AI Agent Prompt & Tool Spec Builder
Designs a complete AI agent specification — system prompt, tool definitions, and decision boundaries — from a description of the task you want the agent to handle.
AI Agent Prompt & Tool Spec Builder is a free AI skill for agent systems & llm workflows. Designs a complete AI agent specification — system prompt, tool definitions, and decision boundaries — from a description of the task you want the agent to handle. It works with Claude, ChatGPT, Cursor and is ready to use out of the box.
About this skill
AI Agent Prompt & Tool Spec Builder takes a description of a task or workflow you want an AI agent to automate and produces the full specification needed to build it: a system prompt defining the agent's role and behavior, a list of tools/functions it needs with parameter definitions, and explicit decision boundaries (what it should do autonomously vs. what requires human approval). Built for developers and product teams building LLM-powered agents who need a clear spec before implementation, especially around where autonomy should stop.
What it does
Given a task description, the skill outputs a system prompt for the agent, a list of required tools with parameters and descriptions, and explicit decision boundaries separating autonomous actions from ones requiring human-in-the-loop approval.
What is included
- Full system prompt defining agent role and behavior
- Tool/function list with parameters and descriptions
- Explicit autonomous vs. human-approval decision boundaries
- Edge case and failure mode considerations
- Format compatible with common agent frameworks and function-calling APIs
How to use it
1. Download the SKILL.md file 2. Upload it to a new Claude conversation 3. Describe the task or workflow you want an AI agent to handle 4. Receive a complete agent specification ready for implementation
Examples
I want an agent that monitors customer support tickets, categorizes them, and auto-responds to simple FAQ-type tickets while escalating complex ones to a human.
AGENT SPEC: Support Ticket Triage Agent SYSTEM PROMPT: You are a support ticket triage assistant. For each incoming ticket, categorize it as FAQ, Bug Report, Billing, or Complex/Other. If the ticket is FAQ and matches a known answer in the knowledge base with high confidence, draft a response using that answer. If category is Bug Report, Billing, or Complex/Other, or confidence is low, escalate to a human agent with a summary and suggested category. Never auto-send a response without it passing the confidence threshold check. TOOLS: 1. search_knowledge_base(query: string) — searches FAQ knowledge base, returns matching articles with confidence scores 2. categorize_ticket(ticket_text: string) — returns category label 3. draft_response(ticket_id: string, answer_text: string) — creates a draft response for review 4. escalate_ticket(ticket_id: string, summary: string, suggested_category: string) — flags ticket for human agent with context DECISION BOUNDARIES: AUTONOMOUS: Categorizing tickets, searching knowledge base, drafting FAQ responses REQUIRES HUMAN APPROVAL: Sending any response to the customer (draft only, human sends), any ticket below confidence threshold, all Bug Report/Billing/Complex tickets EDGE CASES: If knowledge base search returns no results, escalate rather than guessing at an answer; if ticket language is ambiguous or emotionally charged, escalate regardless of category match.
FAQ
What is this skill for?
How do I install it?
Does it write the actual implementation code?
Why does it separate autonomous actions from ones requiring approval?
How is this different from just writing a system prompt myself?
Can I use this spec with any LLM provider?
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