AI Agent Workflow Planner Skill
Design reliable AI agent workflows with clear roles, tool use, safety rules, and human review points built in from the start.
AI Agent Workflow Planner Skill is a free, reviewed AI skill for agent systems & llm workflows. Design reliable AI agent workflows with clear roles, tool use, safety rules, and human review points built in from the start. It works with ChatGPT, Claude, Gemini and is ready to use out of the box.
- • This skill cannot test private tools, APIs, or production systems, and will not invent capabilities or behavior for them. Recommendations are based only on what the user provides — details, logs, documentation, or examples improve accuracy. It will not design fully unsupervised autonomous workflows for high-risk actions.
About this skill
Building AI agents is easy to start and hard to get right — vague roles, unlimited permissions, and missing failure handling are common causes of unreliable or unsafe automations. This skill turns a goal into a complete, implementation-ready agent workflow: defined agent roles, the minimum tools each step needs, memory and context requirements, explicit human approval points for high-risk actions, and clear failure handling. It's built for founders, developers, automation creators, and product teams who need agent systems that are both effective and safe to deploy.
What it does
- Breaks a goal into a step-by-step agent workflow
- Defines single-purpose agent roles instead of vague catch-all agents
- Plans minimum-necessary tool and API access for each step
- Specifies memory and context requirements
- Identifies decision points and required human approval steps
- Defines failure handling and fallback behavior
- Drafts implementation-ready agent system prompts
What is included
- Structured workflow for turning any goal into an agent plan
- Full agent design framework covering roles, tools, memory, and safety
- Practical pre-deployment safety checklist
- Ready-to-use templates for workflow plans, role definitions, and system prompts
- Three worked examples across support, research, and sales use cases
How to use it
1. Describe the goal you want an AI agent (or agents) to accomplish. 2. Share the context, tools, or APIs the agent needs to interact with. 3. Specify the risk level of the actions involved, if known. 4. Review the generated workflow plan, role definitions, and safety rules. 5. Use the draft system prompt and templates to implement the agent in your stack of choice.
Examples
I want an AI agent that handles incoming customer support tickets — answers simple questions and escalates complex ones.
A full workflow plan with a ticket classification step, a knowledge-base-grounded response step, mandatory human approval for refunds or account changes, escalation logic for complex tickets, and a ready-to-use agent system prompt.
Known limitations
- This skill cannot test private tools, APIs, or production systems, and will not invent capabilities or behavior for them. Recommendations are based only on what the user provides — details, logs, documentation, or examples improve accuracy. It will not design fully unsupervised autonomous workflows for high-risk actions.