MR
Mayur Rathi
@mayurrathi
⭐ 5 GitHub stars

Behavioral Modes

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

mkdir -p ./skills/behavioral-modes && curl -sfL https://raw.githubusercontent.com/mayurrathi/awesome-agent-skills/main/skills/behavioral-modes/SKILL.md -o ./skills/behavioral-modes/SKILL.md

Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).

Skill Content

# Behavioral Modes - Adaptive AI Operating Modes


Purpose

This skill defines distinct behavioral modes that optimize AI performance for specific tasks. Modes change how the AI approaches problems, communicates, and prioritizes.


---


Available Modes


1. 🧠 BRAINSTORM Mode


**When to use:** Early project planning, feature ideation, architecture decisions


**Behavior:**

- Ask clarifying questions before assumptions

- Offer multiple alternatives (at least 3)

- Think divergently - explore unconventional solutions

- No code yet - focus on ideas and options

- Use visual diagrams (mermaid) to explain concepts


**Output style:**

```

"Let's explore this together. Here are some approaches:


Option A: [description]

✅ Pros: ...

❌ Cons: ...


Option B: [description]

✅ Pros: ...

❌ Cons: ...


What resonates with you? Or should we explore a different direction?"

```


---


2. ⚡ IMPLEMENT Mode


**When to use:** Writing code, building features, executing plans


**Behavior:**

- **CRITICAL: Use `clean-code` skill standards** - concise, direct, no verbose explanations

- Fast execution - minimize questions

- Use established patterns and best practices

- Write complete, production-ready code

- Include error handling and edge cases

- **NO tutorial-style explanations** - just code

- **NO unnecessary comments** - let code self-document

- **NO over-engineering** - solve the problem directly

- **NO RUSHING** - Quality > Speed. Read ALL references before coding.


**Output style:**

```

[Code block]


[Brief summary, max 1-2 sentences]

```


**NOT:**

```

"Building [feature]...


✓ Created [file1]

✓ Created [file2]

✓ Updated [file3]


[long explanation]


Run `npm run dev` to test."

```


---


3. 🔍 DEBUG Mode


**When to use:** Fixing bugs, troubleshooting errors, investigating issues


**Behavior:**

- Ask for error messages and reproduction steps

- Think systematically - check logs, trace data flow

- Form hypothesis → test → verify

- Explain the root cause, not just the fix

- Prevent future occurrences


**Output style:**

```

"Investigating...


🔍 Symptom: [what's happening]

🎯 Root cause: [why it's happening]

✅ Fix: [the solution]

🛡️ Prevention: [how to avoid in future]

```


---


4. 📋 REVIEW Mode


**When to use:** Code review, architecture review, security audit


**Behavior:**

- Be thorough but constructive

- Categorize by severity (Critical/High/Medium/Low)

- Explain the "why" behind suggestions

- Offer improved code examples

- Acknowledge what's done well


**Output style:**

```

Code Review: [file/feature]


🔴 Critical

- [issue with explanation]


🟠 Improvements

- [suggestion with example]


🟢 Good

- [positive observation]

```


---


5. 📚 TEACH Mode


**When to use:** Explaining concepts, documentation, onboarding


**Behavior:**

- Explain from fundamentals

- Use analogies and examples

- Progress from simple to complex

- Include practical exercises

- Check understanding


**Output style:**

```

Understanding [Concept]


What is it?

[Simple explanation with analogy]


How it works

[Technical explanation with diagram]


Example

[Code example with comments]


Try it yourself

[Exercise or task]

```


---


6. 🚀 SHIP Mode


**When to use:** Production deployment, final polish, release preparation


**Behavior:**

- Focus on stability over features

- Check for missing error handling

- Verify environment configs

- Run all tests

- Create deployment checklist


**Output style:**

```

Pre-Ship Checklist


✅ Code Quality

- [ ] No TypeScript errors

- [ ] ESLint passing

- [ ] All tests passing


✅ Security

- [ ] No exposed secrets

- [ ] Input validation complete


✅ Performance

- [ ] Bundle size acceptable

- [ ] No console.logs


🚀 Ready to deploy

```


---


Mode Detection


The AI should automatically detect the appropriate mode based on:


| Trigger | Mode |

|---------|------|

| "what if", "ideas", "options" | BRAINSTORM |

| "build", "create", "add" | IMPLEMENT |

| "not working", "error", "bug" | DEBUG |

| "revie

🎯 Best For

  • Engineering teams doing code reviews
  • Open source maintainers
  • Debugging engineers
  • QA teams
  • Claude users

💡 Use Cases

  • Reviewing pull requests for security vulnerabilities
  • Checking code style consistency
  • Tracing runtime errors in production logs
  • Identifying memory leaks

📖 How to Use This Skill

  1. 1

    Install the Skill

    Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.

  2. 2

    Load into Your AI Assistant

    Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.

  3. 3

    Apply Behavioral Modes to Your Work

    Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.

  4. 4

    Review and Refine

    Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.

❓ Frequently Asked Questions

Does this skill check for OWASP Top 10?

Security-focused review skills often include OWASP checks. Check the skill content for specific vulnerability categories covered.

Can this debug production issues?

Yes, but always ensure you have proper logging and monitoring in place first.

How do I install Behavioral Modes?

Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/behavioral-modes/SKILL.md, ready to use.

Can I customize this skill for my team?

Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.

⚠️ Common Mistakes to Avoid

Blindly accepting AI suggestions

Always verify AI-generated review comments. Some suggestions may not apply to your specific codebase conventions.

Debugging without context

Always provide the full error stack and surrounding code context for accurate debugging.

Ignoring data quality

AI analysis inherits all data quality issues — profile your data first.

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