best-practices-for-using-github-copilot.md

title	Best practices for using GitHub Copilot
intro	Learn how to get the most out of {% data variables.product.prodname_copilot_short %}.
topics	Copilot
versions	feature copilot
shortTitle	Best practices

Understand {% data variables.product.prodname_copilot_short %}'s strengths and weaknesses

{% data variables.product.prodname_copilot %} is an AI coding assistant that helps you write code faster and with less effort, allowing you to focus more energy on problem solving and collaboration. Before you start working with {% data variables.product.prodname_copilot_short %}, it's important to understand when you should and shouldn't use it.

Some of the things {% data variables.product.prodname_copilot_short %} does best include:

• Writing tests and repetitive code
• Debugging and correcting syntax
• Explaining and commenting code
• Generating regular expressions

{% data variables.product.prodname_copilot_short %} is not designed to:

• Respond to prompts unrelated to coding and technology
• Replace your expertise and skills. Remember that you are in charge, and {% data variables.product.prodname_copilot_short %} is a powerful tool at your service.

Choose the right {% data variables.product.prodname_copilot_short %} tool for the job

While {% data variables.product.prodname_copilot_short %} code completion and {% data variables.copilot.copilot_chat_short %} share some functionality, the two tools are best used in different circumstances.

Code completion works best for:

• Completing code snippets, variable names, and functions as you write them
• Generating repetitive code
• Generating code from inline comments in natural language
• Generating tests for test-driven development

Alternatively, {% data variables.copilot.copilot_chat_short %} is best suited for:

• Answering questions about code in natural language
• Generating large sections of code, then iterating on that code to meet your needs
• Accomplishing specific tasks with keywords and skills. {% data variables.copilot.copilot_chat_short %} has built-in keywords and skills designed to provide important context for prompts and accomplish common tasks quickly. Different types of keywords and skills are available in different {% data variables.copilot.copilot_chat_short %} platforms. See AUTOTITLE{% ifversion fpt %}.{% else %} and AUTOTITLE.{% endif %}
• Completing a task as a specific persona. For example, you can tell {% data variables.copilot.copilot_chat_short %} that it is a Senior C++ Developer who cares greatly about code quality, readability, and efficiency, then ask it to review your code.

Create thoughtful prompts

Prompt engineering, or structuring your request so {% data variables.product.prodname_copilot_short %} can easily understand and respond to it, plays a critical role in {% data variables.product.prodname_copilot_short %}'s ability to generate a valuable response. Here are a few quick tips you should remember while crafting your prompts:

• Break down complex tasks.
• Be specific about your requirements.
• Provide examples of things like input data, outputs, and implementations.
• Follow good coding practices.

To learn more, see AUTOTITLE.

Check {% data variables.product.prodname_copilot_short %}'s work

While {% data variables.product.prodname_copilot_short %} is very powerful, it is still a tool capable of making mistakes, and you should always validate the code it suggests. Use the following tips to ensure you are accepting accurate, secure suggestions:

• Understand suggested code before you implement it. To ensure you fully understand {% data variables.product.prodname_copilot_short %}'s suggestion, you can ask {% data variables.copilot.copilot_chat_short %} to explain the code.
• Review {% data variables.product.prodname_copilot_short %}'s suggestions carefully. Consider not just the functionality and security of the suggested code, but also the readability and maintainability of the code moving forward.
• Use automated tests and tooling to check {% data variables.product.prodname_copilot_short %}'s work. With the help of tools like linting, {% data variables.product.prodname_code_scanning %}, and IP scanning, you can automate an additional layer of security and accuracy checks.

[!TIP] Optionally, you may want to check {% data variables.product.prodname_copilot_short %}'s work for similarities to existing public code. If you don't want to use similar code, you can turn off suggestions matching public code. See {% ifversion fpt %}AUTOTITLE or AUTOTITLE.{% else %}AUTOTITLE, AUTOTITLE, or AUTOTITLE.{% endif %}

Guide {% data variables.product.prodname_copilot_short %} towards helpful outputs

There are several adjustments you can make to steer {% data variables.product.prodname_copilot_short %} towards more valuable responses:

• Provide {% data variables.product.prodname_copilot_short %} with helpful context:
  • If you are using {% data variables.product.prodname_copilot_short %} in your IDE, open relevant files and close irrelevant files.
  • In {% data variables.copilot.copilot_chat_short %}, if a particular request is no longer helpful context, delete that request from the conversation. Alternatively, if none of the context of a particular conversation is helpful, start a new conversation.
  • If you are using {% data variables.copilot.copilot_chat_dotcom_short %}, provide specific repositories, files, symbols, and more as context. See AUTOTITLE.
  • If you are using {% data variables.copilot.copilot_chat_short %} in your IDE, use keywords to focus {% data variables.product.prodname_copilot_short %} on a specific task or piece of context. See AUTOTITLE.
• Rewrite your prompts to generate different responses. If {% data variables.product.prodname_copilot_short %} is not providing a helpful response, try rephrasing your prompt, or even breaking your request down into multiple smaller prompts.
• Pick the best available suggestion. When you are using code completion, {% data variables.product.prodname_copilot_short %} might offer more than one suggestion. You can use keyboard shortcuts to quickly look through all available suggestions. For the default keyboard shortcuts for your operating system, see AUTOTITLE.
• Provide feedback to improve future suggestions. You can provide feedback in many ways:
  • For code completion, accept or reject {% data variables.product.prodname_copilot_short %}'s suggestion.
  • For individual responses in {% data variables.copilot.copilot_chat_short %}, click the thumbs up or thumbs down icons next to the response.
  • For {% data variables.copilot.copilot_chat_short %} in your IDE, see AUTOTITLE for instructions specific to your environment.
  • For {% data variables.copilot.copilot_chat_dotcom_short %}, leave a comment on the feedback discussion.

Stay up-to-date on {% data variables.product.prodname_copilot_short %}'s features

New features are regularly added to {% data variables.product.prodname_copilot_short %} to create new abilities, build on existing features, and improve the user experience. To stay up-to-date with {% data variables.product.prodname_copilot_short %}'s features, see the changelog.

SITE – Redefining FMCG

SITE (Sustainable Integrated Traceability Ecosystem) is a modular, scalable infrastructure designed to embed verifiable traceability across the entire FMCG landscape. Currently under private development, SITE will transition into the open-source ecosystem to provide Source-to-Shelf transparency and decentralized integrity.

Engineered for long-term impact, the framework prioritizes trust, integration flexibility, and ethical governance—empowering businesses and communities alike.

Key Capabilities

• Traceability APIs with event-driven lifecycle and compliance logging
• RESTful Data Orchestration for seamless audit integration
• QR-Based & Encrypted Identity for secure batch- and unit-level product mapping
• Role-Based Access Control for confidential, role-specific ecosystem participation
• Version-Controlled Documentation Pipelines aligned with global sustainability standards

Every product’s journey is a responsibility, not a transaction. SITE honors that journey with control, integrity, and global alignment. — #SachinKPal

Core Repositories (Private Until Open Source Launch)

• dhuniworldwide/site-core — Orchestration logic and lifecycle governance
• dhuniworldwide/trace-sdk — SDK for trace event triggers and public verification
• dhuniworldwide/traceability — Confidential modular trace mapping and ledger-ready workflows

Open Source Roadmap

SITE is built as a hybrid framework. Modules will transition into open-source after stabilization and compliance validation.

Planned integrations include:

• Blockchain-enforced audit trails and tamper-proof notarization
• ML-driven anomaly and fraud detection
• Distributed ledger compatibility for cross-border regulation
• Self-verifiable supply chain proofs with privacy-preserving obfuscation options

GitHub Copilot × Dhuni SITE

Copilot played a pivotal role during development—augmenting our capacity to build clean, secure, and modular code while maintaining architectural coherence.

It supported:

• Scaffold generation for secure API architecture
• Consistency across multi-repo systems
• Documentation-aligned refactoring cycles
• Traceable iterations with structural integrity

We built with vision. Copilot helped us stay honest, fast, and focused.

Community-First, Development-Phase

Dhuni SITE is more than infrastructure—it’s a commitment to community upliftment and shared accountability.

While in development, we welcome strategic dialogue with developers, certifiers, policy-makers, and technologists committed to inclusive systems design.

Email: site@dhuniworldwide.com
Website: https://www.dhuniworldwide.com

Our Commitment

SITE is Dhuni Worldwide’s contribution to redefining traceability for a new generation—rooted in transparency, designed for scalability, and aligned with our mission of empowerment, integrity, and global justice.

Thank you.