agentic-react

name	agentic-react
description	ReAct (Reasoning + Acting) pattern for adaptive, exploratory tasks with unknown solution paths. Iteratively alternate between reasoning and tool actions.

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name: "agentic-react" description: "ReAct (Reasoning + Acting) pattern for adaptive, exploratory agentic tasks. Use when the solution path is unknown and emerges through iterative reasoning and tool use."

Agentic ReAct Pattern

[!TIP] TL;DR: Use this pattern when the solution path is NOT known upfront. The agent iteratively alternates between reasoning and tool actions until a stopping condition is met. Key Principle: "Best default for real-world tasks. Flexible exploration via tool use and step-by-step reasoning."

Pattern Overview

The ReAct pattern treats the next best action as not fully knowable in advance. The agent iteratively:

1. Reasons about the current state
2. Acts by calling tools or making decisions
3. Observes the results
4. Repeats until stopping condition is met

┌─────────────────────────────────────────┐
│           ITERATION LOOP                 │
│  ┌─────────┐    ┌─────────┐             │
│  │ Reason  │───▶│  Act    │             │
│  │ "What's │    │ Call    │             │
│  │ next?"  │    │ tool X  │             │
│  └────┬────┘    └────┬────┘             │
│       │               │                 │
│       │    ┌─────────┐│                 │
│       ◀───│ Observe │─┘                 │
│            │ Get     │                   │
│            │ result  │                   │
│            └─────────┘                   │
│                   │                       │
│         ┌─────────┴─────────┐            │
│         ▼                   ▼            │
│   [Stop? YES]          [Stop? NO]        │
│   → Done               → Next iteration  │
└─────────────────────────────────────────┘

Decision Gate

When to use: Apply this pattern when:

• Question 2b = YES: Task requires tool access or external information
• Question 3 = NO: Task structure is NOT articulable before execution (structure emerges during execution)
• Quality criteria are unclear or latency matters more than perfection

Critical Design Elements

1. Clear Stopping Conditions

Good Stopping	Bad Stopping
"Task completed" + validation passed	"Do a good job"
"N tool calls reached"	"Think harder"
"External API confirms state"	"Feel confident"

2. Tool Design Contracts

Each tool should have:

• Clear input specification
• Predictable output format
• Defined failure modes

From Anthropic's engineering guide: "Effective tool design is the foundation everything else sits on."

3. Progress Tracking

Track reasoning history to:

• Avoid revisiting resolved questions
• Detect excessive looping
• Provide audit trail

Failure Mode: Excessive Looping

Signal	What It Means	Suggested Fix
Too many steps	Agent is uncertain about progress	Add stopping conditions
Revisiting resolved questions	No progress tracking	Implement state tracking
Getting stuck on tool calls	Tool contracts unclear	Refine tool definitions

Escalation Fix for Looping

If ReAct loops excessively → 
  Task likely needs planning (agentic-planner), OR
  Better tool structure, OR
  Clearer stopping condition

ReAct vs. Planning

ReAct	Planning
Structure emerges during execution	Structure defined upfront
Flexible, adaptive	Rigid but organized
Late failure detection	Early dependency exposure
Good for exploration	Good for complex dependencies

AGEM Integration

Native Tools

• run_agem_cycle — Each iteration of the loop
• get_cohomology — Check for inconsistencies in reasoning
• detect_gaps — Find knowledge gaps causing looping
• spawn_agem_agent — Spawn specialized reasoner if stuck

MCP Server Usage

• advanced-reasoning — Meta-cognitive reasoning with confidence tracking
• verifier-graph — Build causal reasoning chains for audit
• hipai-montague — Track beliefs and calibrate when reasoning stalls

Workflow Template

1. Initialize: goal + stopping condition
2. LOOP:
   a. Reason: analyze current state
   b. Act: call tool or make decision
   c. Observe: get result
   d. Evaluate: check stopping condition
   e. If stopped → output result
   f. If not → check for loops → continue
3. On H¹ > 0 → spawn_agem_agent for alternative perspective

Quick-Start Template

## ReAct Task Definition

**Task**: [What needs to be done]
**Solution Path**: [UNKNOWN - key indicator for ReAct]
**Toolset**: [Available tools]

### Stopping Conditions:
1. [Condition 1]
2. [Condition 2]

### Max Iterations: [N - prevent runaway loops]

### Escalation Triggers:
- [Loop detected] → escalate to [agentic-planner]
- [Specialization needed] → escalate to [agentic-multiagent]
- [Quality critical] → add [agentic-reflection]

Combination Patterns

ReAct is often layered with other patterns:

Layer	Pattern	When
Foundation	ReAct	Always
+ Planning	agentic-planner	When structure becomes clear
+ Reflection	agentic-reflection	When quality matters
+ Multi-Agent	agentic-multiagent	When specialization needed

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See Also

• agentic-planner — Add planning layer when structure is articulable
• agentic-reflection — Add quality checks when output matters
• agentic-multiagent — Add specialists when needed