本文へ移動
cccskills
無料GitHub で公開

create-architectural-decision-record

Create an Architectural Decision Record (ADR) document for AI-optimized decision documentation.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md3.0 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Create Architectural Decision Record

Create an ADR document for ${input:DecisionTitle} using structured formatting optimized for AI consumption and human readability.

Inputs

  • Context: ${input:Context}
  • Decision: ${input:Decision}
  • Alternatives: ${input:Alternatives}
  • Stakeholders: ${input:Stakeholders}

Input Validation

If any of the required inputs are not provided or cannot be determined from the conversation history, ask the user to provide the missing information before proceeding with ADR generation.

Requirements

  • Use precise, unambiguous language
  • Follow standardized ADR format with front matter
  • Include both positive and negative consequences
  • Document alternatives with rejection rationale
  • Structure for machine parsing and human reference
  • Use coded bullet points (3-4 letter codes + 3-digit numbers) for multi-item sections

The ADR must be saved in the /docs/adr/ directory using the naming convention: adr-NNNN-[title-slug].md, where NNNN is the next sequential 4-digit number (e.g., adr-0001-database-selection.md).

Required Documentation Structure

The documentation file must follow the template below, ensuring that all sections are filled out appropriately. The front matter for the markdown should be structured correctly as per the example following:

---
title: "ADR-NNNN: [Decision Title]"
status: "Proposed"
date: "YYYY-MM-DD"
authors: "[Stakeholder Names/Roles]"
tags: ["architecture", "decision"]
supersedes: ""
superseded_by: ""
---

# ADR-NNNN: [Decision Title]

## Status

**Proposed** | Accepted | Rejected | Superseded | Deprecated

## Context

[Problem statement, technical constraints, business requirements, and environmental factors requiring this decision.]

## Decision

[Chosen solution with clear rationale for selection.]

## Consequences

### Positive

- **POS-001**: [Beneficial outcomes and advantages]
- **POS-002**: [Performance, maintainability, scalability improvements]
- **POS-003**: [Alignment with architectural principles]

### Negative

- **NEG-001**: [Trade-offs, limitations, drawbacks]
- **NEG-002**: [Technical debt or complexity introduced]
- **NEG-003**: [Risks and future challenges]

## Alternatives Considered

### [Alternative 1 Name]

- **ALT-001**: **Description**: [Brief technical description]
- **ALT-002**: **Rejection Reason**: [Why this option was not selected]

### [Alternative 2 Name]

- **ALT-003**: **Description**: [Brief technical description]
- **ALT-004**: **Rejection Reason**: [Why this option was not selected]

## Implementation Notes

- **IMP-001**: [Key implementation considerations]
- **IMP-002**: [Migration or rollout strategy if applicable]
- **IMP-003**: [Monitoring and success criteria]

## References

- **REF-001**: [Related ADRs]
- **REF-002**: [External documentation]
- **REF-003**: [Standards or frameworks referenced]

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.

日本語の概要は準備中です。原文の説明を表示しています。

github/awesome-copilot4万2026年10月9日 更新

github のスキルをすべて見る

このスキルの問題を報告する