execution-pipeline

Name: execution-pipeline
Availability: InStock
Author: nteract

Traces notebook cell execution from MCP tool invocation through daemon and kernel to resolve failures.

158|12|Updated Feb 11, 2026

Search Tags:#debugging #mcp #pipeline #execution #notebook #daemon #runtime-state

Ready to run

npx skills add https://github.com/nteract/nteract --skill execution-pipeline

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: execution-pipeline
Source: https://github.com/nteract/nteract/tree/main/.agents/skills/execution-pipeline
Command: npx skills add https://github.com/nteract/nteract --skill execution-pipeline

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The execution-pipeline skill provides an end-to-end debugging workflow for notebook cell execution, tracing a MCP tool invocation through the daemon and kernel back to the notebook to identify where failures or delays occur.

Core Features & Use Cases

End-to-end tracing from MCP invocation to kernel results.
Diagnostics for timing gaps, missing outputs, and stale results.
Guidance for Run All Cells workflows and runtime state coordination.

Quick Start

Trace a failing cell execution end-to-end from MCP invocation through the daemon to the kernel and back.

Frequently Asked Questions about execution-pipeline

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

FAQPage Schema

How do I debug notebook cell execution failures from MCP invocation to the kernel?▼

Trace the end-to-end notebook execution pipeline from MCP tool invocation through the daemon and kernel to identify where cells fail to execute. This workflow pinpoints timing gaps, missing outputs, and required_heads gating issues causing run failures.

Why are my notebook outputs missing or delayed during a Run All Cells workflow?▼

Missing or delayed outputs during a Run All Cells workflow occur due to runtime state desynchronization or kernel lifecycle coordination issues. Tracing execution via RuntimeStateDoc polling resolves output manifests and detects stale results across the pipeline.

How does RuntimeStateDoc polling resolve inconsistent notebook execution results?▼

RuntimeStateDoc polling resolves inconsistent notebook execution results by continuously tracking runtime state across the daemon and kernel. This coordinates kernel lifecycle events and output resolution to correct stale outputs and synchronize execution flows.

Can I trace required_heads gating issues when notebook cells fail to execute?▼

Yes, you can trace required_heads gating issues when notebook cells fail to execute. The end-to-end execution pipeline diagnostics track these gating dependencies through the daemon to identify blocking conditions preventing cell execution.

What is the best way to diagnose timing gaps in end-to-end notebook execution?▼

The best way to diagnose timing gaps in end-to-end notebook execution is tracing the MCP invocation path through the daemon and kernel. This pipeline diagnostics approach detects delays, stale results, and missing output manifests.