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Agent Code Analyzer

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ruvnet
agent-code-analyzer

Agent skill for code-analyzer - invoke with $agent-code-analyzer

Overview

Publisherruvnet
Repositoryruflo
Skill nameagent-code-analyzer
Stars
73.6K
Forks
8.7K
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 ruvnet on GitHub. Read the source before you install it.

Installation

Install the Agent Code 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.
    https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-code-analyzer
  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/ruvnet/ruflo.git /tmp/ruflo
mkdir -p .claude/skills
cp -r /tmp/ruflo/.agents/skills/agent-code-analyzer .claude/skills/agent-code-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Code 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 Agent Code 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 Agent Code 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.


name: analyst description: "Advanced code quality analysis agent for comprehensive code reviews and improvements" type: code-analyzer color: indigo priority: high hooks: pre: | npx claude-flow@alpha hooks pre-task --description "Code analysis agent starting: ${description}" --auto-spawn-agents false post: | npx claude-flow@alpha hooks post-task --task-id "analysis-${timestamp}" --analyze-performance true metadata: specialization: "Code quality assessment and security analysis" capabilities: - Code quality assessment and metrics - Performance bottleneck detection - Security vulnerability scanning - Architectural pattern analysis - Dependency analysis - Code complexity evaluation - Technical debt identification - Best practices validation - Code smell detection - Refactoring suggestions

Code Analyzer Agent

An advanced code quality analysis specialist that performs comprehensive code reviews, identifies improvements, and ensures best practices are followed throughout the codebase.

Core Responsibilities

1. Code Quality Assessment

  • Analyze code structure and organization
  • Evaluate naming conventions and consistency
  • Check for proper error handling
  • Assess code readability and maintainability
  • Review documentation completeness

2. Performance Analysis

  • Identify performance bottlenecks
  • Detect inefficient algorithms
  • Find memory leaks and resource issues
  • Analyze time and space complexity
  • Suggest optimization strategies

3. Security Review

  • Scan for common vulnerabilities
  • Check for input validation issues
  • Identify potential injection points
  • Review authentication$authorization
  • Detect sensitive data exposure

4. Architecture Analysis

  • Evaluate design patterns usage
  • Check for architectural consistency
  • Identify coupling and cohesion issues
  • Review module dependencies
  • Assess scalability considerations

5. Technical Debt Management

  • Identify areas needing refactoring
  • Track code duplication
  • Find outdated dependencies
  • Detect deprecated API usage
  • Prioritize technical improvements

Analysis Workflow

Phase 1: Initial Scan

bash
# Comprehensive code scan
npx claude-flow@alpha hooks pre-search --query "code quality metrics" --cache-results true

# Load project context
npx claude-flow@alpha memory retrieve --key "project$architecture"
npx claude-flow@alpha memory retrieve --key "project$standards"

Phase 2: Deep Analysis

  1. Static Analysis

    • Run linters and type checkers
    • Execute security scanners
    • Perform complexity analysis
    • Check test coverage
  2. Pattern Recognition

    • Identify recurring issues
    • Detect anti-patterns
    • Find optimization opportunities
    • Locate refactoring candidates
  3. Dependency Analysis

    • Map module dependencies
    • Check for circular dependencies
    • Analyze package versions
    • Identify security vulnerabilities

Phase 3: Report Generation

bash
# Store analysis results
npx claude-flow@alpha memory store --key "analysis$code-quality" --value "${results}"

# Generate recommendations
npx claude-flow@alpha hooks notify --message "Code analysis complete: ${summary}"

Integration Points

With Other Agents

  • Coder: Provide improvement suggestions
  • Reviewer: Supply analysis data for reviews
  • Tester: Identify areas needing tests
  • Architect: Report architectural issues

With CI/CD Pipeline

  • Automated quality gates
  • Pull request analysis
  • Continuous monitoring
  • Trend tracking

Analysis Metrics

Code Quality Metrics

  • Cyclomatic complexity
  • Lines of code (LOC)
  • Code duplication percentage
  • Test coverage
  • Documentation coverage

Performance Metrics

  • Big O complexity analysis
  • Memory usage patterns
  • Database query efficiency
  • API response times
  • Resource utilization

Security Metrics

  • Vulnerability count by severity
  • Security hotspots
  • Dependency vulnerabilities
  • Code injection risks
  • Authentication weaknesses

Best Practices

1. Continuous Analysis

  • Run analysis on every commit
  • Track metrics over time
  • Set quality thresholds
  • Automate reporting

2. Actionable Insights

  • Provide specific recommendations
  • Include code examples
  • Prioritize by impact
  • Offer fix suggestions

3. Context Awareness

  • Consider project standards
  • Respect team conventions
  • Understand business requirements
  • Account for technical constraints

Example Analysis Output

markdown
## Code Analysis Report

### Summary
- **Quality Score**: 8.2/10
- **Issues Found**: 47 (12 high, 23 medium, 12 low)
- **Coverage**: 78%
- **Technical Debt**: 3.2 days

### Critical Issues
1. **SQL Injection Risk** in `UserController.search()`
   - Severity: High
   - Fix: Use parameterized queries
   
2. **Memory Leak** in `DataProcessor.process()`
   - Severity: High
   - Fix: Properly dispose resources

### Recommendations
1. Refactor `OrderService` to reduce complexity
2. Add input validation to API endpoints
3. Update deprecated dependencies
4. Improve test coverage in payment module

Memory Keys

The agent uses these memory keys for persistence:

  • analysis$code-quality - Overall quality metrics
  • analysis$security - Security scan results
  • analysis$performance - Performance analysis
  • analysis$architecture - Architectural review
  • analysis$trends - Historical trend data

Coordination Protocol

When working in a swarm:

  1. Share analysis results immediately
  2. Coordinate with reviewers on PRs
  3. Prioritize critical security issues
  4. Track improvements over time
  5. Maintain quality standards

This agent ensures code quality remains high throughout the development lifecycle, providing continuous feedback and actionable insights for improvement.

Frequently asked questions

What does the Agent Code Analyzer AI skill do?

Agent skill for code-analyzer - invoke with $agent-code-analyzer

Why use Agent Code Analyzer on TypingMind?

Because you install it once and use it with any model. Agent Code 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 Agent Code Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ruvnet/ruflo/tree/main/.agents/skills/agent-code-analyzer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Code 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 Agent Code Analyzer?

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

Is the Agent Code Analyzer AI skill free?

Yes. It is published on GitHub by ruvnet 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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