dv-debug

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Debug systematically with root cause analysis before fixes. Use when the user types `$dv-debug` or when data preparation, visualization, publish, deployment, test, runtime, or workflow behavior fails and root cause must be proven before fixing.

young-lillo By young-lillo schedule Updated 4/19/2026

name: dv-debug description: Debug systematically with root cause analysis before fixes. Use when the user types $dv-debug or when data preparation, visualization, publish, deployment, test, runtime, or workflow behavior fails and root cause must be proven before fixing. languages: all argument-hint: "[error or issue description]" metadata: author: data-visualization-kit version: "5.0.0"

DV Debug

Treat $dv-debug as the canonical debug entrypoint and the canonical debug methodology for Data Visualization Kit.

Codex Adaptation

  • Use this skill directly for $dv-debug instead of delegating to a separate debug workflow or prompt layer.
  • Keep debug outputs aligned with Data Visualization Kit runtime rules and project docs/ boundaries.
  • Record root cause, evidence, fix path, and unresolved questions in the active project debug report under projects/<slug>/docs/debug-report.md when the task is project-scoped.
  • Route back to the owning workflow after the failure is understood and the next safe action is clear.

Comprehensive framework combining systematic debugging, root cause tracing, defense-in-depth validation, verification protocols, and system-level investigation across workflow runtime, generated outputs, logs, CI/CD, databases, and performance.

Core Principle

NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST

Random fixes waste time and create new bugs. Find root cause, fix at source, validate at every layer, verify before claiming success.

When to Use

Workflow-level: Data preparation, visualization, publish, runtime, hook, or generated-output failures
Code-level: Test failures, bugs, unexpected behavior, build failures, integration problems
System-level: Server errors, CI/CD pipeline failures, performance degradation, database issues, log analysis
Always: Before claiming work complete after a failure

Techniques

1. Systematic Debugging (references/systematic-debugging.md)

Four-phase framework: Root Cause Investigation -> Pattern Analysis -> Hypothesis Testing -> Implementation. Complete each phase before proceeding. No fixes without Phase 1.

Load when: Any bug or issue requiring investigation and fix

2. Root Cause Tracing (references/root-cause-tracing.md)

Trace bugs backward through call stack to find original trigger. Fix at source, not symptom. Includes scripts/find-polluter.sh for bisecting test pollution.

Load when: Error deep in stack, unclear where invalid data originated

3. Defense-in-Depth (references/defense-in-depth.md)

Validate at every layer: entry validation -> business logic -> environment guards -> debug instrumentation.

Load when: After finding root cause, need comprehensive validation

4. Verification (references/verification.md)

Iron law: NO COMPLETION CLAIMS WITHOUT FRESH VERIFICATION EVIDENCE. Run command. Read output. Then claim result.

Load when: About to claim work complete, fixed, or passing

5. Investigation Methodology (references/investigation-methodology.md)

Five-step structured investigation for system-level issues: Initial Assessment -> Data Collection -> Analysis -> Root Cause ID -> Solution Development.

Load when: Server incidents, system behavior analysis, workflow failures, multi-component failures

6. Log & CI/CD Analysis (references/log-and-ci-analysis.md)

Collect and analyze logs from servers, CI/CD pipelines, and application layers. Tools: gh CLI, structured log queries, correlation across sources.

Load when: CI/CD pipeline failures, server errors, deployment issues

7. Performance Diagnostics (references/performance-diagnostics.md)

Identify bottlenecks, analyze query performance, and develop optimization strategies. Covers database queries, API response times, and resource utilization.

Load when: Performance degradation, slow queries, high latency, resource exhaustion

8. Reporting Standards (references/reporting-standards.md)

Structured diagnostic reports: Executive Summary -> Technical Analysis -> Recommendations -> Evidence.

Load when: Need to produce investigation report or diagnostic summary

9. Task Management (references/task-management-debugging.md)

Track investigation pipelines via plan files plus update_plan. Default to markdown plans and concise runtime progress tracking.

Load when: Multi-component investigation, parallel log collection, coordinating debugger subagents

10. Frontend Verification (references/frontend-verification.md)

Visual verification of frontend implementations via Chrome MCP or chrome-devtools skill fallback. Detect if frontend-related -> check Chrome MCP availability -> screenshot + console error check -> report. Skip if not frontend.

Load when: The failure touches frontend files, UI bugs, or visual regressions

Quick Reference

Workflow failure -> investigation-methodology.md
  Hook/runtime issue -> inspect scripts/hooks/ and generated docs
  Generated output issue -> compare expected docs contract vs actual files

Code bug        -> systematic-debugging.md
  Deep in stack -> root-cause-tracing.md
  Found cause   -> defense-in-depth.md
  Claiming done -> verification.md

System issue    -> investigation-methodology.md
  CI/CD failure -> log-and-ci-analysis.md
  Slow system   -> performance-diagnostics.md
  Need report   -> reporting-standards.md

Frontend fix    -> frontend-verification.md

Tools Integration

  • Database: psql for PostgreSQL queries and diagnostics
  • CI/CD: gh CLI for GitHub Actions logs and pipeline debugging
  • Codebase: docs-seeker skill for package/plugin docs; repomix skill for codebase summary
  • Scouting: scout for finding relevant files
  • Frontend: Chrome browser or chrome-devtools skill for visual verification
  • Skills: Activate problem-solving when stuck on complex issues

Project Output Rules

  • Keep debug records under the active project docs/ tree
  • Prefer projects/<slug>/docs/debug-report.md for project-scoped failures
  • When the issue belongs to one owner workflow, state clearly which workflow should resume next
  • If the issue is runtime-wide, separate root cause from downstream symptom files

Red Flags

Stop and follow process if thinking:

  • "Quick fix for now, investigate later"
  • "Just try changing X and see if it works"
  • "It's probably X, let me fix that"
  • "Should work now" or "Seems fixed"
  • "Tests pass, we're done"

All mean: Return to systematic process.

Install via CLI
npx skills add https://github.com/young-lillo/data-visualization-skills --skill dv-debug
Repository Details
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