Use cases

note

Seqera Cloud users receive $20 in free credits to get started with Seqera AI. Contact us for additional credits.

Seqera AI is an intelligent command-line assistant that helps you build, run, and manage bioinformatics workflows. The following sections describe several common use cases.

Work with Nextflow

Seqera AI helps you develop, debug, and understand Nextflow pipelines with AI-powered analysis and code generation.

Working with Nextflow

Understand your pipeline structure:

> Show me the structure of main.nf

> What processes are defined in this pipeline?

> /nf-pipeline-structure

Use /nextflow-config to generate and explain Nextflow configuration files:

> /nextflow-config

Debug your pipeline:

> /debug

> Why is my pipeline failing?

Review local execution history:

> /nf-run-history

Trace output provenance with data lineage:

> /nf-data-lineage

Use /nextflow-schema to generate nextflow_schema.json and sample sheet schema files:

> /nextflow-schema

Convert scripts to Nextflow:

> /convert-python-script

Fix strict syntax issues:

> /fix-strict-syntax

Migrate old schema definitions:

> /nf-schema-migration

Work with Seqera Platform

Use Seqera Platform capabilities to run and manage workflows at scale with AI assistance.

Working with Seqera Platform

List your workflows:

> List my recent workflows

Launch a pipeline:

> Launch the nf-core/rnaseq pipeline with the test profile

Debug failed runs:

> Why did my last workflow fail?

> Get the logs for the failed task in my last run

Build containers with Wave

Seqera AI can create containerized environments using Wave, without the need to write Dockerfiles.

Building containers with Wave

Create a container with conda packages:

> Create a container with samtools and bwa from bioconda

Create a container with pip packages:

> Build a container with pandas, numpy, and scikit-learn

Get a container for a specific tool:

> I need a container with FastQC version 0.12.1

note

The assistant will generate a Wave container URL that you can use directly in your Nextflow pipelines or pull with Docker.

Customize your session

Customize your session with command-line options.

Customize your session

Start with an initial query:

seqera ai "list my pipelines"

Continue your last session:

seqera ai -c

Resume a specific session:

seqera ai -s <session-id>

Set approval mode for local commands:

seqera ai --approval-mode full

Switch between build mode and plan mode:

• Press Shift+Tab in the composer
• Check the current mode in the composer footer
• Use /status if you want a full status readout

Inspect available built-in commands and skills:

/help

Plan work before you edit

Use plan mode when you want analysis and a concrete implementation plan before making changes.

Planning in plan mode

Compare implementation strategies:

> Compare whether I should add FastQC or fastp as the first QC step in this RNA-seq pipeline, including the workflow changes each option would require

Ask for a step-by-step rollout plan:

> Plan the work to add GPU support to this pipeline

Review a codebase without modifying it:

> Inspect this repository and outline the changes needed for Seqera Platform deployment

note

Plan mode is designed for read-only analysis. To execute commands, edit files, or write code, switch back to build mode with Shift+Tab.

Use goal mode for longer tasks

Use goal mode when you want Seqera AI to keep working toward a task over multiple model attempts.

Working in goal mode

Start a persistent task:

/goal migrate this pipeline to DSL2 and add nf-tests

Check the active goal:

/goal

Disable goal mode:

/goal off

note

Goal mode automatically switches command approval to full so the assistant can keep making progress. See Command approval for details.

Exit the assistant

End your Seqera AI session when done.

Exit the assistant

To end your session:

• Type /exit, /quit, or /q
• Press Ctrl+C

note

Your conversation history is preserved. You can resume a session later with seqera ai -c to continue your most recent session.

Use slash commands

Seqera AI includes built-in slash commands for common workflows.

TUI commands

These commands are handled locally by the CLI:

Command	Description
/help	Show available commands
/exit (/quit, /q)	Exit the application
/clear	Clear conversation history
/thinking	Toggle thinking display
/scroll	Toggle auto-scroll
/org	Show current organization
/lsp	Show LSP server status
/status	Show system status
/credits	Show credit balance and usage
/approval	Show or set approval mode
/feedback	Open feedback form
/help-community	Open community help
/stickers	Get Seqera stickers

AI commands

These commands are sent to the AI backend for processing:

Command	Description
/help	Show available commands and skills
/status	Show current mode, LSP, organization, and session status
/sessions	Browse and switch sessions
/goal	Set, inspect, or disable a persistent goal
/credits	Show monthly credit balance and usage
/update	Check for CLI updates
/nextflow-config	Generate and explain Nextflow configuration files
/nextflow-schema	Generate nextflow_schema.json and sample sheet schema files
/debug	Run nextflow lint and preview
/debug-local-run	Debug a local Nextflow pipeline run
/debug-last-run-on-seqera	Debug the last Platform run
/migrate-from-wdl	Convert WDL to Nextflow
/convert-python-script	Convert Python script to Nextflow
/convert-r-script	Convert R script to Nextflow
/convert-jupyter-notebook	Convert Jupyter notebook to Nextflow
/write-nf-test	Write nf-tests for your pipeline

Skills exposed by your Seqera AI deployment also appear in the / command palette and in /help.

Work with skills

Seqera AI can use reusable skills from your current project, your user profile, and the backend skill catalog exposed by your deployment.

Using skills

Open the command palette:

• Type / to browse built-in commands and backend skills
• Run /help to see the same commands in a text list

Use a built-in backend skill:

Examples include:

• /fix-strict-syntax
• /nf-pipeline-structure
• /nf-run-history
• /nf-data-lineage
• /seqera-platform-api
• /seqerakit

Create a project skill:

Create a SKILL.md file in .agents/skills/ or .seqera/skills/ and restart seqera ai.

Install Seqera AI into coding agents:

seqera skill install

Work with data

Seqera AI helps you manage data through Platform data links and access reference datasets.

Working with data

Browse data links:

> List my data links

> Show me the contents of my S3 data link

Download and upload files:

> Generate a download URL for results/final_report.html

> Upload my local results to the data link

Access reference data:

> Find the human reference genome GRCh38

> Search for RNA-Seq test data

Work with local files

Seqera AI can interact with files in your current working directory.

Work with local files

Start the assistant from your project folder:

cd /path/to/your/project
seqera ai

Then, ask the assistant to help with local tasks:

> Show me the structure of main.nf

> Add a new process to handle quality control

note

Local file operations are controlled by approval modes. By default, the assistant will ask for your approval before making changes outside your working directory or running potentially dangerous commands.

Work with nf-core modules

Seqera AI provides access to over 1,000 nf-core modules for common bioinformatics tasks.

Working with nf-core modules

Search for modules:

> Find nf-core modules for sequence alignment

> What modules are available for variant calling?

Get module details:

> Show me how to use the nf-core/bwa/mem module

Run a module:

> Run FastQC on my FASTQ files

note

The assistant can generate the exact Nextflow command with proper parameters for your data.

Work with Seqera Platform

Use Seqera Platform capabilities to run and manage workflows at scale with AI assistance.

Working with Seqera Platform

List your workflows:

> List my recent workflows

Launch a pipeline:

> Launch the nf-core/rnaseq pipeline with the test profile

Debug failed runs:

> Why did my last workflow fail?

> Get the logs for the failed task in my last run

Headless mode

Run Seqera AI in headless mode for scripting and automation. Output is sent to stdout instead of the interactive TUI.

Headless mode

Run a query and pipe the output:

seqera ai --headless "list my pipelines"

Include thinking messages in the output:

seqera ai --headless --show-thinking "debug my pipeline"

Include tool calls in the output:

seqera ai --headless --show-tools "list my workflows"

note

Headless mode is also auto-detected when stdout is piped (e.g., seqera ai "query" | grep "result").

Session management

Seqera AI preserves your conversation history across sessions. You can resume previous sessions to continue your work.

Session management

Continue your most recent session:

seqera ai -c

Continue with a follow-up question:

seqera ai -c "now run the pipeline with the test profile"

Resume a specific session by ID:

seqera ai -s <session-id>

f7f424c5 (Update Seqera AI CLI docs: Python CLI to OpenTUI CLI)

Learn more

• Seqera AI CLI: Seqera AI CLI overview
• Installation: Detailed installation instructions
• Authentication: Log in, log out, and session management
• Skills: Discover, create, and install skills
• Modes: Work in build mode, plan mode, and goal mode
• Command approval: Control which commands run automatically
• Troubleshooting: Troubleshoot common errors