gsd-debug

Orchestrate persistent debugging investigations with session checkpoints and isolated subagents.

Updated Aug 15, 2025
One-click install
npx skills add https://github.com/gesmith0606/nfl_data_engineering --skill gsd-debug-gesmith0606
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gsd-debug
Source: https://github.com/gesmith0606/nfl_data_engineering/tree/main/.claude/skills/gsd-debug
Command: npx skills add https://github.com/gesmith0606/nfl_data_engineering --skill gsd-debug-gesmith0606

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a structured, persistent debugging workflow that preserves investigation state across context resets so long-running diagnoses do not lose progress or context. It reduces repetitive symptom gathering and context loss when investigations require spawning fresh, high-context subagents for deep analysis.

Core Features & Use Cases

  • Orchestrator workflow that checks for active sessions, gathers symptoms interactively, and either resumes or starts new investigations.
  • Spawns isolated gsd-debugger subagents with a fresh large-context model to perform diagnosis and fixes while preserving the main interaction thread.
  • Checkpoint and continuation handling: supports human verification checkpoints, continuation agents, and session files stored under .planning/debug/*.md for reproducibility and audit.
  • Use Case: A developer reports intermittent production errors; the skill collects expected vs actual behavior, error messages and reproduction steps, then spawns a gsd-debugger agent to find and propose fixes while tracking evidence and checkpoints.

Quick Start

Start a new investigation by telling the skill the issue in one sentence, for example: Investigate a pipeline job failing with a timeout and provide recent error output.

Frequently Asked Questions about gsd-debug

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

FAQPage Schema
How do I debug persistent runtime errors without losing context across session resets?▼

Debug persistent runtime errors by orchestrating isolated subagents and storing session state in .planning/debug/*.md files, ensuring investigation progress and context survive context resets for continuous root cause analysis.

What is the best way to diagnose intermittent production errors with structured debugging?▼

Diagnose intermittent production errors by interactively gathering expected versus actual behavior and reproduction steps, then spawning a fresh high-context subagent to perform root cause analysis while tracking evidence and checkpoints.

Can I resume a debugging investigation after stopping and starting a new context window?▼

Resume debugging investigations by checking for active session files stored under .planning/debug/*.md, which allow the orchestrator workflow to continue the diagnosis with a fresh large-context model without losing prior progress.

How do I automate root cause analysis for complex incidents requiring deep investigation?▼

Automate root cause analysis by spawning isolated gsd-debugger subagents with fresh large-context models that perform diagnosis and propose fixes while preserving the main interaction thread and maintaining human verification checkpoints.

Does this debugging workflow support interactive symptom gathering from operators?▼

The debugging workflow supports interactive symptom gathering by using AskUserQuestion to collect error messages, reproduction steps, and expected versus actual behavior before spawning subagents for deep analysis.

When should I use persistent stateful debugging instead of standard debugging approaches?▼

Use persistent stateful debugging when long-running diagnoses risk losing progress to context resets, when repetitive symptom gathering becomes inefficient, or when deep analysis requires fresh high-context subagents for isolated investigation.