surfaces disagreements or borderline choices, and produces a reviewed plan.
Why use it?
It helps organize several kinds of product and code review and brings uncertain decisions together for final approval.

Skill for Claude CodeCodex

Written for Claude Code and Codex: allowed-tools in frontmatter, but also agents/openai.yaml present. Also seen: mentions CLAUDE.md; mentions subagents; names the AskUserQuestion tool.

Good fit It runs the listed reviews in sequence, makes automatic decisions using six principles, surfaces disagreements or borderline choices, and produces a reviewed plan.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/thanh-abaii/gstack-windows-port/gstack-autoplan
Install

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.

Any agent
npx skills add thanh-abaii/gstack-windows-port --skill gstack-autoplan
Clone the repo
git clone --depth 1 https://github.com/thanh-abaii/gstack-windows-port

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for gs:autoplan

README.md
[![agentmods](https://agentmods.dev/badge/skills/thanh-abaii/gstack-windows-port/gstack-autoplan.svg)](https://agentmods.dev/skills/thanh-abaii/gstack-windows-port/gstack-autoplan)
Your own site
<a href="https://agentmods.dev/skills/thanh-abaii/gstack-windows-port/gstack-autoplan"><img src="https://agentmods.dev/badge/skills/thanh-abaii/gstack-windows-port/gstack-autoplan.svg" alt="Measured on agentmods" height="20"></a>
Per session 138 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 20,247 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00138 $0.20247
Opus 5 $0.00069 $0.10124
Sonnet 5 $0.00028 $0.04049
Haiku 4.5 $0.00014 $0.02025

Measured 8d ago against content hash 0e224a0f853f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

gs:autoplan scanned grade A with 0 findings 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 8d ago.

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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/gstack-autoplan/SKILL.md · 1,750 lines

How it starts

The opening of the file, as written. The whole thing — 1,750 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Preamble (run first)

python "bin/gstack-boot.py" --skill autoplan | iex

If PROACTIVE is "false", do not proactively suggest gstack skills AND do not auto-invoke skills based on conversation context. Only run skills the user explicitly types (e.g., /gs:qa, /gs:ship). If you would have auto-invoked a skill, instead briefly say: "I think /skillname might help here — want me to run it?" and wait for confirmation. The user opted out of proactive behavior.

If SKILL_PREFIX is "true", the user has namespaced skill names. When suggesting or invoking other gstack skills, use the /gstack- prefix (e.g., /gstack-qa instead of /qa, /gstack-ship instead of /ship). Disk paths are unaffected — always use $GSTACK_ROOT/[skill-name]/SKILL.md for reading skill files.

If output shows UPGRADE_AVAILABLE <old> <new>: read $GSTACK_ROOT/gstack-upgrade/SKILL.md and follow the "Inline upgrade flow" (auto-upgrade if configured, otherwise AskUserQuestion with 4 options, write snooze state if declined). If JUST_UPGRADED <from> <to>: tell user "Running gstack v{to} (just updated!)" and continue.

If WRITING_STYLE_PENDING is yes: You're on the first skill run after upgrading to gstack v1. Ask the user once about the new default writing style. Use AskUserQuestion:

v1 prompts = simpler. Technical terms get a one-sentence gloss on first use, questions are framed in outcome terms, sentences are shorter.

Keep the new default, or prefer the older tighter prose?

Options:

  • A) Keep the new default (recommended — good writing helps everyone)
  • B) Restore V0 prose — set explain_level: terse

If A: leave explain_level unset (defaults to default). If B: run $GSTACK_BIN/gstack-config set explain_level terse.

Always run (regardless of choice):

Remove-Item -Force ~/.gstack/.writing-style-prompt-pending
touch ~/.gstack/.writing-style-prompted

This only happens once. If WRITING_STYLE_PENDING is no, skip this entirely.

If LAKE_INTRO is no: Before continuing, introduce the Completeness Principle. Tell the user: "gstack follows the Boil the Lake principle — always do the complete thing when AI makes the marginal cost near-zero. Read more: https://garryslist.org/posts/boil-the-ocean" Then offer to open the essay in their default browser:

open https://garryslist.org/posts/boil-the-ocean
touch ~/.gstack/.completeness-intro-seen

Only run open if the user says yes. Always run touch to mark as seen. This only happens once.

If TEL_PROMPTED is no AND LAKE_INTRO is yes: After the lake intro is handled, ask the user about telemetry. Use AskUserQuestion:

Help gstack get better! Community mode shares usage data (which skills you use, how long they take, crash info) with a stable device ID so we can track trends and fix bugs faster. No code, file paths, or repo names are ever sent. Change anytime with gstack-config set telemetry off.

Options:

  • A) Help gstack get better! (recommended)
  • B) No thanks

If A: run $GSTACK_BIN/gstack-config set telemetry community

If B: ask a follow-up AskUserQuestion:

How about anonymous mode? We just learn that someone used gstack — no unique ID, no way to connect sessions. Just a counter that helps us know if anyone's out there.

Options:

  • A) Sure, anonymous is fine
  • B) No thanks, fully off

If B→A: run $GSTACK_BIN/gstack-config set telemetry anonymous If B→B: run $GSTACK_BIN/gstack-config set telemetry off

Always run:

touch ~/.gstack/.telemetry-prompted

This only happens once. If TEL_PROMPTED is yes, skip this entirely.

If PROACTIVE_PROMPTED is no AND TEL_PROMPTED is yes: After telemetry is handled, ask the user about proactive behavior. Use AskUserQuestion:

gstack can proactively figure out when you might need a skill while you work — like suggesting /gs:qa when you say "does this work?" or /gs:investigate when you hit a bug. We recommend keeping this on — it speeds up every part of your workflow.

Read the full file on GitHub · 1,750 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 8d ago First seen · 1,750 lines · 138 tokens per session scan A 0e224a0f853f

Subscribe to this mod's changes

gs:autoplan is a skill published in the GitHub repository thanh-abaii/gstack-windows-port (35 stars, last pushed 3mo ago), licensed MIT. It adds 138 tokens to every session and 20,247 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens