Add Skill: code-review-agent-workflow #20

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---
name: code-review-agent-workflow
version: 1.0.0
description: Automate the code review process using a multi-step workflow with human-in-the-loop
approval.
inputs:
- Sample diff of code changes (str)
- Repo context (dict)
steps:
- 'Step 1: Build the graph for the code review agent using `build_graph()` from `agentkit.workflow.code_review.graph`'
- 'Step 2: Invoke the graph with initial parameters including sample diff, repo context,
user ID, and other metadata'
- 'Step 3: The graph processes the input through a series of steps, generating messages
and issues as it progresses'
outputs:
- Final result containing processed messages and issues (dict)
tags: []
metadata:
source_repo: https://github.com/itszhaoziyan-n/AgentKit.git
extracted_at: ''
confidence: 0.95
---
# code-review-agent-workflow
Automate the code review process using a multi-step workflow with human-in-the-loop approval.
## Setup
**Dependencies:**
```text
pip install langgraph>=0.3 langchain-core>=0.3 langchain-anthropic>=0.3 langfuse>=2.0 mcp[server]>=1.24,<2.0 langchain-mcp-adapters>=0.1 tenacity>=9.0 fastapi>=0.115 uvicorn[standard]>=0.32 psycopg[binary]>=3.1 langgraph-checkpoint-postgres>=2.0 httpx>=0.27 python-dotenv>=1.0 redis>=5.0
```
**Setup steps:**
1. cp .env.example .env
1. docker compose up -d
1. pip install -e '.[dev]'
## Key Files
- `agentkit/workflow/code_review/graph.py - Contains the `build_graph` function and graph invocation logic.`
- `examples/run_code_review.py - Example script demonstrating how to run the code review agent.`
## Steps
1. Step 1: Build the graph for the code review agent using `build_graph()` from `agentkit.workflow.code_review.graph`
2. Step 2: Invoke the graph with initial parameters including sample diff, repo context, user ID, and other metadata
3. Step 3: The graph processes the input through a series of steps, generating messages and issues as it progresses
## Implementation Details
```python
graph = build_graph()
thread_id = str(uuid.uuid4())
result = graph.invoke(...)
```
## Inputs
- Sample diff of code changes (str)
- Repo context (dict)
## Outputs
- Final result containing processed messages and issues (dict)
## Failure Modes
- Specific failure scenario with mitigation: If the `build_graph()` function fails to initialize properly, ensure all required dependencies are correctly installed.
## Source
Extracted from: [https://github.com/itszhaoziyan-n/AgentKit.git](https://github.com/itszhaoziyan-n/AgentKit.git)
Confidence: 0.95
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# Commands: code-review-agent-workflow
## Available Commands
- `/skill code-review-agent-workflow` — Load this skill
- `/run code-review-agent-workflow` — Execute workflow
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# Examples: code-review-agent-workflow
## Usage Example
```python
# How to use this skill
# Inputs: Sample diff of code changes (str), Repo context (dict)
# Process: Step 1: Build the graph for the code review agent using `build_graph()` from `agentkit.workflow.code_review.graph` → Step 2: Invoke the graph with initial parameters including sample diff, repo context, user ID, and other metadata → Step 3: The graph processes the input through a series of steps, generating messages and issues as it progresses
# Outputs: Final result containing processed messages and issues (dict)
```
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{
"name": "code-review-agent-workflow",
"version": "1.0.0",
"goal": "Automate the code review process using a multi-step workflow with human-in-the-loop approval.",
"inputs": [
"Sample diff of code changes (str)",
"Repo context (dict)"
],
"steps": [
"Step 1: Build the graph for the code review agent using `build_graph()` from `agentkit.workflow.code_review.graph`",
"Step 2: Invoke the graph with initial parameters including sample diff, repo context, user ID, and other metadata",
"Step 3: The graph processes the input through a series of steps, generating messages and issues as it progresses"
],
"outputs": [
"Final result containing processed messages and issues (dict)"
],
"failure_modes": [
"Specific failure scenario with mitigation: If the `build_graph()` function fails to initialize properly, ensure all required dependencies are correctly installed."
],
"confidence": 0.95,
"explanation": "This workflow is reusable for any code review process that requires a multi-step analysis and human approval.",
"source_repo": "https://github.com/itszhaoziyan-n/AgentKit.git",
"score": 1.0
}
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# Tests: code-review-agent-workflow
## Test Checklist
- [ ] Workflow has at least 3 steps
- [ ] All inputs are defined
- [ ] All outputs are defined
- [ ] Failure modes are documented
- [ ] Skill can be loaded without errors