mcpField
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deep-research

deep-research

github.com/pedronauckDevelopment64437 installsUpdated 1w ago
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About deep-research

deep-research is a skill for systematically investigating a codebase and external dependencies before complex implementation work. It directs developers through local and external research, Pal analysis, and synthesis into a structured report.

Key features

  1. 01Mandatory local codebase search
  2. 02External code search with Sourcebot
  3. 03Context7 and Perplexity research
  4. 04Architecture analysis with Pal MCP tools
  5. 05Structured research report output

Use cases

  1. 01Map a codebase before complex changes
  2. 02Investigate external library usage and documentation
  3. 03Assess architecture, quality, security, and technical debt
  4. 04Synthesize findings into implementation recommendations

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/pedronauck/skills --skill deep-research

After installing, type/deep-researchin Claude Code to confirm it loaded.

Details

From the project README

Deep Research

This skill provides a systematic approach to researching and analyzing the codebase and external dependencies. It is designed to be used before starting complex implementation tasks.

<critical_tools> You MUST strictly follow the rules defined in the project's command guides.

  1. Local Code Discovery

    • REQUIRED SUB-SKILL: Use codebase_search for local code discovery.
    • MANDATORY: Use codebase_search for local code discovery.
  2. Sourcebot (External Search)

    • Reference: .claude/commands/sourcebot.md
    • MANDATORY: Use Sourcebot (5-7 times) for EXTERNAL libraries/frameworks only.
    • NEVER use it for local code.
    • Workflow: list_repos -> Identify ID -> search_code with filterByRepoIds.
  3. Pal MCP Toolkit (Architecture Analysis)

    • Reference: .claude/commands/pal.md (unified Pal skill)
    • MANDATORY: Use pal skill and appropriate Pal MCP tools before complex tasks.
    • Available Tools: mcp__zen__analyze, mcp__zen__debug, mcp__zen__planner, mcp__zen__refactor, mcp__zen__codereview, mcp__zen__tracer
    • Scope: Architecture, Quality, Performance, Security, Tech Debt.
    • CRITICAL ENFORCEMENT:
      • YOU MUST ALWAYS complete ALL THE STEPS when using any Pal MCP tool.
      • NEVER stop in the middle of the steps.
      • If you don't complete the steps until next_step_required: false, YOUR TASK WILL BE INVALIDATED.
      • NO EXCEPTIONS.
    • MODEL REQUIREMENT:
      • MANDATORY: Always use model: "anthropic/claude-opus-4.6" for ALL Pal MCP tool calls.
      • NEVER use any other model when calling Pal MCP tools.
  4. Context7 & Perplexity (External Knowledge)

    • Reference: .claude/commands/perplexity.md
    • Context7: Use for 3rd party libraries NOT in Sourcebot. Resolve ID -> Get Docs.
    • Perplexity: Use for ANY broad research, latest docs, or debugging. </critical_tools>

<research_strategy> MANDATORY: You MUST use your tools for EVERY research task. NO EXCEPTIONS.

  1. Understand the Request: Identify the specific task, goal, or question.
  2. Internal Discovery:
    • REQUIRED SUB-SKILL: Use codebase_search for local code discovery.
    • Search for relevant local code concepts, patterns, and files using natural language.
    • Identify existing architectural patterns.
    • Use codebase_search to search specific areas.
  3. External Research (Sourcebot):
    • If the task involves external libraries, search for their usage patterns and docs using Sourcebot.
  4. External Knowledge (Context7 & Perplexity):
    • Use Context7 for libraries not in Sourcebot.
    • Use Perplexity for broad research or debugging.
  5. Deep Analysis (Pal Analyze):
    • Run the zen_analyze tool to get a comprehensive view of the architecture, risks, and quality.
    • Complete the analysis loop.
  6. Synthesize: Combine findings from all sources into the final report. </research_strategy>

<quality_standards>

  • MANDATORY: Use tools extensively before answering.
  • Conciseness: Keep summaries high-signal and low-noise.
  • Authoritative: Prioritize findings from the codebase and official documentation (via Sourcebot/Context7).
  • No Hallucinations: NEVER include information not found via tools.
  • Direct Output: Do NOT create files. Return the report directly in the chat. </quality_standards>

<output_format> Return a SINGLE comprehensive message with the following structure:

Deep Analysis Report: [Topic]

1. Context Summary

[Concise summary of what was found in the local codebase, including key files and architectural patterns]

2. External Insights

[Relevant patterns, best practices, or documentation found for external libraries]

3. Deep Analysis Findings

[Insights on Architecture, Security, Performance, and Tech Debt derived from Pal Analyze]

4. Implementation Plan / Recommendations

[Concrete next steps, solution design, or answer to the user's request]

5. Relevant Files

[List of absolute paths to the most important files discovered during research] </output_format>

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