We've prepared a comprehensive collection of production-ready Claude Code subagents: https://github.com/VoltAgent/awesome-claude-code-subagents

It contains 100+ specialized agents covering the most requested development tasks - frontend, backend, DevOps, AI/ML, code review, debugging, and more. All subagents follow best practices and are maintained by the open-source framework community.

Just copy to .claude/agents/ in your project to start using them.

Hi,
could someone explain how the /agents mode in Claude Code actually works? I’m wondering if it’s more of a coding sandbox step-by-step, or closer to autonomous agents handling tasks. What are your experiences with using this mode?

Manual for Writing Your First Claude Code Agents

The short manual:

Step 1: Just ask "I want to build 10 different agents for my code. Study the code and come up with ideas"

Step 2: Claude analyzes your project and suggests agents

Step 3: Ask for 5 more ideas to get even MORE options

Step 4: Pick the best ones and implement

The longer manual:

Instead of trying to think of agents yourself, just let Claude study your entire codebase and come up with ideas. It's like having a senior dev with ADHD hyperfocus on your project for 30 minutes straight.

The Magic Prompt That Started It All

I want to build 10 different agents for my code. Study the code and come up with ideas

That's it. That's the whole thing. No need to overcomplicate it with 47 paragraphs explaining your use case. Claude will:

• Actually read through your code (unlike your coworkers lol)

• Understand your architecture

• Suggest agents that make sense for YOUR specific project

• Give you practical implementation advice

• Come up with some terrible ideas. Avoid these.

Step-by-Step Walkthrough

1. Upload Your Code to Claude's Project Knowledge (web)

First, you gotta feed Claude your codebase. Upload your files to a Claude project so it can actually analyze what you're working with.

Pro tip: Don't just upload random files. Upload the core stuff:

• Main application files

• Key modules/classes

• Config files

• Any existing agent/service patterns

I prefer to do this in Terminal after starting Claude.

2. Drop The Magic Prompt

Just straight up ask:

Claude will go full detective mode on your codebase and come back with thoughtful suggestions.

3. Ask for MORE Ideas (This Is Key!)

After Claude gives you the first 10, immediately ask:

Why? Because the first batch is usually the "obvious" ones. The second batch often has the creative, outside-the-box ideas that end up being game-changers.

4. Name Your Agents Like a Boss

Each agent needs a memorable name. Here's how to do it right:

Bad: DataProcessingAgent Good: DataWranglerAgent or NumberCruncherAgent

Bad: MonitoringAgent Good: WatchdogAgent or SentinelAgent

The name should instantly tell you what it does AND be memorable enough that you don't forget about it in 2 weeks.

Real Example: AI Detection System Agents

Here's what happened when I used this method on an AI detection system. Claude analyzed the code and suggested these absolute bangers:

The Original 10 Agents Claude Suggested:

1. SentinelAgent (Performance Monitoring)

• What it does: Watches your system like a hawk

• Why it's fire: Catches bottlenecks before they ruin your day

• Implementation: Hooks into existing logging, creates dashboards

2. FeedbackWizardAgent (Feedback Analysis)

• What it does: Makes sense of user feedback patterns

• Why it's fire: Turns angry user comments into actionable improvements

• Implementation: Enhances existing training analyzer

3. ImageWranglerAgent (Preprocessing)

• What it does: Gets images ready for analysis

• Why it's fire: Clean input = better output, always

• Implementation: Insert before analyzer pipeline

4. DriftDetectorAgent (Model Drift Detection)

• What it does: Spots when AI generation techniques evolve

• Why it's fire: Keeps you ahead of the curve

• Implementation: Works with code adapter for auto-updates

5. BatchMasterAgent (Batch Processing)

• What it does: Handles multiple images like a champ

• Why it's fire: Scales your system without breaking it

• Implementation: Background job processing

6. ExplainerAgent (Explainability)

• What it does: Tells users WHY something was detected as AI

• Why it's fire: Trust = more users = more money

• Implementation: Enhances LLM analyzer

7. GuardianAgent (Security & Validation)

• What it does: Keeps malicious content out

• Why it's fire: Security breaches are expensive

• Implementation: Security layer before upload processing

8. LearnerAgent (Adaptive Learning)

• What it does: Learns new patterns automatically

• Why it's fire: Self-improving system = less manual work

• Implementation: Unsupervised learning on training system

9. ConnectorAgent (API Integration)

• What it does: Talks to external services

• Why it's fire: More data sources = better accuracy

• Implementation: External data in analysis pipeline

10. ReporterAgent (Analytics & Reporting)

• What it does: Makes pretty charts and insights

• Why it's fire: Management loves dashboards

• Implementation: Business intelligence on training database

Bonus Round: 5 More Ideas When I Asked

11. CacheManagerAgent

• What it does: Smart caching for repeated analyses

• Why it's sick: Speed boost + cost savings

12. A/B TestingAgent

• What it does: Tests different detection strategies

• Why it's sick: Data-driven improvements

13. NotificationAgent

• What it does: Alerts when important stuff happens

• Why it's sick: Stay informed without constant checking

14. BackupAgent

• What it does: Handles data backup and recovery

• Why it's sick: Sleep better at night

15. LoadBalancerAgent

• What it does: Distributes work across resources

• Why it's sick: Handle traffic spikes like a pro

Pro Tips That Will Save Your Sanity

Naming Convention Tips

• Use action words: Wrangler, Guardian, Sentinel, Master

• Make it memorable: If you can't remember the name, pick a better one

• Keep it short: 2-3 words max

• Avoid generic terms: "Handler" and "Manager" are boring

Implementation Priority Framework

Ask the 15 or so agent ideas to be classified by Claude. I use this formula

Make 3 tiers based on the 15 ideas like:

Tier 1 (Do First): Agents that solve immediate pain points
Tier 2 (Do Soon): Agents that add significant value
Tier 3 (Do Later): Nice-to-have features

Also I asked Claude Code to get these by just typing #tier1 #tier2 #tier3

Architecture Best Practices

• Follow your existing patterns (don't reinvent the wheel)

• Make agents modular (easy to add/remove)

• Use dependency injection (easier testing)

• Add monitoring from day 1

Common Pitfalls to Avoid

• Don't build everything at once - Start with 1-2 agents, the massive number of agents is better for almost finished code (well, you thought it was)

• Don't ignore existing code patterns - Claude suggests based on what you have

• Don't skip the naming step - Good names = better adoption

• Don't forget error handling - Agents fail, plan for it

Claude Reads Your ACTUAL Code

Unlike generic "build an agent" tutorials, Claude looks at:

• Your specific architecture patterns

• Existing services and modules

• Configuration and setup

• Pain points in your current system

Suggestions Are Contextual

The agents Claude suggests actually make sense for YOUR project, not some theoretical perfect codebase.

Implementation Guidance Included

Claude doesn't just say "build a monitoring agent" - it tells you exactly how to integrate it with your existing systems.

FAQ Section

Q: What if my codebase is trash? A: Claude will still give you agents that work with what you have. It's surprisingly good at working within constraints.

Q: How many agents should I actually build? A: Start with 2-3 that solve real problems. Don't go crazy on day 1.

Q: Can I use this for any programming language? A: Yeah, Claude reads most languages. Python, JavaScript, Go, whatever.

Q: What if I don't like Claude's suggestions? A: Ask for different ones! "Give me more creative ideas" where you define what you find creative. Often it helps to tell it what you find boring in the code. or "Focus on performance agents" works great.

Q: How do I know which agents to build first? A: Pick the ones that solve problems you're having RIGHT NOW. Future problems can wait. Use the tier 1 2 3 method.

Look, building agents is fun but don't get carried away. Start small, prove value, then expand.

Also, Claude's suggestions can be really good but they're not gospel. If something doesn't make sense for your use case, skip it. You know your code better than anyone.

Now you can create your own custom AI agent team.

For example, an agent for planning, one for coding, one for testing/reviewing etc.

Just type /agents to start.

Did anyone try it yet?