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.

MITAuto-check passed

Install Wgm

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill wgm -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills wgm --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/wgm .claude/skills/wgm && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
wgm
GitHub stars
47k
Used in
1 other repo
Token cost
~1.7k tokens
SKILL.md length
846 words
Files
1
Skills in repo
1,493
Repo updated
First seen
Licence
MIT

At a glance

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.

  • Works in 6 steps: Triage → Grill (align) → Plan → …
  • SKILL.md covers Overview, When to Use This Skill, How It Works and Examples, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Wgm is an agent skill from sickn33/agentic-awesome-skills. 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.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

Example prompts

  • “Use the wgm skill to turn a rough request into working software via a governed build loop: align first, plan, then iterate one task at a time with…”
  • “/wgm”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Triage
  2. Grill (align)
  3. Plan
  4. Preflight
  5. Loop (build)
  6. Ship / Handoff

What it can do on your machine

Read from SKILL.md and the folder at commit 680176d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Wgm loads about 1.7k tokens when it runs. Until then it costs about 47 tokens; SKILL.md has 846 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~47
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit 680176d, republished under its MIT licence (© sickn33). 846 words, ~1,718 tokens.

Download SKILL.mdSave it as .claude/skills/wgm/SKILL.md (or your agent's skills folder).
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

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.

Show full SKILL.md (319 more words)Show less
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 move faster — misalignment discovered after building is far more expensive.
  • Don't treat a high satisfaction score as sufficient on its own — a failing deterministic check always overrides it.

Limitations

  • wgm is a protocol, not a runtime: it has no daemon, scheduler, or bundled dashboard — it expects an existing agentskills.io-compatible host to load and execute it.
  • This skill does not replace environment-specific validation, testing, or expert review.
  • Full holdout-scenario judging and the docs-audit swarm add ceremony that a genuinely trivial task does not need — wgm's own Triage track exists specifically to right-size this, and the skill explicitly says not to use it for one-file edits or pure debugging.

Common Pitfalls

  • Problem: Treating wgm's "build" mode the same as a full-lifecycle request. Solution: /wgm build resumes an existing IMPLEMENTATION_PLAN.md; a bare request like "build the auth module" (more text after "build") is a full-lifecycle request, not build mode.
  • Problem: Letting the agent peek at holdout scenarios while implementing. Solution: Scenarios are read only during Validate/Review, never during Implement — that's the entire point of a holdout set.
  • @grill-me - the narrower alignment-interview primitive wgm's Grill phase is adapted from.
  • @skill-creator - useful for authoring/evaluating the skill itself; wgm ships its own eval fixture (evals/evals.json) using the same eval-driven-iteration discipline.

Additional Resources

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/wgm of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit 680176d

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Wgm compared with similar skills
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Wgm this skillsickn33/agentic-awesome-skills47k1 repos~1.7kAutomated safety check: PassMIT
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Building Identity Governance Lifecycle Processmukul975/Anthropic-Cybersecurity-Skills34k—~7.3kAutomated safety check: PassApache-2.0
Flowstudio Power Automate Governancegithub/awesome-copilot40k2 repos~3.6kAutomated safety check: PassMIT

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Questions about Wgm

What does Wgm do?

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. Wgm is an agent skill from sickn33/agentic-awesome-skills. 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.

How do I install Wgm in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill wgm -a claude-code`. Or copy the skill folder (skills/wgm in sickn33/agentic-awesome-skills) into .claude/skills/wgm in your project. Claude Code loads it when a task matches its description.

How do I install Wgm in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill wgm -a codex`. Or copy the skill folder (skills/wgm in sickn33/agentic-awesome-skills) into .agents/skills/wgm in your project. Codex loads it when a task matches its description.

Can I use Wgm in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill wgm -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/wgm, .gemini/skills/wgm, .github/skills/wgm and .opencode/skills/wgm in your project.

What does Wgm need to run?

SKILL.md names no scripts, command-line tools or credentials: Wgm is instructions for the agent only.

Does Wgm access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Wgm safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Wgm use?

Wgm is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Wgm use?

About 1.7k tokens (SKILL.md is roughly 6.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Wgm?

Skills that share tags, products or a category with Wgm: Agent Governance (github/awesome-copilot, 40k stars), Living Docs Governance (affaan-m/ECC, 276k stars), Governance (plugin87/ux-ui-agent-skills, 1.6k stars) and Building Identity Governance Lifecycle Process (mukul975/Anthropic-Cybersecurity-Skills, 34k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Wgm?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,379 GitHub stars. The repository holds 1,493 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.