Replace DOWNSTREAM panel with a project tree view so agents always know their position in the workflow

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### Syncless version
Latest

### Platform / Device
- Web (Browser)
- macOS Desktop App

### Steps to reproduce
1. Start a project from a template.
2. An agent completes its assigned stage.
3. Observe that the agent does not proceed to delegate the next node — it either stops, asks for guidance, or takes an incorrect action, because it has no clear awareness of where it sits in the overall workflow.

### ✔️ Expected Behavior
The agent should always have clear awareness of its position in the project workflow and what comes next. After completing its stage, it should know which node to delegate to.

To support this, the **DOWNSTREAM panel should be replaced with a full project tree view** that:
- Renders the entire template graph as a tree (or DAG) for the current project.
- Highlights / marks the node currently being executed.
- Shows the downstream nodes the agent is expected to hand off to next.

This gives the agent (and the human) a persistent, unambiguous map of "where am I and what's next" — reducing the chance of the agent losing its place in the workflow.

### ❌ Actual Behavior
The agent frequently does not know what to do after completing its stage. Without a clear view of the workflow graph, it has no reliable signal that it should delegate to a specific next node, causing the workflow to stall or go off-track.

### Additional context
Split from #150 (Issue 2). The root cause is that the agent lacks sufficient structural awareness of the template graph it is operating within. Replacing the flat DOWNSTREAM list with a project tree view gives both the agent and the human a persistent orientation anchor.

Start by reproducing the template workflow and inspecting how the current DOWNSTREAM panel exposes the active stage and next handoff. Trace the project template graph and agent delegation flow, then verify that the full tree renders, marks the executing node, and identifies the expected downstream nodes for both the agent and human.

Written by the indexing model from the issue text.