Run Pipeline

Execute a DAG-based data analysis pipeline to generate a validated slide deck.

289|137|Updated Feb 19, 2026
One-click install
npx skills add https://github.com/ai-analyst-lab/ai-analyst --skill run-pipeline-ai-analyst-lab
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Run Pipeline
Source: https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/run-pipeline
Command: npx skills add https://github.com/ai-analyst-lab/ai-analyst --skill run-pipeline-ai-analyst-lab

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

End-to-end data analyses are complex to orchestrate. This Skill provides a DAG-based execution engine that coordinates multiple agents to transform raw data into a validated, stakeholder-ready slide deck.

Core Features & Use Cases

  • DAG-based execution with automatic dependency resolution and parallelism
  • Plan pruning, dry-run mode, and resume-from-failure for robust workflows
  • Generates narrative slides with speaker notes and exports to deck formats

Quick Start

Invoke the pipeline with /run-pipeline data_path=PATH question="Your business question" to run end-to-end analysis and generate the deck.

Frequently Asked Questions about Run Pipeline

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate end-to-end data analysis and generate a stakeholder deck?▼

You can automate end-to-end data analysis by invoking a DAG-based execution pipeline with your data path and business question. The pipeline coordinates multiple agents to explore data, identify root causes, and generate a narrative slide deck for stakeholders.

What is DAG-based execution for data analytics workflows?▼

DAG-based execution is an orchestration mechanism that maps analysis tasks to a directed acyclic graph. It enables automatic dependency resolution, parallel execution, and plan pruning to transform raw data into validated narrative slide decks efficiently.

How do I run a data analysis pipeline with dry-run mode and resume-from-failure?▼

To run a data analysis pipeline with dry-run mode and resume-from-failure, invoke the pipeline command with your data path and business question. The DAG-based engine automatically handles plan pruning, parallel execution, and workflow recovery from interruptions.

Can I generate narrative slides with speaker notes from raw data automatically?▼

Yes, you can generate narrative slides with speaker notes from raw data automatically. The pipeline processes your data exploration and root cause analysis, then formats the narrative output into ready-to-deliver slide decks with integrated speaker notes.

Does the pipeline orchestration support parallel execution and automatic dependency resolution?▼

Yes, pipeline orchestration supports parallel execution and automatic dependency resolution through its DAG-based engine. This architecture allows multiple analysis agents to run concurrently while automatically resolving task dependencies to produce the final stakeholder deck.