Tool-Using Agent Designer

Design safe, effective tool-using AI agents with proper tool schemas, agent loop architecture, safety gates, and evaluation strategies for production LLM applications.

Gold

v1.0.00 activationsAI & Machine LearningTechnologyexpert

SupaScore

84.45

Research Quality (15%)

8.4

Prompt Engineering (25%)

8.6

Practical Utility (15%)

8.5

Completeness (10%)

8.4

User Satisfaction (20%)

8.3

Decision Usefulness (15%)

8.4

Best for

▸Design ReAct-pattern agents that safely invoke API tools like search, database queries, and file operations
▸Build function-calling workflows with proper parameter validation and error handling for production LLM apps
▸Architect multi-tool agent pipelines with human-in-the-loop approval gates for sensitive operations
▸Create Model Context Protocol (MCP) server integrations with structured tool schemas and sandboxing
▸Implement agent evaluation frameworks that test tool selection accuracy and parameter correctness

What you'll get

●Complete ReAct agent implementation with tool registry, parameter validation middleware, and iteration limits
●JSON Schema definitions for each tool with usage examples and safety constraints
●Agent evaluation suite testing tool selection accuracy across different reasoning scenarios

Not designed for ↓

×Training or fine-tuning language models themselves (focuses on agent architecture, not model training)
×Building traditional rule-based automation systems (this is about LLM-powered reasoning agents)
×Creating chatbots without tool-use capabilities (this is specifically for tool-using agents)

Expects

A clear description of the agent's intended tasks, available tools/APIs, safety requirements, and evaluation criteria for tool-use accuracy.

Returns

Complete agent architecture including tool schemas, ReAct loop implementation, safety validation layers, and testing frameworks with specific code patterns.

Evidence Policy

Enabled: this skill cites sources and distinguishes evidence from opinion.

ai-agentstool-usefunction-callingreact-patternmcpllmsafetyhuman-in-the-loopprompt-engineeringagent-architecturesandboxingjson-schema

Research Foundation: 7 sources (5 official docs, 1 academic, 1 paper)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v1.0.02/16/2026

Initial release

Prerequisites

Use these skills first for best results.

Prompt Engineering StrategistGold

Works well with

API Security HardenerGold LLM Evaluation Framework DesignerGold Prompt Chain ArchitectGold Structured Output DesignerPlatinum System Prompt ArchitectPlatinum

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Multi-Agent OrchestratorPlatinum Human-in-the-Loop Agent DesignerPlatinum AI Red Teaming SpecialistGold

Common Workflows

Safe Production Agent Pipeline

End-to-end workflow from initial prompt design through tool agent architecture to safety testing and evaluation for production deployment

Prompt Engineering Strategist→tool-using-agent-designer→LLM Evaluation Framework Designer→AI Red Teaming Specialist

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