# Reference Guide

#### Important Links

* Documentation: <https://github.github.io/spec-kit/>
* Repository: <https://github.com/github/spec-kit>

#### Core Workflow Commands Cheat Sheet

| **Phase**  | **Command**                   | **Purpose**         |
| ---------- | ----------------------------- | ------------------- |
| Setup      | `specify init . --ai <agent>` | Initialize Spec-Kit |
| Principles | `/speckit.constitution`       | Define standards    |
| Spec       | `/speckit.specify`            | Describe features   |
| Plan       | `/speckit.plan`               | Define tech stack   |
| Tasks      | `/speckit.tasks`              | Create checklist    |
| Code       | `/speckit.implement`          | Generate code       |

#### Supported AI Agents

Spec-Kit is designed to be model-agnostic, though it is optimized for agents with large context windows:

* GitHub Copilot
* Anthropic Claude
* Google Gemini
* OpenAI GPT-4&#x20;

and much more....


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://shankar-lab.gitbook.io/mylearning/github-spec-kit/reference-guide.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.