<objective> Perform comprehensive code research by intelligently selecting from built-in tools, lightweight scripts, and MCP servers. The skill prioritizes context-efficient approaches—using the simplest tool that gets the job done before escalating to heavier solutions. </objective>

<quick_start> Before any Bash command that uses ${AGENT_ROOT}, run:

source ./scripts/agent-env.sh

This resolves AGENT_ROOT to ./.agents in the current working directory.

When researching code, follow the tool escalation ladder:

1. Local first - Use Grep/Glob/Read for codebase exploration
2. Terminal research - Use fast CLI tools (w3m/lynx, curl, jq, rg, fd, gh) and DDG bangs
3. Built-in web - Use WebSearch/WebFetch for documentation and articles
4. Skills & Scripts - Use gh-cli skill for GitHub, scripts for Stack Overflow
5. MCP servers - Use Exa/Deepwiki/Chrome for complex research needs

Start simple. Escalate only when simpler tools fail. </quick_start>

<tool_hierarchy> <tier name="1" label="Built-in Tools (Use First)"> Local codebase exploration:

• Grep - Search for patterns, function names, error messages in code
• Glob - Find files by pattern (e.g., **/*.ts, **/config.*)
• Read - Read specific files once you know what to look at
• Task with subagent_type=Explore - For open-ended codebase exploration

Web research:

• WebSearch - General web search for docs, tutorials, discussions
• WebFetch - Fetch and analyze specific URLs (works for most static sites)

When to use: Always start here. These tools are fast, low-cost, and handle 80% of research tasks. </tier>

<tier name="1.5" label="Terminal Research (CLI)"> **Prefer Rust utils when available (speed/ergonomics):** - `rg` (ripgrep), `fd`, `bat`, `sd`, `xsv`, `hyperfine`

Fallback to POSIX tools:

• grep, find, sed, awk, cut, sort, uniq

Terminal web/doc workflows:

• w3m / lynx for fast doc browsing
• DuckDuckGo bangs (!gh, !so, !npm, !pypi) to jump directly to sources
• curl + jq + rg for structured data and targeted extraction
• pup/htmlq/python -m bs4 for HTML parsing when needed
• readability-lxml (or python -m readability) to clean article content
• csvkit / xsv for CSV docs and tables
• fzf to interactively select snippets and URLs
• Clipboard handoff: pbcopy (macOS) / xclip -selection clipboard (Linux)

Rate-limit hygiene:

• curl --retry 3 --retry-delay 2 --compressed + backoff (sleep)
• Use ETag/If-Modified-Since to avoid refetching unchanged docs

When to use: Quick web/CLI research before WebSearch, or when you need high-throughput data extraction. </tier>

<tier name="2" label="Lightweight Scripts & Skills (CLI Access)"> **GitHub CLI (`gh`)** - Use the `gh-cli` skill for comprehensive GitHub operations: - Repository info, issues, PRs, code search, Actions, releases, and more - Invoke with: `Skill: gh-cli`

stackoverflow-api.sh - Find solutions to errors

# Search Stack Overflow for solutions
${AGENT_ROOT}/skills/code-research/scripts/stackoverflow-api.sh "error message or question"

When to use: When you need structured GitHub data (issues, PRs, code across repos) that WebSearch can't provide cleanly. </tier>

<tier name="3" label="MCP Servers (Heavy Artillery)"> **Exa MCP** - Semantic web search with AI understanding - Use for: Finding related libraries, discovering best practices, semantic similarity search - Better than WebSearch when you need conceptual matches, not keyword matches

Deepwiki MCP - Documentation and wiki content

• Use for: Library documentation, API references, technical wikis
• Better than WebFetch for structured documentation extraction

Chrome Web Tools MCP - Headless browser automation

• Use for: JavaScript-heavy sites, sites requiring authentication, dynamic content
• Example: Navigating https://codewiki.google/github.com/anomalyco/opencode

When to use: When simpler tools fail—JS-rendered content, semantic search needs, or complex documentation sites. </tier> </tool_hierarchy>

<research_workflow> <step name="1" label="Understand the Query"> Classify the research type:

• Codebase understanding - How does this code work? What's the architecture?
• Library/API research - How do I use this library? What are the patterns?
• Bug investigation - Why is this error happening? How do others solve it?
• Pattern discovery - How do other projects implement X? </step>

<step name="2" label="Start Local"> For any codebase question, explore locally first: ``` # Find relevant files Glob: **/*{keyword}*.{ts,py,go}

Search for patterns

Grep: "functionName|className|errorMessage"

Deep exploration

Task(subagent_type=Explore): "Find how authentication is implemented"

</step>

<step name="2.5" label="Terminal Research">
Use fast terminal tools to browse docs and extract data:

Quick doc browsing

w3m https://docs.example.com/guide

DDG bangs

WebSearch: "!gh repo:org/project authentication middleware"

Fast extraction

curl -s https://docs.example.com/api | rg -n "endpoint" | sed -n '1,120p'

Structured GitHub data via gh

gh repo view org/repo --json description --jq '.description'

Clean article text

curl -s https://blog.example.com/post | python -m readability | rg -n "API" | sed -n '1,80p'

CSV extraction

curl -s https://docs.example.com/table.csv | xsv select 1,3 | xsv table | sed -n '1,40p'

Interactive selection

curl -s https://docs.example.com/api | rg -n "endpoint" | fzf

Clipboard handoff

curl -s https://docs.example.com/api | pbcopy # or: xclip -selection clipboard

Prefer Rust utilities when available (rg/fd/bat/sd/xsv); fall back to standard Unix tools otherwise.
</step>

<step name="3" label="Expand to Web">
If local exploration isn't enough:

General search

WebSearch: "library-name how to implement X"

Fetch specific docs

WebFetch: "https://docs.library.com/guide"

</step>

<step name="4" label="Use Skills & Scripts for Structured Data">
When you need GitHub/StackOverflow data:

GitHub operations - invoke the gh-cli skill

Skill: gh-cli

Then use gh directly, e.g.:

gh issue list -R facebook/react --search "useEffect cleanup" gh search code "useEffect cleanup" --repo facebook/react

```bash
# Find error solutions
${AGENT_ROOT}/skills/code-research/scripts/stackoverflow-api.sh "React useEffect memory leak"

</step> <step name="5" label="Escalate to MCP When Needed"> For complex research needs: ``` # Semantic search (Exa) mcp__web_search_exa: "best practices for React state management 2024" mcp__get_code_context_exa: "langgraph deepagent cli" mcp__crawling_exa: "https://codewiki.google/github.com/anomalyco/opencode"

Documentation extraction (Deepwiki)

mcp__deepwiki__read_wiki_contents: "react/react" mcp__deepwiki__read_wiki_structure: "anomalyco/opencode" mcp__deepwiki__ask_question: "What are the context engineering strategies used by anomalyco/opencode?"

Website Navigation

Use chrome-devtools-mcp to open up webpages and crawl through them for deeper information extraction tasks.

</step>

<step name="6" label="Save High-Value Sources to Readwise">
When a source is highly relevant (authoritative docs, key blog posts, insightful discussions), persist it for future retrieval:
```bash
# Save a URL to Reader with research tags
readwise reader-create-document --url "https://..." --tags "code-research,<topic>"

# Create a highlight for a key finding or quote
readwise readwise-create-highlights --highlights '[{"text": "key finding text", "title": "Source Title", "source_url": "https://...", "note": "Why this matters"}]'

Only save sources scoring 2-3 on relevance (directly answers the question or provides strong supporting context). Do not save noise. </step>

<step name="7" label="Synthesize Findings"> Combine findings from all sources: - Cross-reference information across sources - Identify consensus patterns vs. edge cases - Note version-specific information (library versions matter!) - Cite sources when presenting findings </step> </research_workflow>

<output_formats> Adapt output to the query:

Quick answer - For simple questions, respond inline with sources Structured summary - For broader research:

## Findings
- Key finding 1
- Key finding 2

## Recommendations
- Recommended approach with rationale

## Sources
- [Source 1](url)
- [Source 2](url)

Research report - For deep dives, create a markdown file:

Write: research-{topic}-{date}.md

</output_formats>

<tool_selection_heuristics>

Situation	Tool Choice
"How does X work in this codebase?"	Grep → Read → Task/Explore
"What's the best library for X?"	WebSearch → Exa MCP
"How do I use library X?"	WebFetch (docs URL) → Deepwiki MCP
"Why am I getting error X?"	Grep (local) → stackoverflow-api.sh → WebSearch
"How do other projects do X?"	gh-cli skill → gh search
"Show me the docs for X"	WebFetch → Deepwiki → Chrome MCP
"Quickly skim docs"	w3m/lynx → curl + rg/sed
"Find issues related to X"	gh-cli skill → gh issue/search
"Search code for pattern X"	rg (local) → Exa MCP
"Need fast CLI search"	rg/fd/bat (fallback: grep/find/cat)
"Navigate to JS-heavy site"	Chrome MCP (browser_navigate + browser_snapshot)
</tool_selection_heuristics>

<anti_patterns> <pitfall name="mcp_first"> Don't reach for MCP servers immediately. Try built-in tools and scripts first—they're faster and use less context. </pitfall>

<pitfall name="ignoring_local"> Don't skip local codebase exploration. The answer might already be in the code you're working with. </pitfall> <pitfall name="single_source"> Don't rely on one source. Cross-reference findings from multiple tools for accuracy. </pitfall> <pitfall name="no_version_check"> Don't ignore version information. Library APIs change—verify findings match the version in use. </pitfall> <pitfall name="rate_limit_hygiene"> Don't spam endpoints with aggressive scraping. Use retries, backoff, and caching headers to avoid rate limits. </pitfall> </anti_patterns>

<success_criteria> Research is complete when:

• Query is fully answered with supporting evidence
• Multiple sources consulted when appropriate
• Tool selection followed the escalation ladder (simplest first)
• Findings are synthesized, not just listed
• Sources are cited for traceability
• Output format matches query complexity </success_criteria>