> For the complete documentation index, see [llms.txt](https://integrations.impact.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://integrations.impact.com/ai-solutions/mcp-skills/brand-skills/brand-action-inquiry-review-queue-skill.md).

# Brand Action Inquiry Review Queue Skill

Use this skill to build a review queue for action inquiries submitted against your program, like new/unresolved tickets, aging deadlines, inquiries nearing auto-approval, and incomplete replies waiting on a partner. It generates a Markdown review queue with status counts and 3 next actions pointing at *Review* or *Upload Resolutions* in the platform.

### Prerequisites

* MCP access enabled on your impact.com brand account.
* Client connected per [MCP Quick Start](/ai-solutions/mcp-quick-start.md).
* Action Inquiries enabled on your account. This feature may require a specific impact.com edition. [Contact us](https://app.impact.com/support/portal.ihtml?createTicket=true) if you need to upgrade.

### Install the skill

{% file src="/files/6jzryS5toX4FkXkorCWa" %}

1. Download or copy the skill package above.
2. Install it in Claude, Cursor, or VS Code using the [Install an MCP Skill](/ai-solutions/mcp-skills/install-an-mcp-skill.md) help page.
3. Use this package's frontmatter when the AI client asks for metadata:
   * Name: `Brand action-inquiry review queue`
   * Description: `Build an action-inquiry review queue for an impact.com brand account from live MCP data. Use when the user asks about new or unresolved inquiries, partner disputes, aging deadlines, auto-approval, incomplete replies waiting on a partner, or a named inquiry, order, or partner in the inquiries queue.`
   * Folder name (Cursor / VS Code): `brand-action-inquiry-review-queue`
4. With impact.com MCP connected, prompt: "Show my unresolved action inquiries for the last 90 days. Flag anything past deadline or near auto-approval, and pull detail for the inquiry on order \[Order Id] if it appears."


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://integrations.impact.com/ai-solutions/mcp-skills/brand-skills/brand-action-inquiry-review-queue-skill.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.