Write or audit AI agent system prompts component-by-component across identity, instruction architecture, behavioral constraints, tools, examples, context strategy, output format, and error handling. Use when the user wants to design a new agent prompt, write a system prompt, review an existing agent prompt, fix tool-use instructions, audit prompt structure, improve context strategy, tune output formats, or define error handling for single-agent or multi-agent systems.
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100%
Does it follow best practices?
Impact
100%
1.33xAverage score across 3 eval scenarios
Passed
No known issues
Acme Subscriptions is launching an AI support agent for a SaaS billing product. The agent will answer customer questions, triage billing problems, look up account information, and escalate sensitive cases to humans.
The agent will run in a multi-turn chat interface using Claude. It has these tools:
customer_search(email: string) returns account status and plan metadata.invoice_lookup(customer_id: string, invoice_id?: string) returns invoice
details.refund_request(customer_id: string, amount_cents: number, reason: string)
creates a pending refund request for human approval.handoff_to_human(customer_id: string, reason: string, transcript_summary: string) transfers the conversation to support.Constraints:
Write a complete production system prompt for this agent. Include brief design notes explaining the prompt architecture decisions so the support engineering team can maintain it.