본문으로 건너뛰기
cccskills
무료GitHub에 공개

agent-os-framework

Generate standardized .agent-os directory structure with product documentation, mission, tech-stack, roadmap, and decision records. Enables AI-native workflows.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(2)

  • SKILL.md13.7 KB
  • metadata.json944 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Agent OS Framework

Generate standardized .agent-os structure for AI-native repository workflows.

Quick Start

# Generate full .agent-os structure
/agent-os-framework

# Generate for existing project
/agent-os-framework --update

# Generate specific component
/agent-os-framework --component mission

When to Use

USE when:

  • Setting up new repository
  • Adding AI workflow support
  • Documenting product vision
  • Creating decision records

DON'T USE when:

  • Project has complete .agent-os
  • Non-product repositories (e.g., dotfiles)

Prerequisites

  • Repository initialized with git
  • Basic project understanding
  • Stakeholder input for mission

Overview

Creates complete .agent-os structure:

  1. product/ - Core product documentation
  2. specs/ - Feature specifications
  3. standards/ - Code style guidelines
  4. instructions/ - Workflow instructions

Directory Structure

.agent-os/
├── product/
│   ├── mission.md        # Product pitch, users, pain points
│   ├── tech-stack.md     # Technology choices
│   ├── roadmap.md        # Development phases
│   └── decisions.md      # Decision log
├── specs/
│   └── README.md         # Spec index
├── standards/
│   ├── code-style.md     # Coding guidelines
│   └── testing.md        # Testing guidelines
└── instructions/
    ├── create-spec.md    # How to create specs
    └── execute-tasks.md  # How to execute tasks

Core Templates

1. mission.md

# Mission: [Project Name]

> [One-line pitch describing the project's core purpose]

## Product Pitch

[2-3 paragraph description of what the product does, why it exists, and what problem it solves]

## Target Users

### Primary Users
- **[User Type 1]**: [Description and needs]
- **[User Type 2]**: [Description and needs]

### Secondary Users
- **[User Type 3]**: [Description and needs]

## Pain Points Addressed

### Before This Product
1. **[Pain Point 1]**: [Description of the problem]
2. **[Pain Point 2]**: [Description of the problem]
3. **[Pain Point 3]**: [Description of the problem]

### After This Product
1. **[Solution 1]**: [How this product solves the problem]
2. **[Solution 2]**: [How this product solves the problem]
3. **[Solution 3]**: [How this product solves the problem]

## Success Metrics

| Metric | Current | Target | Timeframe |
|--------|---------|--------|-----------|
| [Metric 1] | [Current value] | [Target value] | [When] |
| [Metric 2] | [Current value] | [Target value] | [When] |
| [Metric 3] | [Current value] | [Target value] | [When] |

## Differentiators

### What Makes This Unique
1. **[Differentiator 1]**: [Description]
2. **[Differentiator 2]**: [Description]
3. **[Differentiator 3]**: [Description]

### Competitive Landscape
- **[Competitor 1]**: [How we differ]
- **[Competitor 2]**: [How we differ]

## Non-Goals

Things explicitly out of scope:
- [Non-goal 1]
- [Non-goal 2]
- [Non-goal 3]

---

*Last Updated: [Date]*
*Version: 1.0.0*

2. tech-stack.md

# Tech Stack: [Project Name]

> Technical architecture and technology choices

## Overview

| Category | Technology | Version | Purpose |
|----------|-----------|---------|---------|
| Language | Python | 3.11+ | Primary development |
| Package Manager | UV | Latest | Fast dependency management |
| Testing | pytest | 7.4+ | Test framework |
| Visualization | Plotly | 5.15+ | Interactive charts |
| Data | Pandas | 2.0+ | Data processing |

## Core Technologies

### Python 3.11+
**Why**: Modern async support, performance improvements, type hints
**Usage**: All source code in `src/`

### UV Package Manager
**Why**: 10-100x faster than pip, reliable lockfiles
**Usage**: `uv venv`, `uv pip install`

### pytest
**Why**: Industry standard, excellent fixtures, plugins
**Usage**: All tests in `tests/`

### Plotly
**Why**: Interactive plots, HTML export, professional appearance
**Usage**: All visualizations must be interactive (no static matplotlib)

### Pandas
**Why**: Data manipulation, time series, CSV handling
**Usage**: Data loading and transformation

## Development Tools

| Tool | Purpose | Configuration |
|------|---------|---------------|
| ruff | Linting | pyproject.toml |
| black | Formatting | pyproject.toml |
| mypy | Type checking | pyproject.toml |
| pytest-cov | Coverage | pytest.ini |

## Infrastructure

### Version Control
- **Git**: Source control
- **GitHub**: Remote repository
- **Branch Strategy**: main → feature branches → PR

### CI/CD
- **GitHub Actions**: Automated testing
- **Coverage**: Minimum 80%

## Data Storage

| Type | Location | Format |
|------|----------|--------|
| Raw data | data/raw/ | CSV, JSON |
| Processed | data/processed/ | CSV, Parquet |
| Results | data/results/ | CSV, JSON |
| Reports | reports/ | HTML |

## External Dependencies

### APIs
- [API 1]: [Purpose]
- [API 2]: [Purpose]

### Services
- [Service 1]: [Purpose]
- [Service 2]: [Purpose]

## Decision Rationale

### Why Python?
- Strong ecosystem for data analysis
- Excellent library support (Pandas, NumPy, Plotly)
- Team expertise
- Integration with existing tools

### Why UV over pip?
- Significantly faster installation
- Reliable dependency resolution
- Lockfile support
- workspace-hub standard

### Why Plotly over Matplotlib?
- Interactive by default
- Better HTML export
- Modern API
- workspace-hub HTML reporting standard

---

*Last Updated: [Date]*
*Version: 1.0.0*

3. roadmap.md

# Roadmap: [Project Name]

> Development phases and milestones

## Vision

[Long-term vision for the product - where it will be in 1-2 years]

## Current Phase

**Phase [N]: [Phase Name]**
- Status: [In Progress / Planning / Complete]
- Target: [Date]
- Progress: [X]%

## Phase Overview

Phase 1: Foundation [████████████████████] 100% Phase 2: Core Features [████████████░░░░░░░░] 60% Phase 3: Enhancement [░░░░░░░░░░░░░░░░░░░░] 0% Phase 4: Scale [░░░░░░░░░░░░░░░░░░░░] 0% Phase 5: Optimization [░░░░░░░░░░░░░░░░░░░░] 0%


## Detailed Phases

### Phase 1: Foundation ✅
**Goal**: Establish project structure and basic functionality
**Duration**: 2 weeks

#### Deliverables
- [x] Project structure setup
- [x] Basic configuration
- [x] Core module implementation
- [x] Initial test coverage (80%+)
- [x] Documentation framework

#### Key Outcomes
- Working development environment
- Basic functionality operational
- CI/CD pipeline configured

---

### Phase 2: Core Features 🚧
**Goal**: Implement primary feature set
**Duration**: 4 weeks

#### Deliverables
- [x] Feature A implementation
- [x] Feature B implementation
- [ ] Feature C implementation
- [ ] Integration testing
- [ ] Documentation complete

#### Key Outcomes
- Primary use cases supported
- User-facing functionality complete
- Quality standards met

---

### Phase 3: Enhancement 📋
**Goal**: Add secondary features and improvements
**Duration**: 3 weeks

#### Deliverables
- [ ] Advanced Feature D
- [ ] Performance optimizations
- [ ] Additional integrations
- [ ] Extended test coverage
- [ ] User documentation

#### Key Outcomes
- Feature-complete product
- Performance targets met
- Full documentation

---

### Phase 4: Scale 📋
**Goal**: Prepare for production scale
**Duration**: 2 weeks

#### Deliverables
- [ ] Performance testing
- [ ] Load testing
- [ ] Security review
- [ ] Deployment automation
- [ ] Monitoring setup

#### Key Outcomes
- Production-ready
- Monitoring operational
- Runbook complete

---

### Phase 5: Optimization 📋
**Goal**: Continuous improvement
**Duration**: Ongoing

#### Deliverables
- [ ] User feedback integration
- [ ] Performance tuning
- [ ] Technical debt reduction
- [ ] Feature iteration

#### Key Outcomes
- Improved user satisfaction
- Better performance
- Reduced maintenance burden

## Milestones

| Milestone | Target Date | Status |
|-----------|------------|--------|
| MVP Complete | [Date] | ✅ |
| Beta Release | [Date] | 🚧 |
| Production Release | [Date] | 📋 |
| Feature Complete | [Date] | 📋 |

## Risks and Mitigations

| Risk | Probability | Impact | Mitigation |
|------|-------------|--------|------------|
| [Risk 1] | Medium | High | [Mitigation strategy] |
| [Risk 2] | Low | Medium | [Mitigation strategy] |
| [Risk 3] | High | Low | [Mitigation strategy] |

## Dependencies

### External
- [Dependency 1]: Required for [Feature]
- [Dependency 2]: Required for [Feature]

### Internal
- [Team/Resource 1]: [What's needed]
- [Team/Resource 2]: [What's needed]

---

*Last Updated: [Date]*
*Version: 1.0.0*

4. decisions.md

# Decision Log: [Project Name]

> Record of architectural and design decisions

## How to Use This Document

Document significant technical decisions using the format below. Include context, options considered, and rationale.

## Decision Template

```markdown
### DEC-XXX: [Decision Title]
**Date**: YYYY-MM-DD
**Status**: [Proposed | Accepted | Deprecated | Superseded]
**Deciders**: [Names or roles]

#### Context
[What is the issue or opportunity?]

#### Options Considered
1. **Option A**: [Description]
   - Pros: [Benefits]
   - Cons: [Drawbacks]

2. **Option B**: [Description]
   - Pros: [Benefits]
   - Cons: [Drawbacks]

#### Decision
[Which option was chosen and why]

#### Consequences
- Positive: [Good outcomes]
- Negative: [Trade-offs accepted]

#### Related
- [Links to related decisions, issues, docs]

Decisions

DEC-001: Package Manager Selection

Date: 2026-01-01 Status: Accepted Deciders: Engineering Team

Context

Need to select a Python package manager for dependency management across the project.

Options Considered

  1. pip + requirements.txt

    • Pros: Universal, simple
    • Cons: Slow, no lockfile
  2. poetry

    • Pros: Modern, lockfile support
    • Cons: Slower than UV
  3. UV

    • Pros: Very fast, lockfiles, drop-in pip replacement
    • Cons: Newer tool

Decision

Use UV as the primary package manager.

Consequences

  • Positive: 10-100x faster installations, reliable builds
  • Negative: Team needs to learn UV commands

DEC-002: Visualization Library

Date: 2026-01-01 Status: Accepted Deciders: Engineering Team

Context

Need to select visualization library for data analysis reports.

Options Considered

  1. Matplotlib

    • Pros: Widely used, flexible
    • Cons: Static images, complex API
  2. Plotly

    • Pros: Interactive, HTML export, modern
    • Cons: Larger bundle size
  3. Altair

    • Pros: Declarative, clean syntax
    • Cons: Less flexible than Plotly

Decision

Use Plotly for all visualizations.

Consequences

  • Positive: Interactive reports, better user experience
  • Negative: No static image export (design decision)
  • Note: Aligns with workspace-hub HTML reporting standards

DEC-003: Testing Framework

Date: 2026-01-01 Status: Accepted Deciders: Engineering Team

Context

Need to select testing framework for the project.

Options Considered

  1. unittest

    • Pros: Built-in, no dependencies
    • Cons: Verbose, limited features
  2. pytest

    • Pros: Fixtures, plugins, markers, excellent output
    • Cons: External dependency

Decision

Use pytest with pytest-cov for coverage.

Consequences

  • Positive: Better developer experience, powerful fixtures
  • Negative: Additional dependency (acceptable trade-off)

Pending Decisions

DEC-004: [Pending Decision Title]

Date: Pending Status: Proposed

[Description of pending decision]


Last Updated: [Date] Total Decisions: 3 Accepted, 1 Pending


## Usage Examples

### Example 1: New Project Setup

```bash
# Generate complete .agent-os
/agent-os-framework

# Creates:
# - .agent-os/product/mission.md
# - .agent-os/product/tech-stack.md
# - .agent-os/product/roadmap.md
# - .agent-os/product/decisions.md
# - .agent-os/specs/README.md
# - .agent-os/standards/code-style.md
# - .agent-os/instructions/create-spec.md

Example 2: Update Existing

# Add missing components
/agent-os-framework --update

# Only creates files that don't exist

Execution Checklist

Initial Setup:

  • Create .agent-os directory
  • Generate product/ documents
  • Generate specs/ structure
  • Generate standards/
  • Generate instructions/

Content Review:

  • Update mission with actual project details
  • Fill in tech-stack choices
  • Define roadmap phases
  • Document initial decisions

Best Practices

  1. Keep mission current - Review quarterly
  2. Document decisions promptly - When made, not later
  3. Update roadmap status - Weekly or bi-weekly
  4. Reference in CLAUDE.md - Link from root config

Related Skills

References


Version History

  • 1.0.0 (2026-01-14): Initial release - .agent-os framework with mission, tech-stack, roadmap, and decisions

리뷰

아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.

댓글

로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.

아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.

보내면 바로 공개됩니다. 이메일 주소나 전화번호 같은 개인 정보는 쓰지 마세요. URL은 2개까지입니다.

0 / 1,000자

이 양식은 reCAPTCHA로 보호되며 Google 개인정보처리방침 및 서비스 약관이 적용됩니다.

같은 저장소의 스킬

Use when you need to install the embedded robot agents into either .cursor/agents or .claude/agents, selecting the destination interactively and copying the embedded agent definitions from project assets. This should trigger for requests such as Install embedded agents; Bootstrap .cursor/agents; Bootstrap .claude/agents; Copy robot agents. Part of cursor-rules-java project

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

majiayu000/claude-skill-registry-data272026년 10월 20일 업데이트

Use when you need to generate an AGENTS.md file for a Java repository — covering project conventions, tech stack, file structure, commands, Git workflow, and contributor boundaries — through a modular, step-based interactive process that adapts to your specific project needs. This should trigger for requests such as Create AGENTS.md; Update AGENTS.md file; Add agent instructions. Part of cursor-rules-java project

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

majiayu000/claude-skill-registry-data272026년 10월 20일 업데이트

Expert legal research agent for finding and scraping expungement data state by state. Knows authoritative sources, URL patterns, Firecrawl configuration, and 2026 legal landscape. Activate on "find expungement data", "scrape state laws", "legal research", "court URLs", "statute sources", "Clean Slate laws", "automatic expungement research". NOT for interpreting laws (use national-expungement-expert), building UI, or legal advice.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

majiayu000/claude-skill-registry-data272026년 10월 20일 업데이트

Generated by Gremlin Forge Meta-Agent 🍆👾⚡

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

majiayu000/claude-skill-registry-data272026년 10월 20일 업데이트

Work autonomously without waiting for hand-holding — complete tasks end-to-end without asking for permission at every step.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

majiayu000/claude-skill-registry-data272026년 10월 20일 업데이트

abmahnung

무료

Entwurf einer BAG-konformen Abmahnung im Arbeitsrecht – konkrete Schilderung der Pflichtverletzung, klare Verhaltenserwartung, ausdrückliche Sanktionsandrohung. Use when AG eine verhaltensbedingte Sanktion vor einer Kündigung dokumentieren muss oder AN die Wirksamkeit einer empfangenen Abmahnung prüft.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

majiayu000/claude-skill-registry-data272026년 10월 20일 업데이트

majiayu000의 스킬 모두 보기

이 스킬의 문제 신고