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48 changes: 42 additions & 6 deletions README.md
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## TLDR / Quickstart

**Want to install these prompts as slash commands?** Use the [slash-command-manager](https://github.com/liatrio-labs/slash-command-manager) utility to install them in all of your local AI tools:
### What is this?

This repository provides **structured prompts** (Markdown files) that guide AI assistants through a complete software development workflow. Starting with a feature or story from your backlog, these prompts help you create: detailed specification → task breakdown → implementation → validation. Think of them as reusable playbooks that keep AI agents focused and consistent.

### Installation Options

#### Option A: Install as Slash Commands (Recommended)

Install these prompts as native `/slash-commands` in your AI assistant (Cursor, Windsurf, Claude Code, etc.) using the [slash-command-manager](https://github.com/liatrio-labs/slash-command-manager) utility:

```bash
uvx --from git+https://github.com/liatrio-labs/slash-command-manager \
Expand All @@ -26,15 +34,43 @@ uvx --from git+https://github.com/liatrio-labs/slash-command-manager \
--github-path prompts/
```

**Want to use the prompts directly?** Copy-paste them into your AI assistant:
**What this command does:**

- `uvx` runs Python tools without installation (like `npx` for Python)
- Fetches the `slash-command-manager` tool from GitHub
- `slash-man generate` auto-detects your installed AI assistants
- Downloads the prompt files from `prompts/` directory
- Installs them as slash commands like `/generate-spec`, `/manage-tasks`, etc.

**Result:** You can now type `/generate-spec` in your AI assistant to start the workflow.

#### Option B: Manual Copy-Paste (No Installation)

Copy the prompt files directly from `prompts/` and paste them into your AI chat. The AI will follow the structured instructions in each prompt.

### The 4-Step Workflow

Each step uses a different prompt file and produces specific artifacts:

1. **Generate a spec:** Copy `prompts/generate-spec.md` into your AI chat → AI assesses scope, asks structured questions (numbered/lettered options), optionally reviews codebase, generates spec, iterates with you → Spec saved to `docs/specs/01-spec-<feature-name>/01-spec-<feature-name>.md`
1. **Generate a Spec** (`prompts/generate-spec.md`)
- **What it does:** Guides AI to ask clarifying questions, assess scope, and create a detailed specification document
- **Output:** `docs/specs/01-spec-<feature-name>/01-spec-<feature-name>.md` — A comprehensive spec with goals, requirements, demo criteria, and success metrics
- **Why:** Ensures everyone (human and AI) agrees on what to build before writing code

2. **Generate task list:** Point AI to spec (or let it auto-discover) and use `prompts/generate-task-list-from-spec.md` → AI analyzes spec, generates parent tasks for review, then after confirmation expands into sub-tasks with "Relevant Files" section → Saved to `docs/specs/01-spec-<feature-name>/01-tasks-<feature-name>.md`
2. **Generate Task List** (`prompts/generate-task-list-from-spec.md`)
- **What it does:** Breaks the spec into parent tasks (demoable units) and detailed sub-tasks with relevant files
- **Output:** `docs/specs/01-spec-<feature-name>/01-tasks-<feature-name>.md` — A checklist of all work items with `[ ]` not started, `[~]` in progress, `[x]` complete
- **Why:** Creates an actionable implementation plan with clear checkpoints

3. **Manage tasks:** Use `prompts/manage-tasks.md` while implementing → Choose checkpoint mode (Continuous/Task/Batch), execute with verification checklists, create proof artifacts **before** commits → Proofs saved to `docs/specs/01-spec-<feature-name>/01-proofs/[NN]-task-[TT]-proofs.md`
3. **Manage Tasks** (`prompts/manage-tasks.md`)
- **What it does:** Guides execution with verification checklists, creates proof artifacts (screenshots, test results, CLI output) before each commit
- **Output:** `docs/specs/01-spec-<feature-name>/01-proofs/[NN]-task-[TT]-proofs.md` — Evidence that each task works as intended
- **Why:** Maintains quality and creates a verifiable audit trail of what was built

4. **Validate:** Use `prompts/validate-spec-implementation.md` (or let it auto-discover) → AI verifies proof artifacts, applies validation gates, produces coverage matrix and validation report
4. **Validate Implementation** (`prompts/validate-spec-implementation.md`)
- **What it does:** Verifies the implementation matches the spec using proof artifacts, applies validation gates, generates coverage matrix
- **Output:** Validation report showing what's verified, what's missing, and any issues
- **Why:** Confirms the feature is complete and meets all requirements before shipping

5. **SHIP IT** 🚢💨

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