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reflect

@jtaroreh⭐ 80 stars

Spawn three parallel review subagents over the active transcript, surface learnings, and route each to a concrete edit on an existing skill. Use when the user says reflect.

Choose how to use this skill

You do not need every option. Choose the path your AI client supports. The stable page stays the same; versioned files are immutable.

1. Native installer

This listing has no registered native installer command. Use the complete package or source fallback below, depending on what your client supports.

Do not guess an installer command or replace an existing version without reviewing the diff.

2. Complete package recommended

Download the ZIP when available. It includes SKILL.md plus the references, security notes and version metadata.

No complete ProSkills package is published for this listing yet.

3. Prompt-only

Copy the prompt above when the agent can read the stable page or when you want to adopt the workflow without installing a skill.

Need only the instruction file?

Download SKILL.md only if your client requires a single file. The complete ZIP is safer for a full installation because it preserves the references and release context.

No path installs or executes anything by itself. Your agent still needs access to the project files. Before updating, compare the installed version and review the diff.

—/10

// RATINGS

⭐GitHub Stars
⭐⭐ 80 on GitHubGitHub ↗

Growing

🟢ProSkills Score
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📍

Not yet listed on ClawHub or SkillsMP

// README

agystack

CI License: MIT Antigravity Plugin Python 3.11+ Bun 1.0+

agystack is an agentic engineering framework for Google Antigravity, created by Joel Taroreh. It equips autonomous agents with a set of rigorous skills, playbooks, and cloud swarms built on the anti-slop foundation of poteto's Cursor pstack.

Where pstack brought anti-slop rigor to editor chats, agystack expands it into a distributed, multi-tier engineering fleet:

  • Google Cloud Run Fleets (/swarm). When local machines hit limits, fan out across headless cloud containers. Fleet workers run in parallel, stream real-time milestones, and deliver isolated candidate patches to GCS without git worktree collisions.
  • The /loop Hillclimb Engine. Run automated hypothesis-and-verify loops against a concrete test command (--verify "<cmd>"). agystack applies discrete edits, reverts regressions, and reactively iterates until green without manual babysitting.
  • Automated PR Babysitting & Stack Shipping (watch-pr). Eliminate GitHub PR friction. Dedicated tooling monitors CI checks, detects merge conflicts across Graphite stacks, and triages review comments. Real defects get fixed with runtime reproduction, while bot noise gets dismissed with concrete reasons.
  • Adversarial Reviews & Bakeoffs (/interrogate, /arena). Prevent single-agent blind spots. Dispatch concurrent reviewers to attack diffs from independent angles before shipping, or run competing candidate implementations in parallel worktrees and graft winning pieces sequentially.
  • Subagent Context Isolation & Anti-Slop Discipline (/deslop, comment-sicko). Coordinator contexts stay fast and clean by delegating code modifications over 50 lines to isolated subagents, while dedicated reviewers actively strip defensive bloat, AI apologies, and narrative comments before merge.

Underneath the platform additions is the core engineering philosophy that started it:

"i'm not a president or ceo, but i've worked with millions of lines of code at Meta, Netflix, and Cursor. i'm also on the react core team where i help build and maintain react compiler.

there's a growing sense that ai writes too much slop code. i agree. i don't want to ship like a team of twenty slop artists. throughput without quality is not a goal i aspire to. if you want to go fast, go deep first."

— Lauren Tan (poteto)

The goal is not to maximize lines of code. In fact, it is the opposite. agystack helps you write less code, verify every change against real runtime evidence, and scale parallel work without multiplying slop.

Fork it. Improve it. Make it yours. PRs are welcome!

install (Antigravity)

this repository is agystack, the agentic engineering framework for Google Antigravity created by Joel Taroreh, built on Lauren Tan's pstack.

prerequisites

  • bun (v1.0+) is mandatory for PR babysitting (watch-pr) and multi-agent orchestration (orch). Node.js is not supported.
  • gh (GitHub CLI) is required for PR automation and preflight checks.
  • gt (Graphite CLI) is recommended for stacked PRs.

Install agystack globally (for all workspaces) or locally in your project:

Option A: Global install (recommended)

git clone https://github.com/jtaroreh/agystack.git ~/.gemini/config/plugins/agystack

Option B: Workspace-local install

git clone https://github.com/jtaroreh/agystack.git .agents/plugins/agystack

or honestly. you can probably just tell your chat

install this antigravity plugin for me: https://github.com/jtaroreh/agystack

Native Antigravity tools (invoke_subagent, run_command, manage_task, schedule, ask_question, and visual Artifacts) are documented in skills/poteto-mode/references/antigravity-tools.md.

Restart Antigravity or open a new chat after install.

get started

two steps:

  1. run /setup-agystack and choose which models you want, choose if you want to setup cloud swarm with Google Cloud auth.
  2. use /agystack or /poteto-mode whenever you're doing anything that requires rigor.

new here? the agystack guide walks you through a first real task, from setup and prompting through verification and overnight runs.

that's it. the other skills are situational; the mode skill uses them for you as needed. out of the box on Antigravity the mode splits work by model tier: fast mechanical code and exploration runs on flash, while judgment, complex tasks, and deep code run on pro. the default review panel is pro / flash / inherit. /setup-agystack changes any of it.

usage

use /agystack or /poteto-mode at the start of a task. it reads your request, picks from a set of playbooks, and runs the other skills as the steps need them.

just use /agystack or /poteto-mode

this skill is the main shortcut. i use it whenever i need the agent to do rigorous engineering work. it comes with twenty-three playbooks:

/poteto-mode this pr has a subtle bug where the scroll drifts every 750ms even when idle. repro
first, then fix and verify.
/poteto-mode i'm going to bed. land the stack even if ci flakes. i want everything merged by
morning.
playbookfor
investigationa read-only question. how does x work, why was y built this way, are we sure.
bug fixreproduce a defect, root-cause it, and fix with runtime evidence.
perftrace a measured slowness and improve it against a baseline.
hillclimbsustained, scientific improvement of one metric against a target, looping hypotheses with before/after measurement and one commit per accepted win.
runtime forensicsdiagnose a live symptom (leak, idle-cpu spin, glitch) from instrumentation.
trace forensicsdiagnose a captured profiling artifact (cpuprofile, trace, spindump, heap snapshot).
featurenew or changed behavior, built from a named data shape.
refactoringa behavior-preserving change to structure or shape.
prototypea throwaway sketch to make a design or behavioral decision cheaply, or to settle an empirical fork by observing it.
visual paritypixel-exact ui equivalence between two implementations.
authoring a skillwriting or editing a SKILL.md.
evaltest how a skill or prompt change affects agent behavior, blinded.
babysitdrive a pr or a stack to merge-ready: conflicts, review threads, ci.
[shipping](./skills/poteto-mode/playbooks/shipping.

// HOW IT'S BUILT

KEY FILES

skills/reflect/SKILL.mdREADME.md

// REPO STATS

80 stars