agentpipe

🥈Silver

AgentPipe orchestrates multi-agent conversations by enabling different AI CLI tools to communicate in shared rooms. It benefits operations teams by automating complex workflows. The app connects to tools like Claude Code, Gemini, and Qwen, streamlining AI-driven tasks.

11590Updated 1mo ago

Intermediate30min to implementautomation

Saves ~240 min per use

Quick InstallView Source

git clone https://github.com/kevinelliott/agentpipe.git

Works with:

Claude

Overview

About This Skill

How to Use

[{"step":"Install AgentPipe and required CLI tools (e.g., `pip install agentpipe`, ensure Claude Code, Qwen, or other tools are installed).","action":"Run `agentpipe init` to set up a new room and configure the agents."},{"step":"Define the workflow in the AgentPipe room configuration file (e.g., `agentpipe_config.yaml`). Specify the agents, their roles, and the sequence of tasks.","action":"Use the prompt template to generate the configuration. Example: `agentpipe_config.yaml` includes `agents: [claude_code, qwen]` and `workflow: [refactor_code, validate_quality, generate_tests]`."},{"step":"Start the pipeline with `agentpipe run --config agentpipe_config.yaml`.","action":"Monitor the room’s output in the terminal or AgentPipe’s dashboard for real-time progress."},{"step":"Review the final output and validation report.","action":"Address any errors or bottlenecks flagged by the agents. For example, if Agent B flags missing tests, use Agent A to generate them automatically."},{"step":"Integrate the results into your workflow (e.g., commit the code, trigger CI/CD, or notify stakeholders).","action":"Use the `agentpipe export` command to save the output to a file or repository."}]

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/kevinelliott/agentpipe

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Set up an AgentPipe room with [TOOL_A] and [TOOL_B] to automate [TASK]. Configure the agents to follow this workflow: [STEP_1], [STEP_2], and [STEP_3]. Ensure [TOOL_A] handles [SPECIFIC_ACTION] and [TOOL_B] validates [OUTPUT_CRITERIA]. Run the pipeline and provide a summary of the results, including any errors or bottlenecks encountered.

Example Output

AgentPipe Room: **Code Review & Documentation Pipeline**

**Agents Assigned:**
- **Claude Code (Agent A):** Primary executor for code generation and refactoring.
- **Qwen (Agent B):** Validator for code quality, documentation accuracy, and compliance with [COMPANY_STYLE_GUIDE].

**Workflow Execution:**
1. **Input:** User provided a Python script (`data_processor.py`) with a bug in the `calculate_average()` function and missing docstrings.
2. **Agent A (Claude Code):**
   - Detected the bug in `calculate_average()` (incorrect handling of empty lists).
   - Refactored the function to include a `ZeroDivisionError` check and added type hints.
   - Generated a draft docstring for the function.
   - Output: Updated `data_processor.py` with fixes.
3. **Agent B (Qwen):**
   - Validated the refactored code against [COMPANY_STYLE_GUIDE] (PEP 8 compliance, docstring format).
   - Flagged missing unit tests for the new function.
   - Suggested adding a `pytest` test case for `calculate_average()`.
   - Output: Approved the code with annotations for missing tests.
4. **Agent A (Claude Code):**
   - Generated a `test_data_processor.py` file with a test case for `calculate_average()`.
   - Verified the test passed locally.
5. **Final Output:**
   - **Code:** `data_processor.py` (refactored, bug-free, documented).
   - **Tests:** `test_data_processor.py` (new test case added).
   - **Validation Report:** Qwen confirmed 100% PEP 8 compliance and docstring accuracy.

**Errors/Bottlenecks:** None. The pipeline executed in 4 minutes with no manual intervention required. Agent B’s suggestion for unit tests was incorporated seamlessly by Agent A.

**Next Steps:**
- Merge the changes into the main branch.
- Run the full test suite in CI/CD to ensure no regressions.