wgm

name	wgm
description	Turns a rough request into working software via a governed build loop: align first, plan, then iterate one task at a time with deterministic backpressure and holdout-scenario judging.
category	meta
risk	safe
source	community
source_repo	agent-frontier/wgm
source_type	official
date_added	2026-07-05
author	agent-frontier
tags	["build-loop","spec-driven","ralph-loop","self-improving","agentic-development","methodology"]
tools	["claude","cursor","gemini","copilot","codex"]
license	MIT
license_source	https://github.com/agent-frontier/wgm/blob/main/LICENSE

wgm

Overview

wgm ("well, gosh... make") is a portable build methodology, not a domain skill — a single SKILL.md protocol that any agentskills.io-compatible host loads to turn a rough request into working software. It marries three ideas: a relentless alignment interview before any code is written, a Ralph-style loop (one task per iteration, a persistent plan as shared state, steered by deterministic backpressure), and holdout-scenario LLM judging (scenarios the build never sees, so a high satisfaction score can't be gamed). It also runs its own internal docs-audit and self-improvement loop, cross-pollinating durable lessons from sibling agent-coding projects back into its own protocol.

When to Use This Skill

• Use when building or implementing a feature, app, or prototype from rough or ambiguous intent.
• Use when a task benefits from a governed plan plus iterative, test-validated execution rather than one-shot generation.
• Use when you want a build to converge against acceptance criteria an LLM judge scores blind (0-100), instead of trusting a single self-reported "looks good."
• Not for trivial one-file edits, pure debugging, research-only questions, or tasks that already have complete, unambiguous step-by-step instructions — wgm explicitly stays out of the way there.

How It Works

Step 1: Triage

Classify the work onto a scale-adaptive track (Quick / Standard / Full) so ceremony matches risk — a one-file fix skips holdout scenarios and the docs-audit swarm; a greenfield app gets the full rig. The deterministic backpressure gate itself is never skipped, only the ceremony around it.

Step 2: Grill (align)

Interview the user one question at a time, always with a recommended answer, until the goal, success criteria, and constraints are known — capping interrogation after ~5 questions to avoid theater. Explore the codebase to self-answer before asking anything a human doesn't need to weigh in on.

Step 3: Plan

Produce a project constitution, one spec per coherent slice (each with a magic moment and a demo path), holdout acceptance scenarios the build must never read, and IMPLEMENTATION_PLAN.md — the persistent shared state across every later iteration. Cross-check every artifact against every other one before moving on.

Step 4: Preflight

Score the plan's readiness 0-100 across goal clarity, observable success criteria, scenario coverage, and backpressure mapping. Below the threshold, return to Grill/Plan and fix the weakest dimension — do not start building on a shaky plan.

Step 5: Loop (build)

Run Analyze -> Implement -> Validate -> Review -> Record, one task per iteration: pick the single most important pending task, make the smallest change that completes it, run its deterministic validation command (green or it isn't done), judge holdout-scenario satisfaction, review the diff for scope creep, then record status and any durable lesson before advancing exactly one task.