Official agent skill

Code Exemplars Blueprint Generator

by github in github/awesome-copilot

Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars.

OfficialMITAuto-check passedDevelopment

Install Code Exemplars Blueprint Generator

skills CLI
$ npx skills add github/awesome-copilot --skill code-exemplars-blueprint-generator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install github/awesome-copilot code-exemplars-blueprint-generator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/github/awesome-copilot.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/code-exemplars-blueprint-generator .claude/skills/code-exemplars-blueprint-generator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
code-exemplars-blueprint-generator
GitHub stars
40k
Used in
2 other repos
Token cost
~1.7k tokens
SKILL.md length
615 words
Files
1
Skills in repo
417
Repo updated
First seen
Licence
MIT

At a glance

Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars.

  • Works in 5 steps: Codebase Analysis Phase → Exemplar Identification Criteria → Core Pattern Categories → …
  • Tasks that involve Code quality
  • SKILL.md covers Configuration Variables, Generated Prompt and Expected Output
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Code Exemplars Blueprint Generator is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars. Supports multiple programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with configurable analysis depth, categorization methods, and documentation formats to establish coding standards and maintain consistency across development teams.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development, covering Code quality. It works with .NET, Angular, React and Java. The repository describes itself as: Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot. The licence is MIT.

When your agent uses it

  • Tasks that involve Code quality

Example prompts

  • “/code-exemplars-blueprint-generator”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Codebase Analysis Phase
  2. Exemplar Identification Criteria
  3. Core Pattern Categories
  4. Architecture Layer Exemplars
  5. Exemplar Documentation Format

What it can do on your machine

Read from SKILL.md and the folder at commit 727ff2e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Code Exemplars Blueprint Generator loads about 1.7k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 615 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from github/awesome-copilot at commit 727ff2e, republished under its MIT licence (© github). 615 words, ~1,678 tokens.

Download SKILL.mdSave it as .claude/skills/code-exemplars-blueprint-generator/SKILL.md (or your agent's skills folder).
name
code-exemplars-blueprint-generator
description
Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars. Supports multiple programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with configurable analysis depth, categorization methods, and documentation formats to establish coding standards and maintain consistency across development teams.

Code Exemplars Blueprint Generator

Configuration Variables

${PROJECT_TYPE="Auto-detect|.NET|Java|JavaScript|TypeScript|React|Angular|Python|Other"} <!-- Primary technology --> ${SCAN_DEPTH="Basic|Standard|Comprehensive"} <!-- How deeply to analyze the codebase --> ${INCLUDE_CODE_SNIPPETS=true|false} <!-- Include actual code snippets in addition to file references --> ${CATEGORIZATION="Pattern Type|Architecture Layer|File Type"} <!-- How to organize exemplars --> ${MAX_EXAMPLES_PER_CATEGORY=3} <!-- Maximum number of examples per category --> ${INCLUDE_COMMENTS=true|false} <!-- Include explanatory comments for each exemplar -->

Generated Prompt

"Scan this codebase and generate an exemplars.md file that identifies high-quality, representative code examples. The exemplars should demonstrate our coding standards and patterns to help maintain consistency. Use the following approach:

1. Codebase Analysis Phase
  • ${PROJECT_TYPE == "Auto-detect" ? "Automatically detect primary programming languages and frameworks by scanning file extensions and configuration files" : Focus on ${PROJECT_TYPE} code files}
  • Identify files with high-quality implementation, good documentation, and clear structure
  • Look for commonly used patterns, architecture components, and well-structured implementations
  • Prioritize files that demonstrate best practices for our technology stack
  • Only reference actual files that exist in the codebase - no hypothetical examples
2. Exemplar Identification Criteria
  • Well-structured, readable code with clear naming conventions
  • Comprehensive comments and documentation
  • Proper error handling and validation
  • Adherence to design patterns and architectural principles
  • Separation of concerns and single responsibility principle
  • Efficient implementation without code smells
  • Representative of our standard approaches
3. Core Pattern Categories

${PROJECT_TYPE == ".NET" || PROJECT_TYPE == "Auto-detect" ? `#### .NET Exemplars (if detected)

  • Domain Models: Find entities that properly implement encapsulation and domain logic
  • Repository Implementations: Examples of our data access approach
  • Service Layer Components: Well-structured business logic implementations
  • Controller Patterns: Clean API controllers with proper validation and responses
  • Dependency Injection Usage: Good examples of DI configuration and usage
  • Middleware Components: Custom middleware implementations
  • Unit Test Patterns: Well-structured tests with proper arrangement and assertions` : ""}

${(PROJECT_TYPE == "JavaScript" || PROJECT_TYPE == "TypeScript" || PROJECT_TYPE == "React" || PROJECT_TYPE == "Angular" || PROJECT_TYPE == "Auto-detect") ? `#### Frontend Exemplars (if detected)

  • Component Structure: Clean, well-structured components
  • State Management: Good examples of state handling
  • API Integration: Well-implemented service calls and data handling
  • Form Handling: Validation and submission patterns
  • Routing Implementation: Navigation and route configuration
  • UI Components: Reusable, well-structured UI elements
  • Unit Test Examples: Component and service tests` : ""}

${PROJECT_TYPE == "Java" || PROJECT_TYPE == "Auto-detect" ? `#### Java Exemplars (if detected)

  • Entity Classes: Well-designed JPA entities or domain models
  • Service Implementations: Clean service layer components
  • Repository Patterns: Data access implementations
  • Controller/Resource Classes: API endpoint implementations
  • Configuration Classes: Application configuration
  • Unit Tests: Well-structured JUnit tests` : ""}

${PROJECT_TYPE == "Python" || PROJECT_TYPE == "Auto-detect" ? `#### Python Exemplars (if detected)

  • Class Definitions: Well-structured classes with proper documentation
  • API Routes/Views: Clean API implementations
  • Data Models: ORM model definitions
  • Service Functions: Business logic implementations
  • Utility Modules: Helper and utility functions
  • Test Cases: Well-structured unit tests` : ""}
Show full SKILL.md (242 more words)Show less
4. Architecture Layer Exemplars
  • Presentation Layer:

    • User interface components
    • Controllers/API endpoints
    • View models/DTOs
  • Business Logic Layer:

    • Service implementations
    • Business logic components
    • Workflow orchestration
  • Data Access Layer:

    • Repository implementations
    • Data models
    • Query patterns
  • Cross-Cutting Concerns:

    • Logging implementations
    • Error handling
    • Authentication/authorization
    • Validation
5. Exemplar Documentation Format

For each identified exemplar, document:

  • File path (relative to repository root)
  • Brief description of what makes it exemplary
  • Pattern or component type it represents ${INCLUDE_COMMENTS ? "- Key implementation details and coding principles demonstrated" : ""} ${INCLUDE_CODE_SNIPPETS ? "- Small, representative code snippet (if applicable)" : ""}

${SCAN_DEPTH == "Comprehensive" ? `### 6. Additional Documentation

  • Consistency Patterns: Note consistent patterns observed across the codebase
  • Architecture Observations: Document architectural patterns evident in the code
  • Implementation Conventions: Identify naming and structural conventions
  • Anti-patterns to Avoid: Note any areas where the codebase deviates from best practices` : ""}
${SCAN_DEPTH == "Comprehensive" ? "7" : "6"}. Output Format

Create exemplars.md with:

  1. Introduction explaining the purpose of the document
  2. Table of contents with links to categories
  3. Organized sections based on ${CATEGORIZATION}
  4. Up to ${MAX_EXAMPLES_PER_CATEGORY} exemplars per category
  5. Conclusion with recommendations for maintaining code quality

The document should be actionable for developers needing guidance on implementing new features consistent with existing patterns.

Important: Only include actual files from the codebase. Verify all file paths exist. Do not include placeholder or hypothetical examples. "

Expected Output

Upon running this prompt, GitHub Copilot will scan your codebase and generate an exemplars.md file containing real references to high-quality code examples in your repository, organized according to your selected parameters.

© github, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/code-exemplars-blueprint-generator of github/awesome-copilot.

Open the folder on GitHubat commit 727ff2e

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in github/awesome-copilot, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Code Exemplars Blueprint Generator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Code Exemplars Blueprint Generator compared with similar skills
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Code Exemplars Blueprint Generator this skillgithub/awesome-copilot40k2 repos~1.7kAutomated safety check: PassMIT
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Cross-Language Coding Standardszereight/gitlab-mcp2k1 repos~1.4kAutomated safety check: PassMIT
Code Review SkillRain-kl/OpenFlare288—~2.3kAutomated safety check: NotesMIT
Code Review Excellenceandrew-yangy/gru-ai155—~1.7kAutomated safety check: NotesMIT
Supercovsupercorp-ai/supercov1481 repos~415Automated safety check: PassMIT

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Categories

Questions about Code Exemplars Blueprint Generator

What does Code Exemplars Blueprint Generator do?

Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars. Code Exemplars Blueprint Generator is an agent skill from github/awesome-copilot, published by the product's own GitHub organization. Technology-agnostic prompt generator that creates customizable AI prompts for scanning codebases and identifying high-quality code exemplars.

When should I use Code Exemplars Blueprint Generator?

Code Exemplars Blueprint Generator fits situations like: tasks that involve Code quality.

How do I install Code Exemplars Blueprint Generator in Claude Code?

Run `npx skills add github/awesome-copilot --skill code-exemplars-blueprint-generator -a claude-code`. Or copy the skill folder (skills/code-exemplars-blueprint-generator in github/awesome-copilot) into .claude/skills/code-exemplars-blueprint-generator in your project. Claude Code loads it when a task matches its description.

How do I install Code Exemplars Blueprint Generator in Codex?

Run `npx skills add github/awesome-copilot --skill code-exemplars-blueprint-generator -a codex`. Or copy the skill folder (skills/code-exemplars-blueprint-generator in github/awesome-copilot) into .agents/skills/code-exemplars-blueprint-generator in your project. Codex loads it when a task matches its description.

Can I use Code Exemplars Blueprint Generator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add github/awesome-copilot --skill code-exemplars-blueprint-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-exemplars-blueprint-generator, .gemini/skills/code-exemplars-blueprint-generator, .github/skills/code-exemplars-blueprint-generator and .opencode/skills/code-exemplars-blueprint-generator in your project.

What does Code Exemplars Blueprint Generator need to run?

SKILL.md names no scripts, command-line tools or credentials: Code Exemplars Blueprint Generator is instructions for the agent only. Our summary lists: Python 3.

Does Code Exemplars Blueprint Generator access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Code Exemplars Blueprint Generator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Code Exemplars Blueprint Generator use?

Code Exemplars Blueprint Generator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Code Exemplars Blueprint Generator use?

About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Code Exemplars Blueprint Generator?

Skills that share tags, products or a category with Code Exemplars Blueprint Generator: Code Review Skill (awesome-skills/code-review-skill, 2.1k stars), Cross-Language Coding Standards (zereight/gitlab-mcp, 2k stars), Code Review Skill (Rain-kl/OpenFlare, 288 stars) and Code Review Excellence (andrew-yangy/gru-ai, 155 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Code Exemplars Blueprint Generator?

github (a GitHub organization, an official publisher) maintains it in github/awesome-copilot, which has 39,748 GitHub stars. The repository holds 417 skills in this directory. The repository was last updated on October 7, 2026.

Source: github/awesome-copilot on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.