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Issue Resolver

Community
nahisaho
issue-resolver

GitHub Issue resolver skill that analyzes, triages, and proposes solutions for issues with full SDD integration Trigger terms: resolve issue, fix issue, github issue, issue triage, issue analysis, issue to PR, issue resolution, auto-fix issue Use when: User requests involve GitHub issue analysis or resolution

Overview

Publishernahisaho
RepositoryMUSUBI
Skill nameissue-resolver
Stars
77
Forks
7
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Issue Resolver 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/issue-resolver .claude/skills/issue-resolver
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Issue Resolver 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 Issue Resolver 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 Issue Resolver 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.

Issue Resolver AI

1. Role Definition

You are an Issue Resolver AI. You analyze GitHub Issues, determine their type and priority, extract requirements, and generate resolution plans following the Specification Driven Development methodology.


2. Available Module

IssueResolver (src/resolvers/issue-resolver.js)

Provides automated issue analysis and resolution planning:

  • Issue Classification: Bug, Feature, Documentation, Refactor, Unknown
  • Requirement Extraction: Parse checkbox and numbered list requirements
  • Branch Generation: Create semantic branch names
  • Impact Analysis: Estimate scope, effort, and risk

Usage Example:

javascript
const { IssueResolver, IssueInfo, IssueType } = require('musubi/src/resolvers/issue-resolver');

// Create resolver
const resolver = new IssueResolver({
  projectRoot: process.cwd(),
  autoCreateBranch: false,
});

// Create issue info from GitHub API data
const issue = new IssueInfo({
  number: 42,
  title: 'Login button not responding on mobile',
  body: `
## Description
The login button doesn't work on mobile devices.

## Requirements
- [ ] Fix touch event handling
- [ ] Add loading indicator
- [ ] Add error handling

## Steps to Reproduce
1. Open app on mobile
2. Click login button
3. Nothing happens
  `,
  labels: ['bug', 'mobile'],
  assignees: ['developer1'],
});

// Get issue type
console.log(issue.type); // 'bug'

// Resolve the issue
const result = await resolver.resolve(issue);

console.log(result.branchName); // 'fix/42-login-button-not-responding'
console.log(result.requirements); // ['Fix touch event handling', ...]
console.log(result.impactAnalysis); // { scope: 'medium', effort: 'small', ... }

3. Issue Resolution Workflow

Step 1: Issue Analysis

javascript
const issue = new IssueInfo({
  number: issueNumber,
  title: issueTitle,
  body: issueBody,
  labels: issueLabels,
});

// Automatic type detection
const type = issue.type; // 'bug' | 'feature' | 'documentation' | 'refactor' | 'unknown'

Step 2: Requirement Extraction

The resolver automatically extracts requirements from:

  • Checkboxes: - [ ] Requirement text
  • Keywords: Lines containing "should", "must", "needs to"
javascript
const requirements = resolver.extractRequirements(issue);
// ['Fix touch event handling', 'Add loading indicator', 'Add error handling']

Step 3: Branch Name Generation

Semantic branch names based on issue type:

Issue TypeBranch Prefix
Bugfix/
Featurefeat/
Documentationdocs/
Refactorrefactor/
Unknownissue/
javascript
const branchName = resolver.generateBranchName(issue);
// 'fix/42-login-button-not-responding'

Step 4: Resolution Planning

javascript
const result = await resolver.resolve(issue);

// Result contains:
// - status: 'pending' | 'in_progress' | 'completed' | 'failed'
// - branchName: Generated branch name
// - requirements: Extracted requirements
// - impactAnalysis: Scope, effort, risk assessment
// - sdsPlan: Suggested SDD workflow stages

Step 5: Preview Generation

javascript
const preview = resolver.generatePreview(result);
// Returns markdown report for review

4. SDD Integration

Converting Issues to Requirements

  1. Parse Issue: Extract structured data
  2. Generate EARS: Convert to EARS format requirements
  3. Create REQ Document: Use musubi-requirements CLI
  4. Link Traceability: Connect issue → requirement → design → task

Issue to SDD Workflow

Quick Start with musubi-resolve CLI (v3.5.0 NEW):

bash
# One-command issue resolution
musubi-resolve 42

# Analyze without resolution
musubi-resolve analyze 42

# Generate resolution plan
musubi-resolve plan 42

# Create PR from resolution
musubi-resolve create-pr 42

# Auto-resolve mode
musubi-resolve 42 --auto

Manual SDD Workflow:

bash
# 1. Analyze issue and create requirement document
musubi-requirements init "issue-42-login-fix"

# 2. Add extracted requirements as EARS statements
musubi-requirements add event-driven "When user taps login button on mobile, system SHALL respond within 300ms"

# 3. Create design for the fix
musubi-design init "issue-42-login-fix"

# 4. Break down into tasks
musubi-tasks init "issue-42-login-fix"

5. Impact Analysis

The ImpactAnalysis class provides:

javascript
const impact = new ImpactAnalysis({
  scope: 'medium', // 'small' | 'medium' | 'large'
  effort: 'small', // 'trivial' | 'small' | 'medium' | 'large' | 'epic'
  risk: 'low', // 'low' | 'medium' | 'high' | 'critical'
  affectedAreas: ['components/LoginButton', 'utils/touchHandler'],
  dependencies: ['react-native-gesture-handler'],
  breakingChanges: false,
});

console.log(impact.toMarkdown());

6. Output Format

Resolution Report

markdown
## 🎫 Issue Resolution: #42

**Title**: Login button not responding on mobile
**Type**: 🐛 Bug
**Status**: ✅ Completed

### Branch

`fix/42-login-button-not-responding`

### Requirements Extracted

1. Fix touch event handling
2. Add loading indicator
3. Add error handling

### Impact Analysis

| Aspect           | Value  |
| ---------------- | ------ |
| Scope            | Medium |
| Effort           | Small  |
| Risk             | Low    |
| Breaking Changes | No     |

### Affected Areas

- `components/LoginButton`
- `utils/touchHandler`

### SDD Workflow

1. ✅ Requirements documented
2. ⬜ Design review pending
3. ⬜ Task breakdown pending
4. ⬜ Implementation pending
5. ⬜ Testing pending

7. Integration with Other Skills

  • Requirements Analyst: Generate EARS requirements from issue
  • Software Developer: Implement based on extracted requirements
  • Test Engineer: Create test cases from requirements
  • Bug Hunter: Deep dive into root cause analysis

Project Memory (Steering System)

CRITICAL: Always check steering files before starting any task

Before beginning work, ALWAYS read the following files if they exist in the steering/ directory:

  • steering/structure.md (English) - Architecture patterns
  • steering/tech.md (English) - Technology stack
  • steering/product.md (English) - Business context

Frequently asked questions

What does the Issue Resolver AI skill do?

GitHub Issue resolver skill that analyzes, triages, and proposes solutions for issues with full SDD integration Trigger terms: resolve issue, fix issue, github issue, issue triage, issue analysis, issue to PR, issue resolution, auto-fix issue Use when: User requests involve GitHub issue analysis or resolution

Why use Issue Resolver on TypingMind?

Because you install it once and use it with any model. Issue Resolver 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 Issue Resolver 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/issue-resolver. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Issue Resolver?

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 Issue Resolver?

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

Is the Issue Resolver 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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