Try it in ChatGPT
Paste a setup prompt into a chat. Start with files you choose to share and draft-only work. If your account offers reusable GPTs or skills, move the tested instructions there later.
Copy the ChatGPT setup prompt →The agent field guide
Make an AI agent useful. Keep yourself in control.
Start with one repeatable job, a clear finish line and the smallest access it needs. Copy a setup prompt, test on safe data, then expand only when the result earns your trust.
Start here
Choose the lightest setup that does the job.
A prompt describes behaviour. An agent also needs a way to receive work, use tools, keep the right context, check results and stop safely. Pasting instructions does not magically connect your email, schedule a run or give an AI permission to publish.
Set up Codex
Point Codex at one project and ask it to inspect existing instructions. Repeated workflows may suit a skill; a one-off task usually needs only a good brief.
Copy the Codex setup prompt →Design an API agent
Write the workflow and tests before connecting tools. An API-based agent needs software, hosting and a budget; this free library does not run a model for visitors.
Copy the build-spec prompt →- Pick one task and show two real examples of a good result.
- Write the input, output, allowed sources and definition of done.
- Start read-only or draft-only. Review its first outputs yourself.
- Test ordinary, missing-data and misleading-input cases.
- Add one tool or permission at a time; keep a stop rule and a way to undo changes.
The operating contract
Six things every dependable agent needs.
One job, one finish line
State the real result, intended user and measurable acceptance criteria. “Improve everything” is not a testable task.
Know what is true
Name approved sources and how to cite them. Ask the agent to separate observed facts, inference and missing information.
Limit its reach
Separate reading, drafting, reversible edits and external actions. Sending, publishing, purchasing and deleting need explicit authority.
Connect only what exists
Give the smallest real tool set. A prompt cannot grant access to a mailbox, browser, database or calendar by itself.
Recover from interruption
Record completed steps, sources, pending approvals and rollback points. Keep secrets out of notes and public prompts.
Know when to stop
Set step, time and cost limits; stop on uncertainty, failed checks or missing authority. Report the unfinished part honestly.
Use-case library
Start with a real task, not an agent persona.
Research & decisionsCompare evidence, uncertainty and options.
Customer supportClassify requests and draft grounded replies.
Marketing & contentPlan posts without silently publishing.
Website testingCheck a full journey with observable proof.
Documents & dataExtract fields and flag uncertain records.
MonitoringAlert on meaningful change, not noise.
Before you automate
Test the boundary as hard as the happy path.
Permissions first
Map exactly what the agent may read, draft or change. External communication, spending and destructive operations should have clear approval gates.
Build a permission map →Evaluate actual behaviour
Use realistic normal, edge and adversarial examples. Check tool traces and changed records, not just whether the answer sounds fluent.
Generate a test suite →Watch cost and memory
Set a run budget, retry cap and privacy policy. If the task can be done reliably with a simple rule, do not make every step a model call.
Set a run budget →Common questions
Agent questions, answered plainly.
Is a prompt the same as an agent?
No. A prompt is instructions. An agent is a workflow that can take steps using the tools and permissions its host actually provides. A good instruction prompt is the starting contract, not the whole system.
Can I make one without paying for API calls?
Yes, you can prototype a manual workflow inside a product you already use, subject to that product's plan and usage limits. A custom API-powered service may incur model, hosting and tool costs. PromptJoy itself does not execute these prompts or charge visitors for model runs.
Should I create a team of agents?
Usually start with one. Split into specialists only when tasks, ownership and handoffs are clear enough that the extra coordination helps.
Can I trust an agent to send or publish for me?
Only after scoped permissions, representative tests, a preview, explicit approval and a way to detect errors. A confident summary is not evidence that the correct action happened.
Sources and further reading
Our setup advice is platform-neutral. For current product-specific capabilities, check OpenAI's GPT creation guide, Codex and ChatGPT skill guidance, and the Agents API documentation. Product features, pricing and eligibility can change.