The outcome

Use hosted and custom tools without prompt-injection escalation, cross-tenant access, duplicate side effects, or leaked credentials.

OpenAI API Platform is a Developer platform for multimodal model APIs, the Responses API, tools, realtime applications, agents, files, fine-tuning, batch processing, evaluation, and governance. Building production text, vision, audio, realtime, image, video, retrieval, and tool-using applications through managed models and platform APIs. This guide narrows that broad capability into one repeatable outcome, with checkpoints that keep the source material and your judgment in the loop.

Before you begin

Set the boundary before the tool starts.

Choose one real task, identify who will use the result, and decide what evidence or test will make the result acceptable. Gather only the source material needed for that task. If the work contains confidential, personal, regulated, or client-owned information, confirm that the platform and account are approved before sharing it.

Troiana principle

AI should make the work easier to inspect. If the workflow removes the source, the owner, or the review step, redesign the workflow.

Step by step

A workflow you can repeat.

  1. 01

    Define an allowlist of narrow tools, user and tenant roles, data boundaries, schemas, side effects, approval thresholds, budgets, retries, stopping conditions, and audit fields.

  2. 02

    Keep project keys server-side, send a stable privacy-preserving safety identifier for end users, minimize context, and never place credentials or unrestricted URLs in prompts or tool descriptions.

  3. 03

    Parse tool calls as untrusted, reject unknown names and fields, canonicalize inputs, reauthorize against current server state, and require explicit confirmation for consequential or external writes.

  4. 04

    Execute through scoped service accounts with idempotency, timeouts, rate and spend limits, sandbox code and computer use, and return bounded results with no secrets or excessive records.

  5. 05

    Test direct and indirect injection, confused deputy, tenant crossover, forged IDs, replay, parallel calls, exfiltration, denial, provider failure, safeguard intervention, cancellation, and rollback.

Working standard

What good use looks like.

  • Authorize every action outside the model.
  • Make side effects idempotent.
  • Require approval for consequential tools.

API data is not used for training by default unless the customer opts in, but abuse-monitoring logs and feature-specific application state may still be retained; endpoint eligibility differs for Zero Data Retention, residency, background mode, files, audio, video, search, and other tools. Keep keys server-side, separate projects, minimize and classify data, set store deliberately, pin and evaluate models, authorize tools outside the model, moderate inputs and outputs, log request IDs without content, and require approval for consequential actions.

Official references

Check the current product documentation.

Features, plan limits, availability, and data controls change. These official pages are the starting points used for this collection.