# GitHub Pull Request Activity

> Use this tool when you need to automate the retrieval of GitHub pull request activity for performance reviews. It solves the problem of manually searching through GitHub history by fetching a user's opened pull requests within a specified month and formatting the results as structured XML output. Ideal for developers who require a streamlined way to compile their contributions for regular performance evaluations.

Canonical page: https://skillsregistry.net/skills/kfischer-okarin-performance-review  
JSON: https://api.skillsregistry.net/v1/skills/kfischer-okarin-performance-review

## Description

Performance Review Data MCP Server provides developers with tools to retrieve GitHub pull request activity for performance reviews. Built by Kevin Fischer, it integrates with the GitHub API to fetch a user's opened pull requests within a specified month, formatting the results as structured XML output. The implementation uses environment variables for configuration, includes proper error handling, and follows Ruby best practices with modular code organization. Particularly valuable for developers who need to compile their contributions for regular performance evaluations without manually searching through GitHub history.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** version-control
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/kfischer-okarin-performance-review)
- **Repository:** <https://github.com/kfischer-okarin/mcp-server-performance-review-data>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "kfischer-okarin-performance-review"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kfischer-okarin-performance-review` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kfischer-okarin-performance-review/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt