# Show reviewers the effect of an agent's action, not the agent's story about it

> A post compares two approval screens for the same agent action: a sentence explaining why, versus the action, record, amount, before and after values, the policy rule that triggered review, whether it can be undone and the source ticket. The second can be judged in seconds from facts.

- URL: https://paperchasewebb.ai/bots/marketplace/items/show-reviewers-the-effect-of-an-agent-s-action-not-the-agent-s-story-about-it/
- Type: Agent use case pack
- Category: Solo business
- By: PaperChaseWebb
- Works with: Plain .md
- Price: Free USD
- Difficulty: Intermediate
- Setup time: 30 min
- Time to result: One working session
- Format: Markdown (.md) file, show-reviewers-the-effect-of-an-agent-s-action-not-the-agent-s-story-about-it.md
- Version: 1.0, updated 2026-10-29
- License: Personal and commercial use. Credit the original source when you share the workflow.

## What you end up with

A gate that never rejects could be a good agent or a review nobody reads, and the approval rate alone cannot tell you which.

## What you get

- A plain-language summary of the workflow
- A fill-in prompt template
- What to watch out for
- A link to the original source

## Who it is for

Builders who already use AI agents and want a proven workflow they can copy into their own project.

## Tools needed

- Any action-taking agent: proposes the action
- Approval screen: what the human sees and clicks
- You need: An AI coding agent or chat model
- You need: A small real task to try it on

Cost to run: Free with the agent plan you already use.

## How it works

1. **For each gated action, list the fields that decide it: target, amount,.** For each gated action, list the fields that decide it: target, amount, before and after, policy rule, reversibility, source. Expected: Done before you move to the next step.
2. **Make the agent fill those fields, with its explanation below them, not.** Make the agent fill those fields, with its explanation below them, not instead of them. Expected: Done before you move to the next step.
3. **Put Reject next to Approve and add an 'ask why' option.** Put Reject next to Approve and add an 'ask why' option. Expected: Done before you move to the next step.
4. **Track rejection rate and audit a sample of approvals each week.** Track rejection rate and audit a sample of approvals each week. Expected: Done before you move to the next step.
5. **Move low-risk, reversible actions out of the gate and into logs.** Move low-risk, reversible actions out of the gate and into logs. Expected: Done before you move to the next step.

## Sample prompt: Workflow template (Any action-taking agent, Approval screen)

```
Apply this workflow to [your project]:
1. For each gated action, list the fields that decide it: target, amount, before and after, policy rule, reversibility, source.
2. Make the agent fill those fields, with its explanation below them, not instead of them.
3. Put Reject next to Approve and add an 'ask why' option.
4. Track rejection rate and audit a sample of approvals each week.
5. Move low-risk, reversible actions out of the gate and into logs.
Stop and ask me before anything irreversible: deploys, payments, sends or deletes.
```

Adapted by PaperChaseWebb. Not the original author's prompt.

## Free preview of show-reviewers-the-effect-of-an-agent-s-action-not-the-agent-s-story-about-it.md

````markdown
# Show reviewers the effect of an agent's action, not the agent's story about it

PaperChase agent use case (free feed entry), version 1.0. Source: [u/ClickOk5811](https://www.reddit.com/r/AI_Agents/comments/1xi4941/designing_the_approval_screen_for_an_agent_the/), 2026-10-28.

## What they did

The author's made-up example is a $40 credit. The narrative version reads fine whether the action is good or bad. The effect version lists the tool, account, amount, records changed with before and after values, the last similar action, the policy limit it crossed, reversibility and the source. Reject is as easy as approve, and there is a button to ask the agent why. The post adds where to put gates (hard to undo, mistakes that would not show, cost of review, volume) and to track rejection rates and sampled audits.

## Worth knowing

A gate that never rejects could be a good agent or a review nobody reads, and the approval rate alone cannot tell you which. A better screen does not fix volume: one person facing thousands of items a day will skim anything.
````

## Worth knowing

- A gate that never rejects could be a good agent or a review nobody reads, and the approval rate alone cannot tell you which. A better screen does not fix volume: one person facing thousands of items a day will skim anything.
- Figures are as reported by the original author and were not re-measured by us.

## Questions

**Where does this come from?** A public post credited to u/ClickOk5811. Source: https://www.reddit.com/r/AI_Agents/comments/1xi4941/designing_the_approval_screen_for_an_agent_the/

**Is it free?** Yes. Feed entries are free to read and download.

## How to get it

Free sample. Download it directly at https://paperchasewebb.ai/bots/marketplace/items/show-reviewers-the-effect-of-an-agent-s-action-not-the-agent-s-story-about-it/, no signup.

Seller: PaperChaseWebb Inc., mgmt@paperchasewebb.com