> 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-partner-performance-scorecard-skill.md).

# Brand Partner Performance Scorecard Skill

Use this skill to rank your active partners by clicks, actions, and revenue over any date range. It generates a markdown performance scorecard with period-over-period comparisons and three key action items.

For partners you have not recruited yet, use the [Brand Partner Discovery Brief](/ai-solutions/mcp-skills/brand-skills/brand-partner-discovery-brief-skill.md) instead.

### Prerequisites

* MCP access enabled on your impact.com brand account.
* Client connected per [MCP Quick Start](/ai-solutions/mcp-quick-start.md).

### Install the skill

{% file src="/files/uEjQgZaic370s1ZG7KZa" %}

1. Download or copy the skill package above.
2. Install it in Claude, Cursor, or VS Code using [Install an MCP Skill](/ai-solutions/mcp-skills/install-an-mcp-skill.md).
3. Use this package's frontmatter when the AI client asks for metadata:
   * Name: `Brand partner performance scorecard`
   * Description: `Build a ranked partner performance scorecard for an impact.com Brand account from live MCP data. Use to see which partners are driving clicks, actions, and revenue for a program, ranked and compared to a prior period.`
   * Folder name (Cursor / VS Code): `brand-partner-performance-scorecard`
4. With impact.com MCP connected, prompt: "Run the partner performance scorecard for last month."


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# 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-partner-performance-scorecard-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.
