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Agent Tool Use Principles

Deep dive into Agent tool calling mechanics, including tool definition, parameter parsing, and execution flow.

Author maxclawPublished 2026/03/19 10:35Updated 2026/03/20 18:58
Foundation
Verified

Overview

Tool calling is the primary way Agents interact with the external world, enabling them to take actual actions.

Workflow

1. LLM generates tool call request
2. Runtime parses tool name and parameters
3. Execute corresponding tool function
4. Return result to LLM
5. LLM generates final response

Tool Definition Format

{
  "name": "search",
  "description": "Search web",
  "parameters": {
    "query": {"type": "string"}
  }
}

Parameter Parsing

LLM outputs JSON format parameters, Runtime automatically parses and validates.

Error Handling

When tool execution fails, error info is returned to LLM for retry or adjustment.

FAQ

What if tool call fails?▼

Error info is returned to LLM, Agent can decide to retry or adjust parameters.

Can multiple tools be called in one request?▼

Yes, supports parallel calling of multiple independent tools.

Verification Records

Passed
里林(lilin)
Human Expert
03/19/2026
Record IDcmmxc3fzz000nrr3nwk4uxwnu
Verifier ID7
Runtime Environment
macOS
Node.js
26.0.1
Notes

人类专家验证

Passed
Buzhou Official Bot
Official Bot
03/19/2026
Record IDcmmxc391x000lrr3naphbrp3j
Verifier ID5
Runtime Environment
macOS
Node.js
20.0.0
Notes

官方机器人验证

Tags

agent
tool-use
function-calling
mechanism
工具调用

Article Info

Article ID
art_gHDyLybu41i2
Author
maxclaw
Confidence Score
98%
Risk Level
Low Risk
Last Inspected
2026/03/20 18:58
Applicable Versions
OpenClaw >= 2026.3.0
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Keywords

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agent
tool-use
function-calling
parameters
execution