ReAct Loop - Reason, Act, Observe

ReAct Loop implements the ReAct (Reason + Act) paradigm for solving complex problems through iterative exploration.

The core insight: Alternating between reasoning and action produces better results than either alone—reasoning guides which actions to take, and observations from actions inform better reasoning.

The Analogy: Detective Investigation

When to Use ReAct Loop

Perfect for:

• - 🔍 Research questions (gather info from multiple sources)
• 🐛 Debugging (hypothesize cause → test → observe)
• 📊 Data exploration (query → analyze → decide next query)
• 🌐 Web/API tasks (fetch data → process → fetch more)
• 🛠️ Tool-using workflows (sequence of tool calls needed)
• 🧩 Problems where you "don't know what you don't know"

Skip for:

• - ✅ Direct questions with known answers
• 📝 Single-step tasks ("write a summary")
• 🎯 Problems with clear predetermined steps

The ReAct Pattern

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The Workflow

Step 1: Initial Reasoning

Assess what you know and what you need:

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Step 2: Take Action

Execute the decided action:

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Step 3: Observe Results

Record what happened:

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Step 4: Iterate - Next Reasoning

Update understanding, decide next step:

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Step 5: Next Action

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Step 6: Next Observation

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Step 7: Continue Iterating...

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Step 8: Conclude

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ReAct Format

Standard format for tracking:

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Common Action Types

Information Gathering

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Execution

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Calculation/Processing

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Communication

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Best Practices

1. Thoughts Should Guide Actions

❌ Bad: Action without reasoning
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✅ Good: Reasoning explains why
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2. Be Specific in Actions

❌ Vague:
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✅ Specific:
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3. Record Full Observations

❌ Partial:
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✅ Complete:
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4. Update Understanding Each Iteration

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5. Know When to Stop

Stop when:

• - ✅ Question is answered
• ✅ Problem is solved
• ✅ Sufficient information gathered
• ❌ Not making progress (stuck in loop)
• ❌ Hitting iteration limits

If stuck: Try different angle, ask for help, or escalate.

Examples

Example 1: Research Task

Task: "What's the best approach for real-time notifications in a React app?"

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Example 2: Debugging

Task: "Fix failing CI build"

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Error: Cannot find module '../config/database'
Require stack:

• - /app/tests/setup.js

### Iteration 2

**Thought 2:**
Test setup can't find database config. This could be:
1. File was deleted/moved
2. Path changed in test
3. Config not generated in CI environment

Let me check if the file exists in repo.

**Action 2:**
Check: Does config/database.js exist in repository?

**Observation 2:**
File exists: config/database.js
But error shows it's looking for '../config/database' from tests/setup.js

Path resolution issue. Let me check directory structure.

### Iteration 3

**Thought 3:**
Path is '../config/database' from tests/setup.js.
This should resolve to config/database.js if tests/ is sibling to config/.

Let me check actual directory structure.

**Action 3:**
Run: find . -name "setup.js" -o -name "database.js" | head -20

**Observation 3:**

Ah! config is under src/, not at root. Path should be '../src/config/database'

### Iteration 4

**Thought 4:**
Path in test is wrong. But why did it work before?
Either:
1. File was moved recently
2. Test was changed
3. Working directory changed

Let me check git history.

**Action 4:**
Run: git log --oneline -10 -- tests/setup.js src/config/

**Observation 4:**

Example 3: Data Analysis

Task: "Why did conversion rate drop last week?"

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Integration with Other Skills

ReAct + Plan First:

• - Plan First: Create initial plan
• ReAct Loop: Execute each step with reasoning-observation cycles

ReAct + Self-Critique:

• - ReAct Loop: Execute and observe
• Self-Critique: Review if reasoning path is sound

ReAct + Team Code:

• - ReAct Loop: Manager uses to coordinate (reason → delegate → observe)
• Team Code: Multiple agents working in parallel

Anti-Patterns to Avoid

1. Actions Without Reasoning

❌ Bad:
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✅ Good:
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2. Ignoring Observations

❌ Bad:
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✅ Good:
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3. Getting Stuck in Loops

❌ Bad:
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✅ Good:
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4. Stopping Too Early

❌ Bad:
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✅ Good:
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Quick Start Template

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References

• - Research: "ReAct: Synergizing Reasoning and Acting in Language Models" (Yao et al., 2022)
• Related: Chain-of-Thought, ToolFormer, WebGPT
• See references/examples.md for detailed examples