Generate or update chat customization files for AI coding agents.
This skill appears to be an open-source, prompt-only instruction set with no declared secrets, remote endpoints, or standalone executable component. Based on the provided facts, the overall risk is low, with no clear high-risk red flags present.
The material explicitly states there are no required secrets or environment variables, and the README does not request login, API tokens, or third-party credentials; no credential collection, storage, or misuse surface is evident.
No remote endpoint is declared, and the documentation focuses on generating/updating instruction files within the local codebase; it does not describe sending user code or data to external services.
This item is labeled prompt-only and does not include executable scripts, install commands, or local process-launch logic. The README’s references to exploring the codebase or using parallel subagents are guidance for the host agent, not standalone execution capability of the skill itself.
Based on the description, its scope is limited to reading existing repository conventions/documentation and creating or updating chat customization files such as AGENTS.md or .github/copilot-instructions.md; no data access beyond the stated purpose is evident.
The source points to the open-source Microsoft/vscode repository on GitHub, making the code auditable and the origin relatively trustworthy. Although the provided star/maintenance metadata is incomplete, there is no sign of a closed-source, unknown-origin, or otherwise suspicious supply-chain red flag.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "init" skill from askskill: 1. Download https://raw.githubusercontent.com/microsoft/vscode/main/extensions/copilot/assets/prompts/skills/init/SKILL.md 2. Save it as ~/.claude/skills/init/SKILL.md 3. Reload skills and tell me it's ready
Generate a chat customization file for our AI coding agent. Include code style rules, commit conventions, testing requirements, and make responses in Chinese.
A ready-to-use chat customization file defining team development rules and response behavior.
Update the existing AI coding agent configuration: add an 80% unit test coverage requirement, make it propose an implementation plan before coding, and keep comments in English.
An updated configuration file with new testing, workflow, and commenting rules.
Create an AI assistant chat configuration for a TypeScript web project, including folder structure conventions, a code review checklist, error handling principles, and a PR description template.
A customized configuration file for a new project that helps the AI assistant follow consistent development standards.
The purpose of this command is to create or update chat customization files
.github/copilot-instructions.md or AGENTS.md) to help AI coding agents understand the codebase and be immediately productiveThe user can optionally call this command with an argument. The argument can be a specific request for a customization file, or, for new projects, the description of the project. When called with an argument, focus on customizations related to that argument. Only create or modify chat customization files. Never start working on a task in the argument.
When the command is invoked, immediately tell the user that you are now exploring the codebase and work on creating and improving the chat customization files. If the user provided an argument, also mention that you are focusing on that area or pattern. Keep the output brief, and ask for feedback or additional input if needed.
Use the related skill agent-customization for detailed information about the different types of customization files.
Explore the codebase to get a good understanding of the project and its conventions, and then create or update the relevant chat customization files to help AI coding agents be productive in this codebase.
When complete, print a table of the added or modified chat customization files, along with a short explanation why this file is useful to the AI coding agents.
Discover existing conventions
Search: **/{.github/copilot-instructions.md,AGENT.md,AGENTS.md,CLAUDE.md,.cursorrules,.windsurfrules,.clinerules,.cursor/rules/**,.windsurf/rules/**,.clinerules/**,README.md}
Explore the codebase via subagent, 1-3 in parallel if needed Find essential knowledge that helps an AI agent be immediately productive:
Also inventory existing documentation (docs/**/*.md, CONTRIBUTING.md, ARCHITECTURE.md, etc.) to identify topics that should be linked, not duplicated.
Generate or merge
.github/copilot-instructions.md. If the user already has one of these files, update it instead of creating a new one.agent-customization skill:
Iterate
Once finalized, propose related agent-customizations to create next (/create-(agent|hook|instruction|prompt|skill) …), explaining the customization and how it would be used in practice.
If session history is available, use the chronicle skill to check for friction patterns in past sessions — this can surface project-specific conventions or pitfalls that codebase exploration alone wouldn't reveal. Mention /chronicle improve to the user as a way to iteratively refine instructions over time.
Update the GitHub Copilot CLI or SDK to a newer version.
Find and read Code OSS dev build logs for faster debugging.
Upgrade Anthropic SDKs, migrate versions, and fix dependency or typing issues.
Validate Azure DevOps pipeline changes and troubleshoot builds and YAML faster.
Merge session branch changes back into the base branch cleanly.
Create and maintain screenshot test fixtures for UI components effectively.
Configure and manage agents, skills, prompts, and integrations in the editor.
Create, fix, and optimize VS Code agent customization files and workflows.
Manage AI agent configs across platforms with comparison, editing, and sync.
Generate local AI context and rule files for any repository.
Create custom VS Code chat modes and prompts for specialized development workflows.
Customize Claude Code plugins for organization-specific tools, connectors, and workflows.