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General coding48k · #4556

wgm

Transforms simple requests into working software, following a guided process. It helps ensure software is developed in an organized and correct manner.

What it does

It's a method for turning software ideas into working code. It starts by understanding exactly what you want, creates a detailed plan, and then builds the software step-by-step, testing each part.

When to use it

  • ✓When you have an idea for an app or feature but aren't sure how to start.
  • ✓When you need a clear plan and step-by-step execution for a software project.
  • ✓When it's important for the software to work exactly as intended and be rigorously tested.

Example of what to ask your AI

“Build a to-do list app with commands to add, list, and complete tasks.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/wgm/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/plugins/agentic-awesome-skills-claude/skills/wgm/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

First, it asks questions to understand your goal and how to know if it's successful. Then, it creates a detailed plan and builds the software in small pieces, testing each one before moving to the next.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill wgm

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/wgm/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

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.

Step 6: Ship / Handoff

Summarize what shipped and how to validate it, run a mandatory four-persona docs-audit pass (junior/senior/principal/PM perspectives, consolidated into one paper-trail report), and harvest any durable, cross-project lesson back into the shared skill's own ledger.

Examples

Example 1: Full lifecycle from a rough request

User: "Build a CLI todo app with add/list/complete commands, from scratch."

wgm states its Track (Standard), grills for the ~3-5 unknowns that actually matter, writes specs + IMPLEMENTATION_PLAN.md, scores Preflight readiness, then loops one task at a time — each task's own test/lint/build command must exit 0 before it's marked done — and finally ships with a docs-audit pass.

Example 2: Scoped planning only

User: "/wgm plan: add OAuth login to this existing Express API"

wgm writes the specs and plan, then hard-stops at the Plan-exit gate without starting the build loop — useful when a human wants to review the plan before any code is touched.

Best Practices

  • Do let the plan be the shared state — a fresh agent should be able to resume a build from IMPLEMENTATION_PLAN.md alone.
  • Do keep holdout scenarios genuinely hidden from the generating agent; that's what prevents a judged score from being gamed.
  • Do map every acceptance criterion to a runnable, deterministic check before calling anything done.
  • Don't skip the alignment interview on ambiguous, multi-week, or security/UX-critical work just to

…

FAQ

What does 'governed build loop' mean?

It means the software building process is controlled and follows clear rules, ensuring each step is validated before moving forward.

What are 'holdout scenarios'?

These are examples of how the software should work that the build system doesn't see during development. This ensures the final result is genuinely good, not just 'looks good'.

When should I NOT use this tool?

Don't use it for simple one-file edits, minor bug fixes, research, or when you already have complete, clear step-by-step instructions.

Details

Original description by the author

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.

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#4556
License
MIT
Updated
10/15/2026

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