Git and CI/CD Integration

A coding agent shouldn't just exist in a vacuum; it should be part of your Team. In a professional setting, we don't just "Edit files"; we use Version Control.

In this lesson, we will learn how to build the "Social Skills" of an agent—teaching it to use Git, create branches, and respond to CI/CD failures.

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1. The Git Workflow Toolkit

Your agent needs a set of Git-specific tools to interact with your repository safely.

• create_branch(name): "I'll start this fix on feature/auth-bug."
• git_add_and_commit(msg): "Finished the refactor. Comitting with message: 'refactor: update auth schema'."
• push_to_remote(): Uploading to GitHub/GitLab.
• create_pull_request(): The final step.

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2. Pattern: The "Feature Branch" Isolation

Never let an agent commit directly to main.

The Automated Workflow:

1. User says "Add a dark mode toggle."
2. Agent creates a unique branch: agent-ui-fix-172.
3. Agent performs all edits and tests on this branch.
4. Agent pushes and creates a PR.
5. Human Reviewer (You) looks at the PR and merges it.

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3. Dealing with Merge Conflicts

Merge conflicts are the biggest hurdle for Git-aware agents. Strategy: Conflict Resolution Node.

1. The push tool fails with a "Conflict Error."
2. The agent reads the conflict markers (<<<<<<&lt; HEAD).
3. The agent reasons about which version of the code is "Correct" for its current goal.
4. The agent resolves the markers and attempts the commit again.

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4. Integration with CI/CD (The Feedback Loop)

Often, a code change looks good on the agent's machine but fails on the Production Build Server (due to OS differences or missing secrets).

The "Loop-Back" Pattern:

1. Agent creates a PR.
2. Github Actions runs.
3. The build Fails.
4. A Webhook notifies your FastAPI backbone.
5. The agent "Wakes Up," reads the build logs from the failure, and Applies a new fix to the same branch.

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5. Writing Commit Messages

LLMs are excellent at summarizing their own changes. Pro-tip: In your commit tool, force the agent to follow a Conventional Commits standard:

• feat: ..., fix: ..., docs: .... This keeps your repo history clean and readable for human auditors.

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6. Implementation Example: Creating a PR via API

import requests

def create_pr(branch, title, description):
    # Use the GitHub API to create a PR automatically
    url = f"https://api.github.com/repos/{OWNER}/{REPO}/pulls"
    data = {
        "title": title,
        "head": branch,
        "base": "main",
        "body": description
    }
    return requests.post(url, json=data, auth=(USER, TOKEN))

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Summary and Mental Model

Think of Git Integration like Writing in Pencil.

• The agent works on its own "Paper" (Branch).
• If it makes a mistake, you don't have to restart the whole project (Rollback).
• You are the "Editor" who decides when the pencil marks are turned into "Ink" (Merging to Main).

Git is the safety net that allows you to trust an autonomous coding agent.

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Exercise: Workflow Design

1. Automation: A human engineer pushes a commit to a PR.
   • Design a trigger that wakes up an Audit Agent to review the code and leave comments in the PR.
2. Safety: What happens if the agent tries to git push --force?
   • Should your tool allow this? Why/Why Not?
3. Logic: Draft a "PR Description" for an agent that just added a Logout Button.
   • It should include: "What was changed", "Why it was changed", and "How to test it". Ready for the final step of the coding cycle? Next lesson: Writing Tests for Agent-Generated Code.