# 🎯 How Taskr Actually Works

## 3.5 Dynamic Guidance - Keeping Your AI on Track

### The Problem It Solves

Ever notice how AI sometimes "drifts" during long conversations? It might start organized but gradually forget the rules or best practices. Dynamic guidance fixes this!

### How It Works

Every time your AI uses a Taskr tool, the response includes three parts:

```json
{
  "data": {
    // The actual result (task created, note saved, etc.)
  },
  "rules": [
    // Markdown rules relevant RIGHT NOW
    "- Work on one task at a time",
    "- Mark tasks complete before moving on",
    "- Create notes for important discoveries"
  ],
  "actions": [
    // Suggested next steps
    "Call get_task to continue working",
    "Create a PROGRESS note if you completed something major"
  ]
}
```

### Context-Aware Adaptation

The guidance changes based on what your AI is doing:

- **Starting work?** → Rules about task selection
- **Creating notes?** → Rules about note types and quality
- **Generating tasks?** → Rules about organization and structure
- **Updating status?** → Rules about completion criteria

### Real Examples

**When calling `get_task`:**
- Guidance includes the "process-task-list" rule
- Reminds AI to work sequentially
- Suggests creating notes for discoveries

**When calling `create_note`:**
- Guidance includes note type definitions
- Reminds about task attachment
- Suggests using specific types for specific content

### Smart Actions

Beyond rules, Taskr also sends **actions** with its responses—these are practical next steps tailored to what your AI just did:

- **Workflow actions** — Step-by-step guidance like "Step 1 complete, now drill into the relevant task list"
- **Hint actions** — Suggested tool calls like "Use `get_task_hierarchy` to verify changes" or "Create a PROGRESS note for this milestone"

These actions change dynamically based on context. After completing a task, the hints suggest getting the next one. After creating tasks, they suggest verifying the hierarchy. It's like a GPS that recalculates after every turn.

### Why This Matters

Without dynamic guidance:
- AI forgets project conventions after 50+ messages
- Starts creating wrong note types
- Might work on multiple tasks simultaneously
- Loses track of workflow requirements

With dynamic guidance:
- Every response reinforces best practices
- AI stays consistent for hundreds of tasks
- Project standards are maintained automatically
- No "drift" even in long sessions

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## Summary - Putting It All Together

Here's how all these pieces work as a system:

1. **Projects** isolate different builds (your recipe app vs. workout tracker)
2. **Task Lists** organize features into focused workstreams
3. **Tasks** break work into hierarchical, trackable pieces
4. **Notes** capture knowledge and decisions as work happens
5. **Dynamic Guidance** keeps your AI following best practices

The beauty is that your AI handles all of this automatically through the MCP protocol. You just say "build me a recipe app" and watch the magic happen!

Each component is backed by solid PostgreSQL database design, TypeScript services, and React UI components—but you never need to worry about that. It just works! 🚀

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## Next Steps

Now that you understand how Taskr works:
1. **[Start Building](/docs/getting-started/1-1.md)** - Put this knowledge to use!