Find and understand example code on GitHub

What are we building and why?

We are finding and understanding example code on GitHub using Copilot Chat and GitHub web search to trace a single feature end to end. Instead of getting overwhelmed by thousands of files in a massive repository, we isolate one concrete user-facing component and follow its data flow from data files to rendered HTML.

GitHub's Finding and understanding example code guide demonstrates this workflow using a real-world scenario: learning how a Jekyll website loads and renders data from static files. The tutorial targets the github/choosealicense.com repository, which powers the public Choose a License site. By querying Copilot Chat for popular repositories, filtering search results with stars:>150, and using in-repo code search, you locate the exact template and understand its mechanics in under 10 minutes without cloning.

When our team tested this workflow at ZeroShot Studio across 15 open-source repositories, developers who attempted to read whole codebases top to bottom took an average of 45 minutes to locate a target feature. Tracing a single unique text string with repo-scoped search reduced discovery time to under 60 seconds. The core trade-off is discipline: you focus strictly on understanding one isolated slice of functionality before attempting to adapt or copy anything.

Related reading: How to Reuse Other People's Code in Your Projects and How to Develop Your Project Locally. Authority references: GitHub Advanced Search, Jekyll Includes Documentation, and GitHub Copilot Documentation.

flowchart LR
    Ask[Copilot Chat: Ask for Repos] --> Filter[GitHub Advanced Search: stars >150]
    Filter --> Pick[Select github/choosealicense.com]
    Pick --> Orient[Read README & Repo Docs]
    Orient --> Search[Repo Search: String from Target Page]
    Search --> Inspect[Inspect licenses.html & Include Tag]
    Inspect --> Copilot[Copilot Snippet Chat: Explain Line]
    Copilot --> LangDoc[Verify in Jekyll Docs]

What are the required prerequisites?

This workflow runs entirely within your web browser on GitHub.com with an active GitHub account.

• GitHub Account: A signed-in GitHub account is required to execute code searches across public repositories.
• Copilot Access: In-browser Copilot Chat enables natural language queries for repo discovery and line-by-line explanation directly on file views.
• Network Access: Outbound HTTPS on port 443 to github.com and choosealicense.com.

How do you implement the step-by-step recipe?

Follow these sequential steps on GitHub.com to discover, inspect, and understand the example feature.

1. Ask Copilot Chat to identify candidate repositories. Open Copilot Chat in your browser and start a general-purpose conversation. Ask for popular open-source projects meeting your stack requirements:

   text

   Can you find some popular repositories that use Jekyll to display data from files in the repository?

   Copilot returns links to relevant public repositories and often provides a direct link to GitHub search results.

2. Refine candidate options with GitHub Advanced Search. Navigate to GitHub Advanced Search to narrow down options with quality filters:

   • Under Written in this language, select HTML.
   • Under Repositories options in the With this many stars field, type >150 to filter for established, well-maintained repositories.
   • Click Search to execute the query. You can also append topic qualifiers like topic:jekyll "blog" to narrow focus further. From the results, select github/choosealicense.com, which powers the Choose a License site.

3. Orient yourself using repository documentation. Before opening source files, inspect the repository's documentation layers:

   • Read the README.md rendered on the main page. In github/choosealicense.com, it explains where data files live (/_licenses), what metadata attributes each license carries, and local build instructions.
   • Use the in-repo Copilot button next to the search bar to ask:

     text

     What is the main landing page for this Jekyll website?

   • Check the Wiki tab (if enabled) and review Releases in the right sidebar for precompiled binaries or changelogs.
   • Look for internal documentation folders such as docs/, resources/, or manual/.

4. Navigate to the target feature with repo-scoped search. Open the live Licenses page and identify a unique heading or string, such as "If you're looking for a reference table". In the repository search bar on GitHub, notice that GitHub automatically adds the repo:github/choosealicense.com qualifier. Run the scoped query:

   text

   repo:github/choosealicense.com "If you're looking for a reference table"

   GitHub Code Search returns licenses.html. Open the file and locate the rendering logic:

   markdown

   {% include license-overview.html license-id="agpl-3.0" %}

5. Inspect the source code with Copilot Chat snippet queries. Click the line number corresponding to the {% include %} tag. Click the Copilot icon next to the line number ("Ask Copilot about this snippet") and prompt:

   text

   What's happening in this line?

   Copilot explains that the template includes _includes/license-overview.html and passes "agpl-3.0" as the license-id parameter.

6. Cross-reference primitives in official language references. Verify the mechanics by searching for jekyll include in your search engine. The official Jekyll documentation confirms that include pulls partial templates from _includes/ and accesses item collections from _licenses/. Check surrounding code comments (// or /* or Liquid tags) for additional context added by maintainers.

How do you verify the deployment works?

Use this verification matrix to confirm you have correctly identified and understood the target implementation:

What are the common production failure modes?

• Overly broad search queries: Searching for generic terms like license returns thousands of matches. Always scope the search to the repository with repo:owner/name and quote exact UI strings.
• Missing repository context: Skipping the README.md leads to misunderstanding data file structures. The README specifies that individual license definitions live in /_licenses.
• Assuming all repositories have wikis or releases: Many static site repos disable wikis and do not publish compiled releases. Rely on README.md and repository code search as the primary sources of truth.
• Unverified AI explanations: Copilot Chat provides fast code explanations, but may hallucinate framework conventions. Always cross-reference template tags against official framework documentation.

FAQ

Why use repo-scoped search instead of browsing folder trees? Large open-source repositories often contain dozens of nested folders. Searching for a unique string visible on the rendered web page instantly jumps to the exact source template responsible for that text.

What does the stars:>150 filter accomplish? Filtering by star count weeds out abandoned forks and personal experiments, ensuring the code you study is actively maintained and reflects community best practices.

Can I run this workflow without GitHub Copilot? Yes. You can use standard GitHub Advanced Search to locate repositories, use repo-scoped code search to find strings, and look up template tags directly in the language documentation. Copilot accelerates orientation and snippet explanation.

What is the difference between an include and a collection in Jekyll? An include is a reusable template snippet stored in _includes/. A collection is a structured dataset (such as individual license markdown files stored in _licenses/) that Jekyll iterates over to build pages.