Analysis Generate Copilot Instructions Command

**Perform comprehensive codebase analysis** to generate or update `.github/copilot-instructions.md` with actual project-specific content. This command should produce a complete, analysis-driven copilot instructions file with **NO placeholder text or "to be populated" sections** - all content must be

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Jan 15, 2026

Analysis Generate Copilot Instructions Command

Purpose

Perform comprehensive codebase analysis to generate or update

.github/copilot-instructions.md

with actual project-specific content. This command should produce a complete, analysis-driven copilot instructions file with NO placeholder text or "to be populated" sections - all content must be based on real analysis of the actual project.

Critical Requirement

🚨 DO NOT CREATE PLACEHOLDER CONTENT - This command must analyze the actual codebase and populate all sections with real, discovered information. The output should be immediately useful for GitHub Copilot, not a template waiting for future population.

Step-by-Step Instructions

Step 1: Load Project Context

Review project roadmap in

.github/instructions/roadmap.instructions.md

Load coding standards from

.ai-operator/templates/code-styles/code-style.md

Ensure these files are open in VS Code for Copilot context.

Step 2: Comprehensive Codebase Analysis

EXECUTE THIS PROMPT EXACTLY:

Analyze this codebase to generate or update

.github/copilot-instructions.md

for guiding AI coding agents.

Focus on discovering the essential knowledge that would help an AI agents be immediately productive in this codebase. Consider aspects like:

The "big picture" architecture that requires reading multiple files to understand - major components, service boundaries, data flows, and the "why" behind structural decisions
Critical developer workflows (builds, tests, debugging) especially commands that aren't obvious from file inspection alone
Project-specific conventions and patterns that differ from common practices
Integration points, external dependencies, and cross-component communication patterns

Source existing AI conventions from

**/{.github/copilot-instructions.md,AGENT.md,AGENTS.md,CLAUDE.md,.cursorrules,.windsurfrules,.clinerules,.cursor/rules/**,.windsurf/rules/**,.clinerules/**,README.md}

(do one glob search).

Guidelines (read more at https://aka.ms/vscode-instructions-docs):

If
```
.github/copilot-instructions.md
```
exists, merge intelligently - preserve valuable content while updating outdated sections
Write concise, actionable instructions (~20-50 lines) using markdown structure
Include specific examples from the codebase when describing patterns
Avoid generic advice ("write tests", "handle errors") - focus on THIS project's specific approaches
Document only discoverable patterns, not aspirational practices
Reference key files/directories that exemplify important patterns

Update

.github/copilot-instructions.md

for the user, then ask for feedback on any unclear or incomplete sections to iterate.

Additional Analysis Requirements:

Ignore the
.ai-operator
folder as part of the project codebase; treat it as a customizable workflow

Step 3: Quality Guidelines for Analysis

Write concise, actionable instructions (~20-50 lines) using markdown structure
Include specific examples from the codebase when describing patterns
Avoid generic advice ("write tests", "handle errors") - focus on THIS project's specific approaches
Document only discoverable patterns, not aspirational practices
Reference key files/directories that exemplify important patterns

Step 4: Perform Comprehensive Codebase Analysis

Analyze Project Overview (populate immediately, don't leave as placeholder):
- Read README.md, package.json, or similar to understand project purpose
- Identify key features from actual code structure and functionality
- Determine target users from documentation or code patterns
- Extract business context from existing docs or code organization
Analyze Technology Stack (populate immediately with discovered technologies):
- Scan files to identify all programming languages actually used
- Identify frameworks and libraries from package.json, requirements.txt, etc.
- Document build tools (webpack, vite, gradle, etc.) found in config files
- List deployment technologies found in Docker, CI/CD files, etc.
Analyze Project Structure (populate immediately with actual directories):
- Document key directories and their actual purposes (src/, tests/, docs/, etc.)
- Identify important configuration files that actually exist
- Find entry points (main.js, index.html, app.py, etc.)
- Document test structure as it actually exists
Analyze Workflow Information (populate immediately with discovered workflows):
- Check for actual git workflows in .github/ or documentation
- Identify testing approach from existing test files and scripts
- Document deployment process from actual CI/CD files or scripts

Step 5: Generate Complete Copilot Instructions

Create comprehensive

.github/copilot-instructions.md

with proper frontmatter and all sections populated:

---
description: "Core project context and AI coding guidelines that auto-load with GitHub Copilot"
applyTo: "**"
---

# GitHub Copilot Instructions
[Content follows...]

NO placeholder text like "To be populated by setup agents"
ALL sections filled with actual analysis results
Specific examples from the real codebase
Concrete, actionable guidance based on what actually exists
CRITICAL: Include the frontmatter header with applyTo: "**" to ensure global application

If existing file exists: Merge intelligently, preserving valuable content while updating with fresh analysis
Ensure quality: Instructions should be specific to THIS project, not generic advice

Step 6: Validate Analysis Quality

Review completeness: Every section should have real content from analysis
Verify examples: All examples should reference actual files/patterns from the project
Test usefulness: The instructions should help AI understand this specific project immediately
Ask for feedback on any unclear sections for iteration

Guidelines

AI Team Management

Leverage AI team management for coordinated execution.
For git operations, only checkout to a feature branch via command line (e.g.,
```
git checkout -b "feature/branch-name"
```
) upon explicit user approval. Avoid pushing changes, committing, or other potentially cumbersome actions.

Content Quality Standards

Focus on project-specific approaches, not generic advice.
Document discoverable patterns with examples.
Ensure mandatory context loading for agents and Copilot.

GitHub Copilot Integration

Context Files

When working on this feature, ensure these files are open in VS Code:

```
src/components/[related-component].tsx
```
```
src/types/[related-types].ts
```
```
tests/[related-tests].test.ts
```

Code Examples

[Provide concrete examples that Copilot can reference, e.g., instruction templates]

Common Patterns

[Document project-specific patterns for Copilot to learn, e.g., standard instruction structures]

Analysis Generate Copilot Instructions Command

Analysis Generate Copilot Instructions Command

Purpose

Critical Requirement

Step-by-Step Instructions

Step 1: Load Project Context

Step 2: Comprehensive Codebase Analysis

Step 3: Quality Guidelines for Analysis

Step 4: Perform Comprehensive Codebase Analysis

Step 5: Generate Complete Copilot Instructions

Step 6: Validate Analysis Quality

Guidelines

AI Team Management

Content Quality Standards

GitHub Copilot Integration

Context Files

Code Examples

Common Patterns

Related Skills

Markdown Converter

Nano Banana Pro

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Analysis Generate Copilot Instructions Command

Purpose

Critical Requirement

Step-by-Step Instructions

Step 1: Load Project Context

Step 2: Comprehensive Codebase Analysis

Step 3: Quality Guidelines for Analysis

Step 4: Perform Comprehensive Codebase Analysis

Step 5: Generate Complete Copilot Instructions

Step 6: Validate Analysis Quality

Guidelines

AI Team Management

Content Quality Standards

GitHub Copilot Integration

Context Files

Code Examples

Common Patterns