update-specification
github/awesome-copilot
Update specification files for AI consumption based on new requirements or code changes.
What is update-specification?
This skill updates existing specification files to reflect new requirements or code updates, optimized for Generative AI understanding. Use it when your solution's requirements, constraints, or interfaces change and you need to keep specifications current and machine-readable.
- Revises specification files with precise, unambiguous language suitable for AI processing
- Structures specifications using headings, lists, and tables for easy parsing
- Ensures specifications are self-contained without external context dependencies
- Maintains AI-ready formatting with explicit requirements, constraints, and guidelines
- Validates specifications follow the standard template with all required sections
- Organizes specifications in /spec/ directory with descriptive naming conventions
How to install update-specification
npx skills add https://github.com/github/awesome-copilot --skill update-specification- An existing specification file in /spec/ directory with .md extension
- Understanding of the specification template structure and best practices
- Knowledge of the changes or new requirements to be documented
How to use update-specification
- 1.Identify the specification file that needs updating in the /spec/ directory
- 2.Gather the new requirements, code changes, or constraint updates
- 3.Review the current specification against the standard template
- 4.Update relevant sections (Purpose & Scope, Requirements, Interfaces, Acceptance Criteria, etc.)
- 5.Ensure all acronyms are defined and language is precise and unambiguous
- 6.Verify the specification is self-contained and uses structured formatting
- 7.Update the last_updated date in the front matter
- 8.Save the updated specification file with the same naming convention
Use cases
- Update a specification when new API endpoints or data contracts are added to the codebase
- Revise infrastructure specifications after architecture changes or dependency updates
- Modify process specifications when workflow requirements change based on stakeholder feedback
- Update schema specifications when data models are refactored or extended
- Refresh acceptance criteria and test strategies when feature scope expands
- Software architects designing AI-consumable documentation
- Development teams maintaining specification accuracy alongside code changes
- Technical leads ensuring specifications remain current and machine-readable
- AI coding agents (Claude Code, Cursor) that rely on clear specifications for implementation
update-specification FAQ
Files should be named [a-z0-9-]+.md in the /spec/ directory, starting with a high-level purpose (schema, tool, data, infrastructure, process, architecture, or design) followed by a descriptive name.
Precise, structured, and unambiguous specifications allow Generative AIs to parse requirements accurately, reducing misinterpretation and improving code generation quality.
Include the section header but note it as 'Not applicable' or 'N/A' with a brief explanation, maintaining the complete template structure.
Update specifications whenever requirements change, code interfaces are modified, constraints are added, or new dependencies are introduced.
No—focus on architectural and business dependencies (e.g., 'OAuth 2.0 authentication library') rather than specific package versions unless they represent critical architectural constraints.
Full instructions (SKILL.md)
Source of truth, from github/awesome-copilot.
name: update-specification description: 'Update an existing specification file for the solution, optimized for Generative AI consumption based on new requirements or updates to any existing code.'
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
- **DAT-001**: [External data source] - [Format, frequency, and access requirements]
### Technology Platform Dependencies
- **PLT-001**: [Platform/runtime requirement] - [Version constraints and rationale]
### Compliance Dependencies
- **COM-001**: [Regulatory or compliance requirement] - [Impact on implementation]
**Note**: This section should focus on architectural and business dependencies, not specific package implementations. For example, specify "OAuth 2.0 authentication library" rather than "Microsoft.AspNetCore.Authentication.JwtBearer v6.0.1".
## 9. Examples & Edge Cases
```code
// Code snippet or data example demonstrating the correct application of the guidelines, including edge cases
10. Validation Criteria
[List the criteria or tests that must be satisfied for compliance with this specification.]
11. Related Specifications / Further Reading
[Link to related spec 1] [Link to relevant external documentation]
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