[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6FD7NRDX37AMQJZVS7NATTH":3,"skill-same:01M6FD7NRDX37AMQJZVS7NATTH":78},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":40,"linkOnly":41,"markdownContent":42,"markdownBody":43,"frontMatter":44,"refName":31,"commitSha":58,"skillDirectory":59,"forksCount":60,"repositoryHtmlUrl":61,"repositoryHomepageUrl":6,"ownerHtmlUrl":62,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":63,"install":64,"resources":77},"01M6FD7NRDX37AMQJZVS7NATTH","wgm",null,"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.","boisenoise\u002Fskills-collections","boisenoise","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F193180?v=4","01M6CDBDQK6BDN55ZMA6B6PKBM","01M6CDBDVSJ3JPTBYN26FZ7TZK",12,"MIT","https:\u002F\u002Fgithub.com\u002Fboisenoise\u002Fskills-collections\u002Fblob\u002Fmain\u002Fskills\u002Fantigravity-wgm\u002FSKILL.md",[],[5,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39],"self","2026","request","at","agentic-development","self-improving","spec-driven","build-loop","software","scenario","time","safe","align","main","community","ralph","plan","loop","Meta","official","copilot","agentic","2026-11-10 10:12:30",false,"---\nname: wgm\ndescription: \"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.\"\ncategory: meta\nrisk: safe\nsource: community\nsource_repo: agent-frontier\u002Fwgm\nsource_type: official\ndate_added: \"2026-07-05\"\nauthor: agent-frontier\ntags: [build-loop, spec-driven, ralph-loop, self-improving, agentic-development, methodology]\ntools: [claude, cursor, gemini, copilot, codex]\nlicense: \"MIT\"\nlicense_source: \"https:\u002F\u002Fgithub.com\u002Fagent-frontier\u002Fwgm\u002Fblob\u002Fmain\u002FLICENSE\"\n---\n\n# 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-improvement loop, cross-pollinating durable lessons from sibling agent-coding projects back\ninto its own protocol.\n\n## When to Use This Skill\n\n- Use when building or implementing a feature, app, or prototype from rough or ambiguous intent.\n- Use when a task benefits from a governed plan plus iterative, test-validated execution rather\n  than one-shot generation.\n- Use when you want a build to converge against acceptance criteria an LLM judge scores blind\n  (0-100), instead of trusting a single self-reported \"looks good.\"\n- Not for trivial one-file edits, pure debugging, research-only questions, or tasks that already\n  have complete, unambiguous step-by-step instructions — wgm explicitly stays out of the way there.\n\n## How It Works\n\n### Step 1: Triage\nClassify the work onto a scale-adaptive track (Quick \u002F Standard \u002F Full) so ceremony matches risk —\na one-file fix skips holdout scenarios and the docs-audit swarm; a greenfield app gets the full rig.\nThe deterministic backpressure gate itself is never skipped, only the ceremony around it.\n\n### Step 2: Grill (align)\nInterview the user one question at a time, always with a recommended answer, until the goal,\nsuccess criteria, and constraints are known — capping interrogation after ~5 questions to avoid\ntheater. Explore the codebase to self-answer before asking anything a human doesn't need to weigh\nin on.\n\n### Step 3: Plan\nProduce a project constitution, one spec per coherent slice (each with a magic moment and a demo\npath), holdout acceptance scenarios the build must never read, and `IMPLEMENTATION_PLAN.md` — the\npersistent shared state across every later iteration. Cross-check every artifact against every other\none before moving on.\n\n### Step 4: Preflight\nScore the plan's readiness 0-100 across goal clarity, observable success criteria, scenario\ncoverage, and backpressure mapping. Below the threshold, return to Grill\u002FPlan and fix the weakest\ndimension — do not start building on a shaky plan.\n\n### Step 5: Loop (build)\nRun `Analyze -> Implement -> Validate -> Review -> Record`, one task per iteration: pick the single\nmost important pending task, make the smallest change that completes it, run its deterministic\nvalidation command (green or it isn't done), judge holdout-scenario satisfaction, review the diff\nfor scope creep, then record status and any durable lesson before advancing exactly one task.\n\n### Step 6: Ship \u002F Handoff\n\nDelegation, external judging and durable shared-skill edits require current user\u002Frepository authorization; the protocol alone does not grant it. Keep holdout scenarios in an evaluator boundary the implementation process cannot read, and do not claim a genuinely blind holdout when the same model\u002Fsession has already seen them.\nSummarize what shipped and how to validate it, run a mandatory four-persona docs-audit pass\n(junior\u002Fsenior\u002Fprincipal\u002FPM perspectives, consolidated into one paper-trail report), and propose any durable cross-project lesson for an explicitly authorized ledger update.\n\n## Examples\n\n### Example 1: Full lifecycle from a rough request\n\n```\nUser: \"Build a CLI todo app with add\u002Flist\u002Fcomplete commands, from scratch.\"\n```\n\nwgm states its Track (Standard), grills for the ~3-5 unknowns that actually matter, writes specs +\n`IMPLEMENTATION_PLAN.md`, scores Preflight readiness, then loops one task at a time — each task's\nown test\u002Flint\u002Fbuild command must exit 0 before it's marked done — and finally ships with a\ndocs-audit pass.\n\n### Example 2: Scoped planning only\n\n```\nUser: \"\u002Fwgm plan: add OAuth login to this existing Express API\"\n```\n\nwgm writes the specs and plan, then hard-stops at the Plan-exit gate without starting the build loop\n— useful when a human wants to review the plan before any code is touched.\n\n## Best Practices\n\n- Do let the plan be the shared state — a fresh agent should be able to resume a build from\n  `IMPLEMENTATION_PLAN.md` alone.\n- Do keep holdout scenarios genuinely hidden from the generating agent; that's what prevents a\n  judged score from being gamed.\n- Do map every acceptance criterion to a runnable, deterministic check before calling anything done.\n- Don't skip the alignment interview on ambiguous, multi-week, or security\u002FUX-critical work just to\n  move faster — misalignment discovered after building is far more expensive.\n- Don't treat a high satisfaction score as sufficient on its own — a failing deterministic check\n  always overrides it.\n\n## Limitations\n\n- wgm is a protocol, not a runtime: it has no daemon, scheduler, or bundled dashboard — it expects\n  an existing agentskills.io-compatible host to load and execute it.\n- This skill does not replace environment-specific validation, testing, or expert review.\n- Full holdout-scenario judging and the docs-audit swarm add ceremony that a genuinely trivial task\n  does not need — wgm's own Triage track exists specifically to right-size this, and the skill\n  explicitly says not to use it for one-file edits or pure debugging.\n\n## Common Pitfalls\n\n- **Problem:** Treating wgm's \"build\" mode the same as a full-lifecycle request.\n  **Solution:** `\u002Fwgm build` resumes an *existing* `IMPLEMENTATION_PLAN.md`; a bare request like\n  \"build the auth module\" (more text after \"build\") is a full-lifecycle request, not `build` mode.\n- **Problem:** Letting the agent peek at holdout scenarios while implementing.\n  **Solution:** Scenarios are read only during Validate\u002FReview, never during Implement — that's the\n  entire point of a holdout set.\n\n## Related Skills\n\n- `@grill-me` - the narrower alignment-interview primitive wgm's Grill phase is adapted from.\n- `@skill-creator` - useful for authoring\u002Fevaluating the skill itself; wgm ships its own eval\n  fixture (`evals\u002Fevals.json`) using the same eval-driven-iteration discipline.\n\n## Additional Resources\n\n- [Repository](https:\u002F\u002Fgithub.com\u002Fagent-frontier\u002Fwgm)\n- [Full protocol (`SKILL.md`)](https:\u002F\u002Fgithub.com\u002Fagent-frontier\u002Fwgm\u002Fblob\u002Fmain\u002FSKILL.md)\n- [Reference library](https:\u002F\u002Fgithub.com\u002Fagent-frontier\u002Fwgm\u002Ftree\u002Fmain\u002Freferences)\n","# 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-improvement loop, cross-pollinating durable lessons from sibling agent-coding projects back\ninto its own protocol.\n\n## When to Use This Skill\n\n- Use when building or implementing a feature, app, or prototype from rough or ambiguous intent.\n- Use when a task benefits from a governed plan plus iterative, test-validated execution rather\n  than one-shot generation.\n- Use when you want a build to converge against acceptance criteria an LLM judge scores blind\n  (0-100), instead of trusting a single self-reported \"looks good.\"\n- Not for trivial one-file edits, pure debugging, research-only questions, or tasks that already\n  have complete, unambiguous step-by-step instructions — wgm explicitly stays out of the way there.\n\n## How It Works\n\n### Step 1: Triage\nClassify the work onto a scale-adaptive track (Quick \u002F Standard \u002F Full) so ceremony matches risk —\na one-file fix skips holdout scenarios and the docs-audit swarm; a greenfield app gets the full rig.\nThe deterministic backpressure gate itself is never skipped, only the ceremony around it.\n\n### Step 2: Grill (align)\nInterview the user one question at a time, always with a recommended answer, until the goal,\nsuccess criteria, and constraints are known — capping interrogation after ~5 questions to avoid\ntheater. Explore the codebase to self-answer before asking anything a human doesn't need to weigh\nin on.\n\n### Step 3: Plan\nProduce a project constitution, one spec per coherent slice (each with a magic moment and a demo\npath), holdout acceptance scenarios the build must never read, and `IMPLEMENTATION_PLAN.md` — the\npersistent shared state across every later iteration. Cross-check every artifact against every other\none before moving on.\n\n### Step 4: Preflight\nScore the plan's readiness 0-100 across goal clarity, observable success criteria, scenario\ncoverage, and backpressure mapping. Below the threshold, return to Grill\u002FPlan and fix the weakest\ndimension — do not start building on a shaky plan.\n\n### Step 5: Loop (build)\nRun `Analyze -> Implement -> Validate -> Review -> Record`, one task per iteration: pick the single\nmost important pending task, make the smallest change that completes it, run its deterministic\nvalidation command (green or it isn't done), judge holdout-scenario satisfaction, review the diff\nfor scope creep, then record status and any durable lesson before advancing exactly one task.\n\n### Step 6: Ship \u002F Handoff\n\nDelegation, external judging and durable shared-skill edits require current user\u002Frepository authorization; the protocol alone does not grant it. Keep holdout scenarios in an evaluator boundary the implementation process cannot read, and do not claim a genuinely blind holdout when the same model\u002Fsession has already seen them.\nSummarize what shipped and how to validate it, run a mandatory four-persona docs-audit pass\n(junior\u002Fsenior\u002Fprincipal\u002FPM perspectives, consolidated into one paper-trail report), and propose any durable cross-project lesson for an explicitly authorized ledger update.\n\n## Examples\n\n### Example 1: Full lifecycle from a rough request\n\n```\nUser: \"Build a CLI todo app with add\u002Flist\u002Fcomplete commands, from scratch.\"\n```\n\nwgm states its Track (Standard), grills for the ~3-5 unknowns that actually matter, writes specs +\n`IMPLEMENTATION_PLAN.md`, scores Preflight readiness, then loops one task at a time — each task's\nown test\u002Flint\u002Fbuild command must exit 0 before it's marked done — and finally ships with a\ndocs-audit pass.\n\n### Example 2: Scoped planning only\n\n```\nUser: \"\u002Fwgm plan: add OAuth login to this existing Express API\"\n```\n\nwgm writes the specs and plan, then hard-stops at the Plan-exit gate without starting the build loop\n— useful when a human wants to review the plan before any code is touched.\n\n## Best Practices\n\n- Do let the plan be the shared state — a fresh agent should be able to resume a build from\n  `IMPLEMENTATION_PLAN.md` alone.\n- Do keep holdout scenarios genuinely hidden from the generating agent; that's what prevents a\n  judged score from being gamed.\n- Do map every acceptance criterion to a runnable, deterministic check before calling anything done.\n- Don't skip the alignment interview on ambiguous, multi-week, or security\u002FUX-critical work just to\n  move faster — misalignment discovered after building is far more expensive.\n- Don't treat a high satisfaction score as sufficient on its own — a failing deterministic check\n  always overrides it.\n\n## Limitations\n\n- wgm is a protocol, not a runtime: it has no daemon, scheduler, or bundled dashboard — it expects\n  an existing agentskills.io-compatible host to load and execute it.\n- This skill does not replace environment-specific validation, testing, or expert review.\n- Full holdout-scenario judging and the docs-audit swarm add ceremony that a genuinely trivial task\n  does not need — wgm's own Triage track exists specifically to right-size this, and the skill\n  explicitly says not to use it for one-file edits or pure debugging.\n\n## Common Pitfalls\n\n- **Problem:** Treating wgm's \"build\" mode the same as a full-lifecycle request.\n  **Solution:** `\u002Fwgm build` resumes an *existing* `IMPLEMENTATION_PLAN.md`; a bare request like\n  \"build the auth module\" (more text after \"build\") is a full-lifecycle request, not `build` mode.\n- **Problem:** Letting the agent peek at holdout scenarios while implementing.\n  **Solution:** Scenarios are read only during Validate\u002FReview, never during Implement — that's the\n  entire point of a holdout set.\n\n## Related Skills\n\n- `@grill-me` - the narrower alignment-interview primitive wgm's Grill phase is adapted from.\n- `@skill-creator` - useful for authoring\u002Fevaluating the skill itself; wgm ships its own eval\n  fixture (`evals\u002Fevals.json`) using the same eval-driven-iteration discipline.\n\n## Additional Resources\n\n- [Repository](https:\u002F\u002Fgithub.com\u002Fagent-frontier\u002Fwgm)\n- [Full protocol (`SKILL.md`)](https:\u002F\u002Fgithub.com\u002Fagent-frontier\u002Fwgm\u002Fblob\u002Fmain\u002FSKILL.md)\n- [Reference library](https:\u002F\u002Fgithub.com\u002Fagent-frontier\u002Fwgm\u002Ftree\u002Fmain\u002Freferences)\n",{"name":5,"risk":29,"tags":45,"tools":48,"author":53,"source":32,"license":14,"category":54,"date_added":55,"description":7,"source_repo":56,"source_type":37,"license_source":57},[25,24,46,23,22,47],"ralph-loop","methodology",[49,50,51,38,52],"claude","cursor","gemini","codex","agent-frontier","meta","2026-07-05","agent-frontier\u002Fwgm","https:\u002F\u002Fgithub.com\u002Fagent-frontier\u002Fwgm\u002Fblob\u002Fmain\u002FLICENSE","7bf2279c8a65758319526a721d5c4b75683aec9c","skills\u002Fantigravity-wgm",3,"https:\u002F\u002Fgithub.com\u002Fboisenoise\u002Fskills-collections","https:\u002F\u002Fgithub.com\u002Fboisenoise","2026-11-10 14:20:15",{"source":8,"skillName":5,"commands":65,"prompt":75,"zipAvailable":76},[66,69,72],{"tool":67,"command":68},"npx","npx skills add boisenoise\u002Fskills-collections --skill wgm",{"tool":70,"command":71},"bunx","bunx skills add 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information.","https:\u002F\u002Fgithub.com\u002Fboisenoise\u002Fskills-collections\u002Fblob\u002Fmain\u002Fskills\u002Fantigravity-lead-signals\u002FLICENSE","https:\u002F\u002Fgithub.com\u002Fboisenoise\u002Fskills-collections\u002Fblob\u002Fmain\u002Fskills\u002Fantigravity-lead-signals\u002FSKILL.md",[],[211,212,213,122,37,123,214,215,151,216,217,102,218,219,220,221,222,223,224,134],"signals","lead","lead signals","how","find","ready","as","how to","qualify","people","information","enrich","changes","funding"]