deep-debug

jezweb/claude-skills · updated Apr 8, 2026

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$npx skills add https://github.com/jezweb/claude-skills --skill deep-debug
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summary

Status: Production Ready

  • Last Updated: 2026-02-03
  • Dependencies: Chrome MCP tools (optional), debugger agent, code-reviewer agent
skill.md

Deep Debug - Multi-Agent Investigation

Status: Production Ready Last Updated: 2026-02-03 Dependencies: Chrome MCP tools (optional), debugger agent, code-reviewer agent


When to Use

  • Going in circles - You've tried multiple fixes but nothing works
  • Browser + API interaction bugs - Need to see Network tab, console logs
  • Symptoms don't match expectations - Something deeper is wrong
  • Complex state management bugs - React hooks, closures, race conditions

Commands

Command Purpose
/debug Guided debugging workflow with evidence gathering and parallel investigation

Quick Start

/debug [description of the bug]

Or invoke naturally:

  • "I'm stuck on this bug, can you do a deep investigation?"
  • "This bug is resisting normal debugging"
  • "I need you to really dig into this"

The Process

Phase 1: Gather Evidence (Before Hypothesizing)

For browser-related bugs, use Chrome MCP tools:

// Get network requests (look for duplicates, failures, timing)
mcp__claude-in-chrome__read_network_requests

// Get console logs (errors, warnings, debug output)
mcp__claude-in-chrome__read_console_messages

// Get page state
mcp__claude-in-chrome__read_page

For backend bugs, gather:

  • Error logs and stack traces
  • Request/response payloads
  • Database query logs
  • Timing information

Phase 2: Launch Parallel Investigation (3 Agents)

Launch these agents simultaneously with the gathered evidence:

Agent 1: Execution Tracer (debugger)

Task(subagent_type="debugger", prompt="""
EVIDENCE: [paste network/console evidence]

Trace the execution path that leads to this bug. Find:
1. Where the bug originates
2. What triggers it
3. The exact line/function causing the issue

Focus on TRACING, not guessing.
""")

Agent 2: Pattern Analyzer (code-reviewer)

Task(subagent_type="code-reviewer", prompt="""
EVIDENCE: [paste evidence]

Review the relevant code for common bug patterns:
- React useCallback/useMemo dependency issues
- Stale closures
- Race conditions
- State update ordering
- Missing error handling

Find patterns that EXPLAIN the evidence.
""")

Agent 3: Entry Point Mapper (Explore)

Task(subagent_type="Explore", prompt="""
EVIDENCE: [paste evidence]

Map all entry points that could trigger this behavior:
- All places [function] is called
- All event handlers involved
- All state updates that affect this

Find if something is being called MULTIPLE TIMES or from UNEXPECTED places.
""")

Phase 3: Cross-Reference Findings

After agents complete, look for:

Signal Meaning
All 3 agree on root cause High confidence - fix it
2 agree, 1 different Investigate the difference
All 3 different Need more evidence

Phase 4: Verify Fix

After implementing the fix, re-gather the same evidence to confirm:

  • Network tab shows expected behavior
  • Console has no errors
  • State updates correctly

Real Example: Duplicate API Calls Bug

Evidence Gathered

Network tab showed 2 fetch requests for the same message.

Parallel Investigation Results

Agent Finding
debugger state.messages in useCallback deps causes callback recreation
code-reviewer Same finding + explained React pattern causing it
Explore Verified UI layer wasn't double-calling (ruled out)

Root Cause (Consensus)

sendMessage useCallback had state.messages in dependency array. Every state update recreated the callback, causing duplicate calls during React re-renders.

Fix

Use stateRef to access current state without including in dependencies:

const stateRef = useRef(state);
stateRef.current = state;

const sendMessage = useCallback(async (text) => {
  // Use stateRef.current instead of state
  const messages = stateRef.current.messages;
  // ...
}, [/* state.messages removed */]);

Common Bug Patterns This Catches

React Hook Issues

  • state in useCallback dependencies causing recreation
  • Missing dependencies causing stale closures
  • useEffect running multiple times

API/Network Issues

  • Duplicate requests (visible in Network tab)
  • Race conditions between requests
  • CORS failures
  • Timeout handling

State Management Issues

  • State updates not batching correctly
  • Optimistic updates conflicting with server response
  • Multiple sources of truth

Chrome Tools Quick Reference

Tool Use For
read_network_requests See all fetch/XHR calls, duplicates, failures
read_console_messages Errors, warnings, debug logs
read_page Current DOM state
javascript_tool Execute debug code in page context

Tips for Success

  1. Evidence first, hypotheses second - Don't guess until you have concrete data
  2. Network tab is gold - Most frontend bugs show symptoms there
  3. Parallel agents save time - 3 perspectives at once vs sequential guessing
  4. Cross-reference findings - Agreement = confidence
  5. Verify with same evidence - Confirm fix with same tools that found bug
how to use deep-debug

How to use deep-debug on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add deep-debug
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/jezweb/claude-skills --skill deep-debug

The skills CLI fetches deep-debug from GitHub repository jezweb/claude-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/deep-debug

Reload or restart Cursor to activate deep-debug. Access the skill through slash commands (e.g., /deep-debug) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.529 reviews
  • Daniel Haddad· Dec 20, 2024

    deep-debug reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Dev Brown· Dec 8, 2024

    deep-debug is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Dev Shah· Nov 27, 2024

    Keeps context tight: deep-debug is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Nia Desai· Nov 11, 2024

    We added deep-debug from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Nikhil Dixit· Oct 18, 2024

    We added deep-debug from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Anaya Flores· Oct 2, 2024

    Keeps context tight: deep-debug is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Oshnikdeep· Sep 21, 2024

    Useful defaults in deep-debug — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Anika Li· Sep 9, 2024

    deep-debug has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Nia Agarwal· Aug 28, 2024

    deep-debug fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ganesh Mohane· Aug 12, 2024

    Registry listing for deep-debug matched our evaluation — installs cleanly and behaves as described in the markdown.

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