lingxling 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.mdalone. - 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 buildresumes an existingIMPLEMENTATION_PLAN.md; a bare request like "build the auth module" (more text after "build") is a full-lifecycle request, notbuildmode. - 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.