AI API Validator

Do all your endpoints agree on what a 404 means? Does one return an empty array for a missing collection while another returns 404, and can anyone say which is correct?

APIs drift endpoint by endpoint, and each individual decision looked reasonable at the time. The AI API Validator reads your API and checks it against the conventions it claims to follow, so the inconsistencies surface before your integrators find them.

What is AI API Validator?

Validation here means review, not runtime checking. It compares what your API does against what a well behaved HTTP API is expected to do, and against what the rest of your own API does.

The prompt box asks you to describe the API or endpoint you need, naming the resource, methods and fields. For a review, paste what exists: route definitions, an OpenAPI file, or a written description of every endpoint.

The output is a list of findings with reasoning. Some will be genuine mistakes, some will be deliberate choices, and the reasoning is what lets you tell them apart.

Why Use AI API Validator?

Inconsistency costs more than imperfection. An integrator can learn one convention, even an unusual one. Three conventions across twelve endpoints means every call needs checking against the documentation.

The second reason is that some mistakes are invisible from inside. Returning 200 with an error body, using POST for a read, or exposing an internal identifier in a public response are all things you stop noticing after the second endpoint.

Who Should Use It?

• Teams about to publish an API, where changing it afterwards means versioning
• Platform teams reviewing APIs written by several squads
• Developers inheriting an API and needing to know how consistent it really is
• Anyone writing an API style guide who needs evidence of where things diverge
• Reviewers checking that a new endpoint matches the ones around it

How Does AI API Validator Work?

Prompt box. Open the AI API Validator and paste your route definitions, schema or endpoint descriptions.

Model selector. Set the engine, from MSB AI, OpenAI ChatGPT, Google Gemini, Anthropic Claude AI, xAI Grok AI, DeepSeek, Qwen, Meta AI, NVIDIA AI, OpenRouter AI and MiniMax.

Advanced options accordion. Ten controls in total: Language / Framework, API Style, Output and Auth as dropdowns, four toggles, a Detail Level slider and a free text field.

Generate button. Definitions, model and settings run through the prompt engineering layer written for API work, which is the instruction set that makes it review rather than generate.

Output card. The findings appear under the button with a live word count, plus copy, listen, reuse, download and open in full view.

Export row. DOC, TXT and HTML. DOC when the review is going into a discussion about what to change before launch.

Activity history. Session generations stay listed, so a review before changes and one afterwards can be compared directly.

Step-by-Step Guide

1. Collect every endpoint of one API, or one coherent group of them.
2. Write down the conventions you believe you follow. Casing, pluralisation, error format, versioning.
3. Paste the endpoints and those conventions into the prompt.
4. Set API Style and Auth to match reality.
5. Set Detail Level around 70 so the review goes past the obvious.
6. Generate, then split the findings into mistakes, deliberate choices and matters of taste.
7. Fix the mistakes before you publish. After publication they need a version.
8. Write the deliberate choices into your style guide so the next review does not raise them again.

Advanced Options Guide

Example Inputs

Review these endpoints against each other and against REST.

GET    /users                 200 list
GET    /user/{id}             200 or 404
POST   /users                 200 with the created user
PUT    /users/{id}/deactivate 200 {"ok": true}
DELETE /users/{id}            200 {"deleted": true}
GET    /users/{id}/Orders     200 list, empty array if none
POST   /orders/create         201

Conventions we think we follow: plural paths, snake case
fields, errors as {code, message}.

Seven endpoints and at least five inconsistencies, none of which looked wrong when it was written. That is what makes this worth doing before publication rather than after.

Example Outputs

FINDING 1  Path pluralisation is inconsistent
  /user/{id} is singular, every other path is plural.

FINDING 2  Created resources return 200, not 201
  POST /users returns 200. POST /orders/create returns 201.
  Two endpoints, two conventions.

FINDING 3  /orders/create is RPC style
  The action is in the path rather than the method. POST
  /orders is the equivalent under the conventions you stated.

FINDING 4  Casing changes in /users/{id}/Orders
...

Finding 3 is the interesting one, because the endpoint works perfectly and nobody will ever file a bug about it. It just means an integrator cannot predict your next endpoint from the last one, which is the whole benefit of a convention.

Once the findings are agreed, write them down properly with the AI Technical Spec Writer, and pin the corrected behaviour with the AI Test Case Generator so it does not drift back.

Comparison Table

• ✅ Several endpoints reviewed together, not one
• ✅ Your stated conventions written into Custom Instructions
• ✅ Findings split into mistakes, choices and taste
• ✅ Mistakes fixed before publication rather than after
• ✅ Deliberate choices recorded in a style guide

AIToolsay is a free AI tools platform where each tool is a dedicated workspace with its own prompt engineering and its own options panel, rather than one general chat box under many names. All the tools are free to run and none of them need an account. Picking the engine is part of it too, from MSB AI, OpenAI ChatGPT, Google Gemini, Anthropic Claude AI, xAI Grok AI, DeepSeek, Qwen, Meta AI, NVIDIA AI, OpenRouter AI and MiniMax. Around the tools sit an AI directory, an AI models directory, courses, prompts, guides and news, all reachable from the AIToolsay homepage.

Frequently Asked Questions

An API is a promise about how the next endpoint will behave. Paste the whole set, say what conventions you meant to follow, and let the AI API Validator show you where the promise has quietly stopped being kept.

Thanks for reading, and good luck with the review. If this becomes part of how you ship an API, join the AIToolsay community, follow along on social media, turn on push notifications for new tools, and subscribe to the newsletter for the occasional summary.

Let AI Speak.