AI agents and automation prompts are advanced instructions for building the prompts and logic that power autonomous workflows. On Prompt Dock they cover real engineering tasks: system prompts and personas, tool-use and function-calling instructions, multi-step reasoning chains, agent role definitions, guardrail and error-handling wording, and workflow automation blueprints. Every prompt is human-reviewed before it goes live, so the structure is reliable rather than brittle. Free and premium prompts are both available, and you can reveal any prompt and run it live in the Playground to see how the model behaves before you wire it into an agent, chatbot, or automation.
7 prompts
Paste your agent's messy run logs — tool calls, errors, weird outputs — and get back a structured failure analysis grouped by root cause, plus a ready-to-use eval set of test cases so you can verify the fix instead of hoping. Built for debugging flaky agents.
Describe your email categories and routing rules and get a classification prompt that sorts every inbound email with a confidence score, a fallback secondary category, verbatim signal phrases, a priority guess, and a human-review flag for anything ambiguous, threatening, or off-list.
Describe what your agent needs to do in plain English. Get a complete JSON function schema with name, model-readable description, typed parameters, enums, required fields, and usage notes for when to call it and when not to — pasteable into your agent config.
Describe your product, support scope, tone, and escalation rules. Get a production-ready system prompt for a support agent with persona, knowledge boundaries, escalation triggers, and a refusal policy baked in — pasteable straight into your agent config.
Describe a multi-step task you want an agent to automate. Get a structured workflow with per-step inputs, outputs, decision branches, failure handling, a verification step, and human checkpoints for irreversible actions — ready to implement in any agent framework.
Describe the fields you need from messy text and get an extraction prompt that returns clean, valid JSON every time — explicit schema, null strategy for missing fields, array handling, a defined error object, and a per-item confidence score. Works without native JSON mode.
Define what your agent must never do and how it handles manipulation, and get a complete guardrail policy to embed in any system prompt — hard stops, soft redirects, prompt-injection and roleplay resistance, three refusal templates, and a fallback meta-rule.
Prompt Dock's AI Agents & Automation category collects them, and every prompt is human-reviewed before it publishes. Reveal the full text, pick free or premium, and run it in the Playground to observe the model's behavior on real input before you build the prompt into an agent or automated workflow.
They cover system prompts and personas, tool-use and function-calling instructions, multi-step reasoning chains, agent role definitions, guardrails, and automation blueprints. Each prompt is scoped to an agent-building task and human-reviewed, so you start from robust, reviewed structure instead of debugging a fragile system prompt yourself.
Claude and GPT both power production agents; Claude is often chosen for careful tool use and long-context reasoning, GPT for broad ecosystem support. Agent prompts note a recommended model, and the Playground lets you run the same system prompt to compare behavior before committing to a model for your build.