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Skillv1.0.0

wgm

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.

by sickn33(0) 0 installs
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Imported from sickn33/agentic-awesome-skills (skills/wgm/SKILL.md). Install upstream with npx skills add sickn33/agentic-awesome-skills --skill wgm. Copyright stays with the author (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.

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.

Related Skills

  • @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

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml
targets:
  - https://api.opensmartroute.ai/api/v1/registry/sickn33-agentic-awesome-skills-wgm/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

sickn33-agentic-awesome-skills-wgm.ocm.jsonjson
{
  "ocm": "1",
  "id": "sickn33-agentic-awesome-skills-wgm",
  "kind": "skill",
  "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.",
  "publisher": "sickn33",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "general"
    ],
    "tags": [
      "skill-md",
      "build-loop",
      "spec-driven",
      "ralph-loop",
      "self-improving",
      "agentic-development",
      "methodology",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "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."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/sickn33/agentic-awesome-skills",
      "path": "skills/wgm/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/sickn33/agentic-awesome-skills/blob/HEAD/skills/wgm/SKILL.md",
      "key": "sickn33/agentic-awesome-skills/skills/wgm/SKILL.md"
    },
    "license": "MIT"
  },
  "instructions": "# wgm\n\n## Overview\n\nwgm (\"well, gosh... make\") is a portable build **methodology**, not a domain skill — a single\n`SKILL.md` protocol that any agentskills.io-compatible host loads to turn a rough request into\nworking software. It marries three ideas: a relentless alignment interview before any code is\nwritten, a Ralph-style loop (one task per iteration, a persistent plan as shared state, steered by\ndeterministic backpressure), and holdout-scenario LLM judging (scenarios the build never sees, so a\nhigh satisfaction score can't be gamed). It also runs its own internal docs-audit and\nself-improve",
  "cost": {
    "context_tokens": 1568
  }
}

Fetch it by URL: GET /api/v1/registry/sickn33-agentic-awesome-skills-wgm/manifest?version=1.0.0

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