update-specification
Updates specification files for AI. It optimizes content so AI models can understand and use it better.
What it does
This tool updates an existing specification file. It ensures that the rules and details of a software project are clear and well-organized so that other AI tools can easily understand them.
When to use it
- ✓When a software project needs its rules and details documented.
- ✓When the rules of a software project change and the documentation needs updating.
- ✓When you want to ensure your project's documentation is easy for other AIs to understand.
Example of what to ask your AI
“Update the specification for the file 'api-gateway.md' with the new authentication rules.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool takes the specification file you point to and modifies it following best practices. It organizes the information clearly, using headings, lists, and avoiding ambiguous language, so that AI can process everything correctly.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add github/awesome-copilot --skill update-specificationOr download just the file:
curl -L https://raw.githubusercontent.com/github/awesome-copilot/main/skills/update-specification/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Update Specification
Your goal is to update the existing specification file ${file} based on new requirements or updates to any existing code.
The specification file must define the requirements, constraints, and interfaces for the solution components in a manner that is clear, unambiguous, and structured for effective use by Generative AIs. Follow established documentation standards and ensure the content is machine-readable and self-contained.
Best Practices for AI-Ready Specifications
- Use precise, explicit, and unambiguous language.
- Clearly distinguish between requirements, constraints, and recommendations.
- Use structured formatting (headings, lists, tables) for easy parsing.
- Avoid idioms, metaphors, or context-dependent references.
- Define all acronyms and domain-specific terms.
- Include examples and edge cases where applicable.
- Ensure the document is self-contained and does not rely on external context.
The specification should be saved in the /spec/ directory and named according to the following convention: [a-z0-9-]+.md, where the name should be descriptive of the specification's content and starting with the highlevel purpose, which is one of [schema, tool, data, infrastructure, process, architecture, or design].
The specification file must be formatted in well formed Markdown.
Specification files must follow the template below, ensuring that all sections are filled out appropriately. The front matter for the markdown should be structured correctly as per the example following:
---
title: [Concise Title Describing the Specification's Focus]
version: [Optional: e.g., 1.0, Date]
date_created: [YYYY-MM-DD]
last_updated: [Optional: YYYY-MM-DD]
owner: [Optional: Team/Individual responsible for this spec]
tags: [Optional: List of relevant tags or categories, e.g., `infrastructure`, `process`, `design`, `app` etc]
---
# Introduction
[A short concise introduction to the specification and the goal it is intended to achieve.]
## 1. Purpose & Scope
[Provide a clear, concise description of the specification's purpose and the scope of its application. State the intended audience and any assumptions.]
## 2. Definitions
[List and define all acronyms, abbreviations, and domain-specific terms used in this specification.]
## 3. Requirements, Constraints & Guidelines
[Explicitly list all requirements, constraints, rules, and guidelines. Use bullet points or tables for clarity.]
- **REQ-001**: Requirement 1
- **SEC-001**: Security Requirement 1
- **[3 LETTERS]-001**: Other Requirement 1
- **CON-001**: Constraint 1
- **GUD-001**: Guideline 1
- **PAT-001**: Pattern to follow 1
## 4. Interfaces & Data Contracts
[Describe the interfaces, APIs, data contracts, or integration points. Use tables or code blocks for schemas and examples.]
## 5. Acceptance Criteria
[Define clear, testable acceptance criteria for each requirement using Given-When-Then format where appropriate.]
- **AC-001**: Given [context], When [action], Then [expected outcome]
- **AC-002**: The system shall [specific behavior] when [condition]
- **AC-003**: [Additional acceptance criteria as needed]
## 6. Test Automation Strategy
[Define the testing approach, frameworks, and automation requirements.]
- **Test Levels**: Unit, Integration, End-to-End
- **Frameworks**: MSTest, FluentAssertions, Moq (for .NET applications)
- **Test Data Management**: [approach for test data creation and cleanup]
- **CI/CD Integration**: [automated testing in GitHub Actions pipelines]
- **Coverage Requirements**: [minimum code coverage thresholds]
- **Performance Testing**: [approach for load and performance testing]
## 7. Rationale & Context
[Explain the reasoning behind the requirements, constraints, and guidelines. Provide context for design decisions.]
## 8. Dependencies & External Integrations
[Define the external systems, services, and architectural dependencies required for this specification. Focus on **what** is needed rather than **how** it's implemented. Avoid specific package or library versions unless they represent architectural constraints.]
### External Systems
- **EXT-001**: [External system name] - [Purpose and integration type]
### Third-Party Services
- **SVC-001**: [Service name] - [Required capabilities and SLA requirements]
### Infrastructure Dependencies
- **INF-001**: [Infrastructure component] - [Requirements and constraints]
### Data Dependencies
…
FAQ
What is a specification file?
It's a document that describes in detail how a software or part of it should work, including rules, constraints, and how it communicates with other parts.
Why does documentation need to be 'optimized for AI'?
So that artificial intelligence tools can read, understand, and use the information efficiently, without confusion or misinterpretation.
What kind of information goes into this file?
Requirements (what the software must do), constraints (what it cannot do or how it must be done), interfaces (how it connects with other systems), acceptance criteria (how to know if it's working correctly), and more.
Details
Original description by the author
Update an existing specification file for the solution, optimized for Generative AI consumption based on new requirements or updates to any existing code.
repo: github/awesome-copilot
Popularity
- GitHub stars
- 40k
- Ranking position
- #5409
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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