# How should an AI assistant validate a post before publishing?

> Call validate_post before every schedule or publish. It runs the same checks as the real call, creates nothing, & returns valid plus a list of issues. When valid is false, fix what issues[].next says & retry, instead of publishing anyway.

Updated: 2026-10-05.

## What validate_post is

`validate_post` is a dry run. It takes the same input as `schedule_post` or `publish_now` & checks whether that post would be accepted, without creating a post or queueing anything.

It exists so an assistant can find problems while they're cheap to fix, instead of finding them as a failed publish.

## What it checks

- Character limits for each target platform
- Media: whether it exists & fits the platform
- Required platform options, such as a Reddit subreddit & title or an Instagram format
- The X monthly posting cap, when X is a target

Because it runs the same checks as the real call, a post that passes validation can be sent unchanged to schedule or publish.

## What the answer looks like

The result is a `valid` flag plus a list of issues. Each issue names the account, the platform, a code & a message.

When `valid` is `false`, the assistant should read `issues[].next`, which says what to change, apply the fix & validate again. It shouldn't publish anyway & hope.

## Why validation is all-or-nothing

DunSocial validates a whole batch together. If one account in the batch has a problem, such as a post that is too long for one platform, none of the accounts are created.

That avoids a half-published batch where some platforms went out & others didn't. Fix the single failing target & send the batch again.

## Teaching an assistant to do it

Most assistants won't validate unless told to. Add one line to your instructions or a saved prompt:

> Always call validate_post first. If valid is false, fix the issues & retry. Never publish while valid is false.

That single rule prevents the most common failures, like a 283-character post going to X.

DunSocial's MCP tool descriptions already tell assistants to validate first, but a line in your own instructions makes it a habit rather than a suggestion.

## Where it fits in DunSocial

Validation guards the technical side. It can't judge tone, accuracy or whether a claim is true. DunSocial's calendar & review step are where a person catches those.

A good pattern is validate, schedule rather than publish, then review in the calendar. The assistant does the repetitive checking & you keep the final say.

## Related guides

- [What can an AI assistant do with DunSocial MCP tools?](https://www.dunsocial.com/hub/dunsocial-mcp-guides/what-can-an-ai-assistant-do-with-dunsocial-mcp-tools.md)
- [Why can't my AI assistant publish through DunSocial MCP?](https://www.dunsocial.com/hub/dunsocial-mcp-guides/why-cant-my-ai-assistant-publish-through-dunsocial-mcp.md)
- [How to validate a social post before scheduling it with the API](https://www.dunsocial.com/hub/dunsocial-api-and-sdk-guides/how-to-validate-a-social-post-before-scheduling-it-with-the-api.md)
- [Do you still need to review AI-written social media posts?](https://www.dunsocial.com/hub/ai-social-media-manager/do-you-still-need-to-review-ai-written-social-media-posts.md)

## About this document

This is the Markdown representation of https://www.dunsocial.com/hub/dunsocial-mcp-guides/how-should-an-ai-assistant-validate-a-post-before-publishing. The HTML version of the same page is at the same URL. You can also request Markdown from any page by sending `Accept: text/markdown`.

Machine-readable summary of the whole site: https://www.dunsocial.com/llms.txt

## Company

- Product: DunSocial, https://www.dunsocial.com
- Legal entity: THISUX PRIVATE LIMITED, Chennai, Tamil Nadu, India
- Support: support@dunsocial.com
- Open the app: https://app.dunsocial.com/login