✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount
✨ New Plugin Alert ✨ SleekRank is now available with €50 launch discount

SleekView Feedback for OpenAI for WordPress

OpenAI for WordPress stores prompts, completions, and run logs in your database. SleekView Feedback reads those rows and renders them as a sorted board with vote counts, status pills, and category tags so writers, editors, and clients can react to the output instead of arguing about it in Slack.

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SleekView Feedback board for OpenAI for WordPress

From OpenAI run logs to a live review board

OpenAI for WordPress writes every completion to a post or a row in its log table, with the prompt template, the model, the token usage, and the resulting draft attached as meta. That is useful when you want to debug a single run, but it is a terrible interface for an editor who wants to know which of the last two hundred drafts are worth publishing and which prompts keep producing the same generic intro.

SleekView Feedback reads any data source you point it at, whether that is a custom query against wp_posts, the plugin log table, or a saved postmeta view scoped by job. It renders one card per completion with vote count, author, category pill, and status pill, and the upvote button writes straight back to the column you wired up as the score.

The result is a public board where prompt revisions, hallucination reports, and feature requests live next to the original generation. Editors stop missing good drafts, clients stop guessing what is queued next, and the prompt engineer finally has a sorted backlog of what to fix first.

Workflow

From OpenAI runs to a sorted feedback board

1

Pick the OpenAI data source

Point SleekView at the post type or table OpenAI for WordPress writes to. Generated drafts in posts, prompt templates in a CPT, or run logs all work. Apply a WHERE clause to scope by model or date so the board shows only what you care about.
2

Map score, status, category

Choose which column counts as upvotes, which one carries the status label such as draft or approved, and which one holds the campaign or niche tag. SleekView reads those columns on every page load so the board always reflects what your editors did last.
3

Embed the feedback view

Drop the SleekView block on a page or use the shortcode. Visitors see a paginated, filterable list of completions with title, vote count, author, status pill, and category pill. Restrict the board to editors or open it up to readers with a single setting.
4

Votes write back to the row

Every upvote increments the score column on the source row. Future OpenAI jobs can sort by that score, retire low scoring templates, and prioritise the prompts earning real attention. The feedback loop becomes a number in the database instead of a hunch.

Sample board

Sample OpenAI for WordPress review board

A look at how recent OpenAI runs land on a SleekView Feedback board, with prompt revisions, hallucination flags, model swaps, and editor praise mixed together in one sortable list.
284 votes
GPT 4 keeps inventing fake statistics in finance posts
Helena Roth Hallucination Investigating
196 votes
Add a prompt template for product comparison roundups
@chefmarco Prompt request Planned
147 votes
Token usage column missing from the run log
Priya Narayanan Bug In progress
118 votes
Switching default model to GPT 4o sped up bulk runs
Tomasz Kowalski Praise Shipped
73 votes
Retry on rate limit hits the same prompt twice
@seoannika Bug Open
29 votes
Native function calling for outline generation
Lukas Wagner Feature request Under review

Comparison

Plugin admin screens vs SleekView Feedback

OpenAI plugin defaults

  • Completion logs sit in a back office table only admins ever open
  • No way for editors or readers to upvote prompts that produced good drafts
  • Hallucination reports live in Slack screenshots, not next to the draft
  • Status of each run is buried in row level meta with no shared view
  • No public queue to show clients which prompts are queued, shipped, or killed

SleekView Feedback

  • One card per OpenAI completion with title, votes, status pill, and category tag
  • Upvote writes back to the source column so future runs can sort by score
  • Filter by model, campaign, or status using any column in wp_posts
  • Embed on a public page or behind a login with one block or shortcode
  • Editors stop arguing in Slack and start voting on prompts in WordPress

Features

What SleekView Feedback gives you for OpenAI for WordPress

Prompt review built in

Each OpenAI prompt template becomes a votable card. Writers see which prompts the team prefers, which produce hallucinations, and which ones get retired. The board acts as a living changelog of your generation strategy without anyone touching a spreadsheet.

Hallucination reports inline

Add a Hallucination category to the board and editors flag any completion with one click. The flag lives next to the source row, so the prompt engineer fixes the template before the next bulk run instead of finding out from a reader email weeks later.

Upvotes feed back into runs

Because votes write to the source column, you can sort OpenAI queues by score, give high voted prompts more token budget, and retire ones nobody likes. The feedback loop stops being a feeling and becomes a number in the database that future runs can read.

Audience

How teams use the OpenAI feedback board

Editorial team review

Internal editors upvote the OpenAI drafts worth publishing and flag the ones that need a rewrite. The board replaces a messy Google Doc and gives the editor in chief one screen to triage the queue every morning.

Client facing prompt vote

Agencies share the board with clients so they can vote on which OpenAI prompts to keep running. The client sees exactly what is shipping next week and feels in control without ever touching the WordPress admin.

Quality control queue

Compliance teams use the board as a hallucination queue. Anything flagged with a high vote count gets reviewed first, and resolved items move to a Fixed status so the audit trail stays visible without trawling raw logs.

The bigger picture

Why an OpenAI feedback board changes the workflow

OpenAI for WordPress is great at producing volume. It is much worse at telling you which of those completions should actually be published, refined, or thrown away. Most teams end up with a back office full of drafts and a Slack channel full of opinions, and the two never meet.

Editors miss the prompts that work, prompt engineers keep shipping templates that hallucinate, and clients lose trust because nobody can show them what was decided. A feedback board changes that pattern. Completions stop being throwaway artifacts and start being something the team and the audience react to in public.

Upvotes give you a cheap, honest signal about which prompts deserve more budget. Hallucination flags give you a backlog sorted by impact instead of by whoever shouted loudest in the last meeting. And because every vote writes back to the source row, the next OpenAI run already knows what worked.

The result is fewer wasted tokens, fewer embarrassing posts, and a much shorter loop between the prompt you write today and the article that goes live tomorrow.

Questions

Common questions about SleekView Feedback for OpenAI for WordPress

No. SleekView Feedback reads directly from whatever table or post type the OpenAI plugin uses. You point it at the source, pick the columns for votes, status, category, author, and title, and the board renders. No ETL job, no sync, no duplicated data. Anything OpenAI writes shows up on the next page load.

 

Yes. SleekView ships with anonymous voting backed by cookies so public visitors can upvote prompts and drafts without an account. You can also require login if you want the board restricted to editors or paying members, and the same view handles both modes with a single toggle.

 

Each visitor gets a cookie scoped vote token per item. Logged in users are tracked by user ID. A built in rate limit caps how often a single IP can hit the vote endpoint, which keeps public boards honest without forcing a signup wall in front of casual readers.

 

Yes. SleekView accepts a WHERE clause when you wire up the data source, so you can scope the board to GPT 4o runs, GPT 3.5 runs, runs from a particular campaign, or any combination of meta fields. Different boards on different pages can use different filters.

 

Hallucination is just a category value on the row. You can write it into a meta key the plugin already understands or a dedicated column. Either way it shows up in the WordPress admin alongside the original prompt, so the prompt engineer who wrote the template can see the flag without leaving WordPress.

 

They write back to the source column, which means the plugin and any of your own queries can sort future jobs, retries, and bulk runs by that score. Several teams use the score to gate which prompts get more token budget, which makes the board operational and not just a vanity dashboard.

 

Both. SleekView ships as a Gutenberg block, an Elementor widget, a Bricks element, and a classic shortcode. Theme developers can also call the render function from PHP and pass a configuration array, so you can mount the board on any template without touching the page editor.

 

The view paginates server side and only loads the rows it needs to render the current page. Indexed columns stay fast even on long tables. For really big projects, scoping the board by campaign or date keeps both the query and the audience focused so the page feels snappy even at scale.

 

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