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Integrated project management system covering documentation, language initialization, template optimization, docs generation, and JIT document loading. Absorbed from moai-workflow-templates, moai-docs-generation, and moai-workflow-jit-docs.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
AI text humanization and 윤문 (post-editing) specialist that detects and removes AI tells while preserving meaning, facts, and figures. Covers Korean, English, Japanese, and Chinese with a shared severity model (S1/S2/S3), quality grades (A/B/C/D), and 30%/50% over-editing guardrails. Use to make AI-generated text read as human-authored without changing what it says (de-ai, naturalness pass).
MoAI unified orchestrator for autonomous development. Routes natural language or subcommands (plan, run, sync, project, fix, loop, mx, feedback, review, clean, codemaps, gate, harness) to specialized agents.
Markdown-to-single-file-HTML report renderer. Six modes (status, incident, plan, explainer, financial, pr) selected automatically by report type. Zero external JS/CSS framework dependencies — inline SVG charts, single font-CDN exception for Korean readability. Self-contained output for email attachment, print, and offline viewing.
Unified thinking toolkit: Creative frameworks (Critical Evaluation, Diverge-Converge, Deep Questioning), First Principles reasoning (absorbed from moai-foundation-philosopher), and Adaptive Thinking via the `ultrathink` keyword. Use for ideation, strategic analysis, architecture decisions, and deep reasoning on complex problems.
Provides MoAI-ADK foundational principles including TRUST 5 quality framework, SPEC-First DDD methodology, delegation patterns, progressive disclosure, agent catalog reference, and token budget management (absorbed from moai-foundation-context). Use when referencing TRUST 5 gates, SPEC workflow, or context window optimization.
Provides MoAI-ADK foundational principles including TRUST 5 quality framework, SPEC-First DDD methodology, delegation patterns, progressive disclosure, agent catalog reference, and token budget management (absorbed from moai-foundation-context). Use when referencing TRUST 5 gates, SPEC workflow, or context window optimization.
| name | moai-workflow-project |
| description | Integrated project management system covering documentation, language initialization, template optimization, docs generation, and JIT document loading. Absorbed from moai-workflow-templates, moai-docs-generation, and moai-workflow-jit-docs. |
| when_to_use | Use for integrated project management: documentation scaffolding (product/structure/tech.md), multilingual language initialization, template and boilerplate optimization, docs generation (Sphinx, MkDocs, TypeDoc, OpenAPI), and JIT document loading. |
| license | Apache-2.0 |
| compatibility | Designed for Claude Code |
| allowed-tools | Read, Write, Edit, Bash(git:*), Bash(npm:*), Bash(npx:*), Bash(uv:*), Bash(pip:*), Bash(ls:*), Bash(mkdir:*), Grep, Glob, WebFetch, WebSearch, mcp__context7__resolve-library-id, mcp__context7__get-library-docs |
| user-invocable | false |
| metadata | {"version":"3.0.0","category":"workflow","status":"active","updated":"2026-04-25","modularized":"true","tags":"workflow, project, documentation, initialization, templates, boilerplate, scaffolding, jit-docs, docs-generation","aliases":"moai-workflow-project","related-skills":"moai-workflow-templates, moai-docs-generation, moai-workflow-jit-docs"} |
| progressive_disclosure | {"enabled":true,"level1_tokens":100,"level2_tokens":5000} |
Comprehensive project management system integrating documentation generation, multilingual support, and template optimization into a unified architecture with intelligent automation and Claude Code integration.
Scope: Consolidates documentation management, language initialization, and template optimization into a single cohesive system supporting complete project lifecycle from initialization to maintenance.
Target: Claude Code agents for project setup, documentation generation, multilingual support, and performance optimization.
Core Capabilities:
Key Features:
Supported Project Types: web applications, mobile applications, CLI tools, libraries, ML projects.
Three capability areas:
Three workflows: project initialization, documentation generation from SPEC, template performance optimization. Each follows a 3-step pattern (configure → execute → review results).
See core workflow walkthroughs for detailed step-by-step procedures.
Automatic Language Detection: analyzes file content, configuration files, system locale, and directory structure.
Multilingual Documentation: language-specific directories (e.g., docs/ko, docs/en), language negotiation, automatic redirection.
Agent Prompt Localization: language-specific instructions, cultural context, token cost optimization.
See language and localization detail for token cost analysis and locale configuration.
Performance Analysis: file size, complexity, performance bottlenecks, optimization opportunities, resource usage, backup recommendations.
Optimization Techniques: whitespace reduction, structure optimization, complexity reduction, performance caching.
Integrated configuration covers project metadata, language settings + costs, documentation status, template optimization results, module initialization states.
Language Settings: conversation_language (user-facing), agent_prompt_language (internal, often English for cost), documentation language (per language).
Updates trigger configuration file modifications, documentation structure updates, template localization.
See configuration schema and language fields for full field reference and supported language metadata.
For advanced patterns (custom templates, performance caching, batch processing, integration workflows), see references/reference.md and references/examples.md.
| Operation | Typical Duration |
|---|---|
| Complete documentation generation | 2-5 seconds |
| Language detection analysis | ~500 ms |
| Template optimization | 10-30 seconds |
| Configuration updates | ~100 ms |
Memory: base ~50MB, large projects +10-50MB, optimization cache 5-20MB.
File sizes: documentation 50-200KB per project, optimization backups match originals, configuration 5-10KB.
| Rationalization | Reality |
|---|---|
| "project docs are a one-time setup, no need to keep them current" | Stale product.md and tech.md mislead every SPEC written against them. They are living documents. |
| "structure.md will stay accurate since the codebase does not change much" | Every PR that adds a directory invalidates structure.md. Sync on every /moai project invocation. |
| "I know the tech stack, I do not need tech.md" | tech.md is not for you. It is for every agent that consults the project context before acting. |
| "codemaps take too long to generate" | codemaps are the only artifact that gives agents file-level awareness without reading every file. The cost pays for itself. |
| "I will write project docs after the feature is done" | Post-hoc docs capture what was built, not what was intended. Pre-feature docs guide the build. |
ls output of the project rootCode boilerplates, feedback templates, scaffolding, and project template optimization.
Analysis metrics: file size, complexity score, redundancy ratio, load performance.
Optimization techniques: whitespace reduction, deduplication, structure simplification.
Always create backup before applying optimization (backup: true).
Technical docs generation using Sphinx, MkDocs, TypeDoc, OpenAPI, and Nextra. Covers project configuration discovery, how to integrate with existing docs sites, and best practices for keeping framework documentation and technology guide content current.
| Generator | Use Case | Primary Format |
|---|---|---|
| Sphinx | Python projects, API docs | RST / Markdown |
| MkDocs | General projects | Markdown |
| TypeDoc | TypeScript libraries | TypeScript JSDoc |
| OpenAPI / Swagger | REST APIs | YAML / JSON |
| Nextra | Next.js docs sites | MDX |
.moai/config/sections/language.yaml/moai sync artifacts: README, CHANGELOG, API referenceJIT docs (just in time docs) — on-demand documentation discovery and loading based on user intent and conversation context.
mcp__context7__resolve-library-id, mcp__context7__get-library-docs): Official library docs.moai/, README, SPEC documents)Token budget: 5000 tokens per JIT load. Summarize if source exceeds budget.