3 Agent Guide
3.1 What This Page Helps You Do
This guide is for users who want to connect IOBRpy to Codex or Claude Code. It focuses on three practical goals:
- How to install
/iobrpyfor workflow assistance and/iobrpy-resultfor result interpretation and visualization. - How to verify that the installation worked.
- When to use
/iobrpyversus/iobrpy-result.
3.2 Tutorial 1: How to Install the Plugin
3.2.1 Step 0: Activate the IOBRpy Environment
This page assumes that IOBRpy is already installed. If not, please read installation guide first. Here, the only environment preparation you need is:
conda activate iobrpy3.2.2 Step 1: Run the Installation Command
Choose the one command that matches your actual client:
# Claude Code only
iobrpy-cli agent install --client claude-code
# Codex only
iobrpy-cli agent install --client codex
# Both Codex and Claude Code
iobrpy-cli agent install --client allWhat this installs:
codex: the/iobrpyand/iobrpy-resultskills, both Codex plugins, and MCP integration.claude-code: the Claude Code memories,/iobrpyand/iobrpy-resultcommands, and MCP integration.all: both of the above.
Reference standard:
- The command finishes successfully instead of exiting with an error.
- If a component was already present, an
already_installed-style result is still acceptable. - You should not need to manually copy plugin, skill, or MCP files.
3.2.3 Step 2: Verify the Installation
Use the status command that matches what you installed:
# Check Codex only
iobrpy-cli agent status --client codex
# Check Claude Code only
iobrpy-cli agent status --client claude-code
# Check everything
iobrpy-cli agent statusReference standard:
- Ideally, the output should include
Agent status: healthy. - You should no longer see states such as
not_installed,not_configured, orinvalid_config. - After installation, the relevant client should be able to use
/iobrpyand/iobrpy-result.
3.2.4 Step 3: Call the Plugin Inside the Agent
After installation, open your agent client and call the IOBRpy entrypoint directly in the chat input.
IOBRpy provides two agent entrypoints:
/iobrpyis for analysis setup and execution. Use it to inspect input data, choose the right IOBRpy workflow, and prepare or run commands./iobrpy-resultis for finished outputs. Use it to summarize, audit, interpret, compare, or visualize IOBRpy result directories and result tables.
If you are using Codex and specifically want the plugin-scoped namespace, you can also use:
/iobrpy:iobrpy
Reference standard:
- Typing
/iobrpyin the agent should show or trigger the IOBRpy entrypoint. - Typing
/iobrpy-resultshould trigger IOBRpy-specific result visualization and interpretation. - After you send a message with
/iobrpy, the agent should respond as an IOBRpy workflow assistant rather than a generic chat assistant. - After you send a message with
/iobrpy-result, the agent should focus on existing result files rather than planning a new run by default. - In Codex,
/iobrpy:iobrpyshould also work when you want the plugin namespace explicitly. - The best first test is to give a real path or a concrete analysis goal, not just
/iobrpyor/iobrpy-resultalone.
3.3 Common Problems and Fixes
| Symptom | Common cause | Suggested fix |
|---|---|---|
iobrpy-cli is not recognized |
The current shell is not in the right environment, or IOBRpy is not installed yet | Activate the environment with conda activate iobrpy, and if needed follow the installation guide first |
agent status shows needs attention |
One client is missing part of the skill, plugin, or MCP setup | Check iobrpy-cli --json agent status first, then rerun the relevant agent install --client ... command |
Codex does not show /iobrpy or /iobrpy-result |
The skill or plugin did not take effect | Rerun iobrpy-cli agent install --client codex --force |
| Claude Code installation fails | The claude CLI is missing, or the config path is not writable |
Install or fix the Claude Code CLI setup, then retry iobrpy-cli agent install --client claude-code |
| You suspect the setup is outdated | Older local agent files may still be present | Rerun the matching iobrpy-cli agent install --client ... command and check status again |
3.4 Tutorial 2: Prompt Examples
3.4.1 1. /iobrpy: Workflow Assistance
Use /iobrpy before or during analysis, especially when you are not yet sure what the directory contains or which workflow command is the right one.
/iobrpy Please scan path/to/your/target/directory
Show me the full checklist first, then tell me the current stage and the best next step.
After the scan, the agent will usually tell you which workflow best matches your directory and your current stage.
Typical examples:
- If the directory contains raw FASTQ data, the agent will usually suggest
runall. - If the directory already contains a TPM matrix, the agent will usually suggest
tme_profile. - If the directory contains BAM files for HLA analysis, the agent will usually suggest
hla_typing. - If the goal is TCR/BCR repertoire analysis, the agent will usually suggest
trust4.
This means you do not need to decide the command first. Start with the scan, then choose the command that matches the agent’s recommendation and your real analysis goal.
Reference standard:
- Your first prompt includes a real path.
- The agent returns a checklist and a current-stage summary.
- You choose the next command based on the scan result instead of guessing before the scan.
3.4.2 2. /iobrpy-result: Result Interpretation and Visualization
Use /iobrpy-result after IOBRpy has already generated result files.
/iobrpy-result Please summarize, interpret, and visualize path/to/iobrpy/result/directory
Typical examples:
- If you want to understand what has already been generated, ask
/iobrpy-resultto summarize the result directory. - If you want biological interpretation, point
/iobrpy-resultto the output table or workflow output directory. - If you want a figure, explicitly ask
/iobrpy-resultto visualize the result and say whether you prefer Python or R. - If you ask for visualization without naming a backend,
/iobrpy-resultwill ask you to choose Python or R before creating figures.
Reference standard:
- Use
/iobrpy-resultfor result reading, interpretation, comparison, and visualization. - Use
/iobrpywhen you still need to choose, configure, or run an IOBRpy workflow.