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docs: reorganize README with clearer usage options
- Restructure Hands-On Usage section into three clear options:
Option 1: Manual Copy-Paste (No Tooling Required)
Option 2: Native Slash Commands (Recommended)
Option 3: MCP Server (Advanced)
- Add git URL examples for running via uvx --from
- Improve organization from simplest to most automated
- Add PyPI notes for future simplified syntax
Provides a clearer progression for users choosing their preferred
workflow integration method.
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@@ -115,21 +115,40 @@ sequenceDiagram
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-**Status Keys:**`[ ]` not started, `[~]` in progress, `[x]` complete, mirroring the manage-tasks guidance.
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-**Proof Artifacts:** URLs, CLI commands, screenshots, or tests captured per task to demonstrate working software.
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## Hands-On Usage (No MCP Required)
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## Hands-On Usage
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The SDD workflow can be used in three ways, from simplest to most automated:
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### Option 1: Manual Copy-Paste (No Tooling Required)
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1.**Kick off a spec:** Copy or reference `prompts/generate-spec.md` inside your preferred AI chat. Provide the feature idea, answer the clarifying questions, and review the generated spec before saving it under `/tasks`.
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2.**Plan the work:** Point the assistant to the new spec and walk through `prompts/generate-task-list-from-spec.md`. Approve parent tasks first, then request the detailed subtasks and relevant files. Commit the result to `/tasks`.
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3.**Execute with discipline:** Follow `prompts/manage-tasks.md` while implementing. Update statuses as you work, attach proof artifacts, and pause for reviews at each demoable slice.
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### Slash Command Integration (TBD)
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### Option 2: Native Slash Commands (Recommended)
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Generate slash commands for your AI coding assistant and use the prompts as native commands:
This will auto-detect your configured AI assistants (Claude Code, Cursor, Windsurf, etc.) and generate command files in your home directory.
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Guides are coming for wiring these prompts as first-class slash commands in popular IDEs and AI tools (Windsurf, VS Code, Cursor, Claude Code, Codex, and more).
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**Note**: Once available on PyPI, you'll be able to run `uvx spec-driven-development-mcp sdd-generate-commands --yes` for a one-liner installation.
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See [docs/slash-command-generator.md](./docs/slash-command-generator.md) for details on generating command files for AI assistants.
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See [docs/slash-command-generator.md](./docs/slash-command-generator.md) for details.
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##Optional: Automate with the MCP Server
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### Option 3: MCP Server (Advanced)
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Prefer tighter tooling? This repository also ships an MCP server that exposes the same prompts programmatically. Treat it as an accelerator—everything above works without it.
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Run the prompts as an MCP server for programmatic access. This option is most useful for custom integrations and tools that support MCP.
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> Note: MCP prompt support is not uniformly supported across AI tools. See [docs/mcp-prompt-support.md](./docs/mcp-prompt-support.md) for details.
**Note**: Once available on PyPI, you'll be able to run `uvx spec-driven-development-mcp` for a one-liner installation with optional `--transport` and `--port` arguments. The `fastmcp run` approach remains available for development and advanced options.
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See [docs/operations.md](docs/operations.md) and [CONTRIBUTING.md](CONTRIBUTING.md) for advanced configuration, deployment, and contribution guidelines.
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