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@umgbhalla/pi-gigaplan

v0.1.3

Published

Structured AI planning with cross-model critique — gigaplan as a pi extension

Readme

pi-gigaplan

Structured AI planning with cross-model critique — a native pi extension.

What it does

Gigaplan coordinates multiple AI agents through a rigorous planning loop:

  1. Clarify — Agent clarifies ambiguous intent
  2. Plan — Agent produces a concrete implementation plan
  3. CritiqueDifferent agent independently raises flags
  4. Evaluate — Decision engine scores flags → CONTINUE/SKIP/ESCALATE/ABORT
  5. Integrate — Planner addresses flags, revises plan (loops back to critique)
  6. Gate — Preflight checks before execution
  7. Execute — Agent implements the approved plan
  8. Review — Agent validates against success criteria

Each step runs as an autonomous subagent in a visible cmux terminal pane. You can watch agents work in real-time.

Install

pi install git:github.com/umgbhalla/pi-gigaplan

Usage

/gigaplan build a rate limiter for the API endpoints

This will:

  1. Ask for robustness level (light/standard/thorough) and auto-approve preference
  2. Initialize a .gigaplan/ directory with plan artifacts
  3. Enter gigaplan mode — orchestrating subagents through the full loop
  4. Pause at gate for your approval (unless auto-approve)
  5. Execute and review

Tools

| Tool | Description | |------|-------------| | gigaplan_step | Get subagent config for a step | | gigaplan_advance | Process output and advance state machine | | gigaplan_status | Show plan status | | gigaplan_override | Manual intervention (add-note, abort, force-proceed, skip) |

Artifacts

All state lives in .gigaplan/plans/<plan-name>/:

.gigaplan/plans/rate-limiter/
├── state.json           # Mutable plan state
├── faults.json          # Flag registry
├── plan_v1.md           # Versioned plan (markdown)
├── plan_v1.meta.json    # Plan metadata (criteria, assumptions)
├── critique_v1.json     # Critique flags
├── evaluation_v1.json   # Decision engine output
├── gate.json            # Gate preflight results
├── execution.json       # Execution output
└── review.json          # Review results

Configuration

Robustness levels control how strict the critique is:

| Level | Behavior | |-------|----------| | light | Pragmatic. Only flags real failures. | | standard | Balanced judgment. Significant risks flagged. | | thorough | Exhaustive. Edge cases, performance, production concerns. |