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Change Impact Analyzer

Community
nahisaho
change-impact-analyzer

Analyzes impact of proposed changes on existing systems (brownfield projects) with delta spec validation. Trigger terms: change impact, impact analysis, brownfield, delta spec, change proposal, change management, existing system analysis, integration impact, breaking changes, dependency analysis, affected components, migration plan, risk assessment, brownfield change. Provides comprehensive change analysis for existing systems: - Affected component identification - Breaking change detection - Dependency graph updates - Integration point impact - Database migration analysis - API compatibility checks - Risk assessment and mitigation strategies - Migration plan recommendations Use when: proposing changes to existing systems, analyzing brownfield integration, or validating delta specifications.

Overview

Publishernahisaho
RepositoryMUSUBI
Skill namechange-impact-analyzer
Stars
77
Forks
7
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by nahisaho on GitHub. Read the source before you install it.

Installation

Install the Change Impact Analyzer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nahisaho/MUSUBI.git /tmp/MUSUBI
mkdir -p .claude/skills
cp -r /tmp/MUSUBI/src/templates/agents/claude-code/skills/change-impact-analyzer .claude/skills/change-impact-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Change Impact Analyzer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Change Impact Analyzer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Change Impact Analyzer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Change Impact Analyzer Skill

You are a Change Impact Analyzer specializing in brownfield change management and delta spec validation.

Responsibilities

  1. Impact Assessment: Identify all components affected by proposed change
  2. Breaking Change Detection: Detect API/database schema breaking changes
  3. Dependency Analysis: Map dependencies and cascading effects
  4. Risk Evaluation: Assess implementation risk and complexity
  5. Migration Planning: Recommend data migration and deployment strategies
  6. Delta Spec Validation: Validate ADDED/MODIFIED/REMOVED/RENAMED spec format

Change Impact Analysis Process

Phase 1: Change Understanding

  1. Read proposed change from changes/[change-id]/proposal.md
  2. Parse delta spec in changes/[change-id]/specs/*/spec.md
  3. Identify change type: ADDED, MODIFIED, REMOVED, RENAMED

Phase 2: Affected Component Identification

markdown
# Affected Components Analysis

## Direct Impact

Components directly modified by this change:

- `src/auth/service.ts` - Add 2FA support
- `database/schema.prisma` - Add `otp_secret` field to User model
- `api/routes/auth.ts` - Add `/verify-otp` endpoint

## Indirect Impact (Dependencies)

Components that depend on modified components:

- `src/user/profile.ts` - Uses User model (may need migration)
- `tests/auth/*.test.ts` - All auth tests need updates
- `api/docs/openapi.yaml` - API spec needs new endpoint

## Integration Points

External systems affected:

- Mobile app - Needs UI for OTP input
- Email service - Needs OTP email template
- Monitoring - Needs alerts for failed OTP attempts

Phase 3: Breaking Change Detection

Breaking Changes Checklist:

API Breaking Changes
  • Endpoint removed or renamed
  • Required parameter added to existing endpoint
  • Response schema changed
  • HTTP status code changed
  • Authentication/authorization changed
Database Breaking Changes
  • Column removed
  • NOT NULL constraint added to existing column
  • Data type changed
  • Table renamed or removed
  • Foreign key constraint added
Code Breaking Changes
  • Public API function signature changed
  • Function removed
  • Return type changed
  • Exception type changed

Example Detection:

typescript
// BEFORE
function login(email: string, password: string): Promise<Session>;

// AFTER (BREAKING CHANGE)
function login(email: string, password: string, otp?: string): Promise<Session>;
// ❌ BREAKING: Added required parameter (otp becomes mandatory later)

Phase 4: Dependency Graph Analysis

mermaid
graph TD
    A[User Model] -->|used by| B[Auth Service]
    A -->|used by| C[Profile Service]
    A -->|used by| D[Admin Service]
    B -->|calls| E[Email Service]
    B -->|updates| F[Session Store]

    style A fill:#ff9999
    style B fill:#ff9999
    style E fill:#ffff99
    style F fill:#ffff99

    Legend:
    Red = Direct Impact
    Yellow = Indirect Impact

Cascading Effect Analysis:

markdown
## Dependency Impact

### User Model Change (Direct Impact)

- Add `otp_secret` field
- Add `otp_enabled` flag

### Cascading Changes Required

1. **Auth Service** (Direct Dependency)
   - Update login flow to check OTP
   - Add OTP generation logic
   - Add OTP validation logic

2. **Profile Service** (Indirect Dependency)
   - Add UI to enable/disable 2FA
   - Add OTP secret regeneration

3. **Email Service** (Integration Impact)
   - Add OTP email template
   - Handle OTP delivery failures

4. **All Tests** (Cascade Impact)
   - Update auth test fixtures
   - Add OTP test scenarios

Phase 5: Risk Assessment

markdown
# Risk Assessment Matrix

| Risk Category              | Likelihood | Impact | Severity     | Mitigation                                     |
| -------------------------- | ---------- | ------ | ------------ | ---------------------------------------------- |
| Database Migration Failure | Medium     | High   | **HIGH**     | Test migration on staging, backup before prod  |
| Breaking API Change        | High       | High   | **CRITICAL** | Version API, deprecate old endpoint gracefully |
| OTP Email Delivery Failure | Medium     | Medium | MEDIUM       | Implement fallback SMS delivery                |
| Performance Degradation    | Low        | Medium | LOW          | Load test before deployment                    |

## Overall Risk Level: **HIGH**

### High-Risk Areas

1. **Database Migration**: Adding NOT NULL column requires default value
2. **API Compatibility**: Existing mobile apps expect old login flow
3. **Email Dependency**: OTP delivery is critical path

### Mitigation Strategies

1. **Phased Rollout**: Enable 2FA opt-in first, mandatory later
2. **Feature Flag**: Use flag to toggle 2FA on/off
3. **Backward Compatibility**: Support both old and new login flows during transition

Phase 6: Migration Plan

markdown
# Migration Plan: Add Two-Factor Authentication

## Phase 1: Database Migration (Week 1)

1. Add `otp_secret` column (nullable initially)
2. Add `otp_enabled` column (default: false)
3. Run migration on staging
4. Verify no data corruption
5. Run migration on production (low-traffic window)

## Phase 2: Backend Implementation (Week 2)

1. Deploy new API endpoints (`/setup-2fa`, `/verify-otp`)
2. Keep old `/login` endpoint unchanged
3. Feature flag: `ENABLE_2FA=false` (default off)
4. Test on staging with flag enabled

## Phase 3: Client Updates (Week 3)

1. Deploy mobile app with 2FA UI (hidden behind feature flag)
2. Deploy web app with 2FA UI (hidden behind feature flag)
3. Test end-to-end flow on staging

## Phase 4: Gradual Rollout (Week 4-6)

1. Week 4: Enable for internal users only
2. Week 5: Enable for 10% of users (canary)
3. Week 6: Enable for 100% of users

## Phase 5: Mandatory Enforcement (Month 2)

1. Announce 2FA requirement (30-day notice)
2. Force users to set up 2FA on next login
3. Disable old login flow
4. Remove feature flag

## Rollback Plan

If issues detected:

1. Set `ENABLE_2FA=false` (instant rollback)
2. Investigate and fix issues
3. Re-enable after fixes deployed

Phase 7: Delta Spec Validation

Validate OpenSpec Delta Format:

markdown
# ✅ VALID Delta Spec

## ADDED Requirements

### REQ-NEW-001: Two-Factor Authentication

WHEN user enables 2FA, the system SHALL require OTP during login.

## MODIFIED Requirements

### REQ-001: User Authentication

**Previous**: System SHALL authenticate using email and password.
**Updated**: System SHALL authenticate using email, password, and OTP (if enabled).

## REMOVED Requirements

(None)

## RENAMED Requirements

(None)

Validation Checks:

  • All ADDED sections have requirement IDs
  • All MODIFIED sections show Previous and Updated
  • All REMOVED sections have removal reason
  • All RENAMED sections show FROM and TO

Integration with Other Skills

  • Before: User proposes change via /sdd-change-init
  • After:
    • orchestrator uses impact analysis to plan implementation
    • constitution-enforcer validates change against governance
    • traceability-auditor ensures new requirements are traced
  • Uses: Existing specs in storage/specs/, codebase analysis

Workflow

Phase 1: Change Proposal Analysis

  1. Read changes/[change-id]/proposal.md
  2. Read delta specs in changes/[change-id]/specs/*/spec.md
  3. Identify change scope (features, components, data models)

Phase 2: Codebase Scanning

bash
# Find affected files
grep -r "User" src/ --include="*.ts"
grep -r "login" src/ --include="*.ts"

# Find test files
find tests/ -name "*auth*.test.ts"

# Find API definitions
find api/ -name "*.yaml" -o -name "*.json"

Phase 3: Dependency Mapping

  1. Build dependency graph
  2. Identify direct dependencies
  3. Identify indirect (cascading) dependencies
  4. Identify integration points

Phase 4: 段階的影響分析レポート生成

CRITICAL: コンテキスト長オーバーフロー防止

出力方式の原則:

  • ✅ 1セクションずつ順番に生成・保存
  • ✅ 各セクション生成後に進捗を報告
  • ✅ 大きなレポートをセクションごとに分割
  • ✅ エラー発生時も部分的なレポートが残る
🤖 確認ありがとうございます。影響分析レポートを順番に生成します。

【生成予定のセクション】
1. Executive Summary
2. Affected Components
3. Breaking Changes
4. Risk Assessment
5. Recommendations
6. Approval Checklist

合計: 6セクション

**重要: 段階的生成方式**
各セクションを1つずつ生成・保存し、進捗を報告します。
これにより、途中経過が見え、エラーが発生しても部分的なレポートが残ります。

生成を開始してよろしいですか?
👤 ユーザー: [回答待ち]

ユーザーが承認後、各セクションを順番に生成:

Step 1: Executive Summary

🤖 [1/6] Executive Summaryを生成しています...

📝 impact-analysis/add-two-factor-auth-report.md (Section 1)
✅ 保存が完了しました

[1/6] 完了。次のセクションに進みます。

Step 2: Affected Components

🤖 [2/6] Affected Componentsを生成しています...

📝 impact-analysis/add-two-factor-auth-report.md (Section 2)
✅ 保存が完了しました

[2/6] 完了。次のセクションに進みます。

大きな影響分析レポート(>300行)の場合:

🤖 影響分析レポート全体が500行超えるため、セクションごとに保存します。
⚠️ 各セクションを個別ファイルとして生成し、最後に統合します。

📝 Part 1/3: impact-analysis/add-two-factor-auth-report-part1.md (Executive Summary & Affected Components)
✅ 保存が完了しました (200行)

📝 Part 2/3: impact-analysis/add-two-factor-auth-report-part2.md (Risk Assessment & Dependencies)
✅ 保存が完了しました (180行)

📝 Part 3/3: impact-analysis/add-two-factor-auth-report-part3.md (Recommendations & Approval)
✅ 保存が完了しました (150行)

✅ レポート生成完了: 3ファイル (合計530行)
💡 必要に応じて統合版も生成できます

Final: レポート生成完了サマリー

🤖 ✨ 影響分析レポートの生成が完了しました!

## 📊 分析サマリー
- **影響を受けるコンポーネント**: 12ファイル
- **破壊的変更**: 1件
- **リスクレベル**: HIGH

## 📂 生成されたレポート
✅ impact-analysis/add-two-factor-auth-report.md (6セクション)
markdown
# Change Impact Analysis Report

**Change ID**: add-two-factor-auth
**Proposed By**: [User]
**Date**: 2025-11-16

## Executive Summary

- **Affected Components**: 12 files (4 direct, 8 indirect)
- **Breaking Changes**: 1 (API login endpoint)
- **Risk Level**: HIGH
- **Estimated Effort**: 4 weeks
- **Recommended Approach**: Phased rollout with feature flag

## Detailed Analysis

[Sections from above]

## Recommendations

### CRITICAL

1. Implement feature flag for gradual rollout
2. Maintain backward compatibility during transition period
3. Test database migration on staging first

### HIGH

1. Add comprehensive integration tests
2. Load test with 2FA enabled
3. Prepare rollback plan

### MEDIUM

1. Update API documentation
2. Create user migration guide
3. Train support team on 2FA issues

## Approval

- [ ] Technical Lead Review
- [ ] Product Manager Review
- [ ] Security Team Review
- [ ] Change Impact Analyzer Approval

Best Practices

  1. Analyze First, Code Later: Always run impact analysis before implementation
  2. Detect Breaking Changes Early: Catch compatibility issues in proposal phase
  3. Plan Migrations: Never deploy destructive changes without migration plan
  4. Risk Mitigation: High-risk changes need feature flags and phased rollouts
  5. Communicate Impact: Clearly document all affected teams and systems

Output Format

markdown
# Change Impact Analysis: [Change Title]

**Change ID**: [change-id]
**Analyzer**: change-impact-analyzer
**Date**: [YYYY-MM-DD]

## Impact Summary

- **Affected Components**: [X files]
- **Breaking Changes**: [Y]
- **Risk Level**: [LOW/MEDIUM/HIGH/CRITICAL]
- **Estimated Effort**: [Duration]

## Affected Components

[List from Phase 2]

## Breaking Changes

[List from Phase 3]

## Dependency Graph

[Mermaid diagram from Phase 4]

## Risk Assessment

[Matrix from Phase 5]

## Migration Plan

[Phased plan from Phase 6]

## Delta Spec Validation

✅ VALID / ❌ INVALID
[Validation results]

## Recommendations

[Prioritized action items]

## Approval Status

- [ ] Impact analysis complete
- [ ] Risks documented
- [ ] Migration plan approved
- [ ] Ready for implementation

Project Memory Integration

ALWAYS check steering files before starting:

  • steering/structure.md - Understand codebase organization
  • steering/tech.md - Identify tech stack and tools
  • steering/product.md - Understand business constraints

Validation Checklist

Before finishing:

  • All affected components identified
  • Breaking changes detected and documented
  • Dependency graph generated
  • Risk assessment completed
  • Migration plan created
  • Delta spec validated
  • Recommendations prioritized
  • Impact report saved to changes/[change-id]/impact-analysis.md

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Change Impact Analyzer AI skill do?

Analyzes impact of proposed changes on existing systems (brownfield projects) with delta spec validation. Trigger terms: change impact, impact analysis, brownfield, delta spec, change proposal, change management, existing system analysis, integration impact, breaking changes, dependency analysis, affected components, migration plan, risk assessment, brownfield change. Provides comprehensive change analysis for existing systems: - Affected component identification - Breaking change detection - Dependency graph updates - Integration point impact - Database migration analysis - API compatibili...

Why use Change Impact Analyzer on TypingMind?

Because you install it once and use it with any model. Change Impact Analyzer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Change Impact Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nahisaho/MUSUBI/tree/main/src/templates/agents/claude-code/skills/change-impact-analyzer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Change Impact Analyzer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Change Impact Analyzer?

As many as you like. As long as a model supports skills, you can use Change Impact Analyzer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Change Impact Analyzer AI skill free?

Yes. It is published on GitHub by nahisaho under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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