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game-systems-designer

Use when designing the systems of a game from a locked concept — core loops, meta loops, player verbs, progression, content systems, level structure, and narrative integration. Triggers on "game design doc", "GDD", "system spec", "core loop design", "progression design", "level design", "MDA", or "design the systems". Produces a design doc plus per-system specs that game-balancer numbers, iap-manager stocks, and godot-engineer builds. Stops at design — no number tuning, pricing, or engine code. For balance numbers see game-balancer; for the engine implementation see godot-engineer.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

LazyIsEfficient/agentic-os
설치 방법 보기

포함된 파일(11)

  • SKILL.md4.7 KB
  • assets/design-doc-template.md4.4 KB
  • assets/level-spec-template.md1.8 KB
  • assets/system-spec-template.md2.6 KB
  • references/cohesion-checklist.md5.5 KB
  • references/content-and-levels.md5.7 KB
  • references/core-loops-and-progression.md5.7 KB
  • references/mda-framework.md4.3 KB
  • references/narrative-and-pacing.md6.0 KB
  • references/onboarding-and-failure.md6.7 KB
  • references/player-verbs.md4.6 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Game Systems Designer

Your job is to turn a locked concept one-pager into a design that downstream skills can build, balance, monetize, and ship. You produce: the design doc, per-system specs, loop diagrams, progression structure, and level/content framework. You do not pick numbers (game-balancer) or write engine code (godot-engineer).

If systems are locked and the team wants numbers tuned, stop and route to game-balancer.

Procedure

  1. Read the locked concept one-pager end-to-end (fantasy, aesthetics, player verbs, payment rails, comp titles).
  2. Apply MDA backwards — start from aesthetics → dynamics → mechanics. See references/mda-framework.md.
  3. Specify the core loop — see references/core-loops-and-progression.md. One core loop only.
  4. Specify meta loops — what carries between sessions; each must connect back to the core loop.
  5. Specify player verbs — for each verb (max 3): input, representation, feedback, failure mode, depth axis. See references/player-verbs.md.
  6. Specify content systems — type, volume per arc, variety source. See references/content-and-levels.md.
  7. Specify narrative integration — delivery method, minimum narrative needed. See references/narrative-and-pacing.md.
  8. Specify failure and onboarding — see references/onboarding-and-failure.md.
  9. Fill assets/design-doc-template.md — canonical design output.
  10. Fill assets/system-spec-template.md once per major system.
  11. Validate cohesion — see references/cohesion-checklist.md. Every system must answer "what does this make better in the rest of the game?"
  12. Hand off to game-balancer, iap-manager, godot-engineer.

Universal Rules

  • Aesthetics first, mechanics last
  • One core loop; two means one is meta
  • Three player verbs maximum
  • Every system must compound — a system that doesn't make another better should be cut
  • Failure is a system — design how it feels fair and what players take from it
  • Numbers are placeholders — use <TBD by game-balancer> for damage values, XP curves, drop rates
  • Pricing is not a system — no dollar values or store SKUs in the design doc
  • Stop at the spec — no engine code, shaders, or networking

Related Skills

  • game-balancer — tunes the numbers in the system specs
  • iap-manager — catalogs the SKUs the design implies
  • godot-engineer — builds the design in Godot 4 + C#
  • content-ops — expert-panel scoring of the design doc before committing to build

리뷰

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같은 저장소의 스킬

adversarial-claims-reviewer

무료

Use when adversarially reviewing a document that makes formal or technical claims — math derivations, physics papers, statistical analyses, benchmark reports, whitepapers. Inventories every equation and quantitative claim, verifies each AS NAMED in the text (never a paraphrase or a neighboring statement), and classifies VERIFIED / REFUTED / UNVERIFIABLE / VACUOUS. Triggers on "check this paper", "verify these claims", "is this derivation right", "review this proof", "audit this benchmark", "does the math hold up". For source-code review see code-review-and-quality; for skill/agent library audits see skill-library-review; for content quality scoring see content-ops.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

LazyIsEfficient/agentic-os172026년 7월 17일 업데이트

autoresearch

무료

Run Karpathy-style autoresearch optimization on any content. Generates 50+ variants, scores with a 5-expert simulated panel, evolves winners through multiple rounds, outputs optimized version + full experiment log. Use when optimizing landing pages, email sequences, ad copy, headlines, form pages, CTA text, or any conversion-focused content. Triggers on "optimize this page", "run autoresearch", "score these variants", "A/B test this copy".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

LazyIsEfficient/agentic-os172026년 7월 17일 업데이트

browser-testing-with-devtools

무료

Tests in real browsers. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data via Chrome DevTools MCP.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

LazyIsEfficient/agentic-os172026년 7월 17일 업데이트

code-review-and-quality

무료

Conducts multi-axis code review across correctness, readability, architecture, security, and performance. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Triggers on "review my PR", "review this diff", "code review", "review this changeset", "is this ready to merge", "pre-merge review".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

LazyIsEfficient/agentic-os172026년 7월 17일 업데이트

codebase-cost-estimator

무료

Estimate the full development cost of an existing codebase from lines of code, architectural complexity, and team-composition overhead. Use for 'how much would this cost to build', 'what did this codebase cost', development-cost or build-cost estimates, calendar-time estimates, and Claude/AI ROI on a delivered codebase. Estimates by measured LOC and complexity, not by ticket volume.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

LazyIsEfficient/agentic-os172026년 7월 17일 업데이트

content-ops

무료

Auto-assembles a domain-specific expert panel (7–10 experts), scores any content or strategy artifact against a typed rubric, and iterates until the aggregate hits 90+ (max 3 rounds). Use as a quality gate on copy, email sequences, landing-page drafts, strategy docs, charts, titles, or recruiting evaluations — or when another skill needs a final review gate on its output. Triggers on "expert panel this", "score this", "rate these variants", "quality check this", "panel review", "expert score", "evaluate this copy/strategy/page". For variant generation and multi-round conversion optimization see autoresearch; for live-URL CRO auditing see conversion-ops; for the scripted content-production pipeline see content-pipeline.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

LazyIsEfficient/agentic-os172026년 7월 17일 업데이트

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