Reasoning Strategies¶

Import: from selectools import AgentConfig Stability: beta

from selectools import Agent, AgentConfig, LocalProvider, tool

@tool(description="Look up a fact")
def lookup(topic: str) -> str:
    return f"Fact about {topic}: it is interesting."

agent = Agent(
    tools=[lookup],
    provider=LocalProvider(),
    config=AgentConfig(reasoning_strategy="react"),
)
result = agent.run("What is the capital of France?")
print(result.content)
print(result.reasoning)

Added in: v0.17.6 File: src/selectools/prompt.py, src/selectools/agent/config.py Exports: REASONING_STRATEGIES

Overview¶

Reasoning strategies inject structured instructions into the agent's system prompt, guiding the LLM to follow a specific reasoning pattern. Combined with result.reasoning, you get full visibility into the agent's thought process.

Quick Start¶

from selectools import Agent, AgentConfig

agent = Agent(
    tools=[...],
    config=AgentConfig(reasoning_strategy="react"),
)
result = agent.run("What's the weather in NYC and how should I dress?")
print(result.reasoning)  # Shows Thought → Action → Observation steps

Available Strategies¶

ReAct (Reason + Act)¶

config = AgentConfig(reasoning_strategy="react")

Follows the Thought → Action → Observation cycle from the ReAct paper. The agent explains its reasoning before each tool call and analyzes results before proceeding.

Best for: multi-step tool use where you want to see the agent's decision-making process.

Chain of Thought (CoT)¶

config = AgentConfig(reasoning_strategy="cot")

The agent writes out its complete chain of reasoning step by step before taking action. Breaks complex problems into smaller steps.

Best for: complex reasoning tasks, math, logic puzzles, multi-part questions.

Plan Then Act¶

config = AgentConfig(reasoning_strategy="plan_then_act")

The agent first creates a numbered plan of all steps needed, then executes each step in order. Revises the plan if a step fails.

Best for: multi-tool workflows where upfront planning improves execution.

API Reference¶

AgentConfig¶

REASONING_STRATEGIES¶

from selectools import REASONING_STRATEGIES

print(REASONING_STRATEGIES.keys())
# dict_keys(['react', 'cot', 'plan_then_act'])

A dict mapping strategy names to their instruction text. Useful for discovering available strategies or customizing prompts.

Custom PromptBuilder¶

You can also set the strategy directly on PromptBuilder:

from selectools import PromptBuilder

pb = PromptBuilder(reasoning_strategy="cot")
agent = Agent(tools=[...], prompt_builder=pb)

See Also¶

• Agent — main agent configuration
• Prompt — prompt builder internals

Related Examples¶