This PR updates subagent ID generation to use short 8-character hex
strings instead of full UUID v4 strings. Previously, subagent IDs were
36-character UUIDs (e.g. `550e8400-e29b-41d4-a716-446655440000`), which
were verbose in CLI output and unwieldy when the LLM needed to reference
them in tools like `send_input`, `wait`, and `close_agent`. The new
format generates IDs like `a3f1b20c` — compact, human-readable, and with
~4 billion possible values, effectively collision-free within a session.
The change is made at the source in `subagent.rs`, where UUID generation
is replaced with `format!("{:08x}",
uuid::Uuid::new_v4().as_fields().0)`. Because IDs are now inherently 8
characters, the display-layer truncations in `cli.rs` (5 occurrences)
and `run_progress.rs` (2 occurrences) are redundant and have been
removed — `agent_id` is used directly in format strings instead of a
`short_id` slice.
### Plan Summary
- **Replace UUID generation** in `subagent.rs`: use the first field of a
UUID v4 formatted as 8-char lowercase hex, yielding IDs like `a3f1b20c`
instead of full 36-char UUIDs
- **Remove `short_id` truncation** in `cli.rs` (5 places) and
`run_progress.rs` (2 places): since IDs are now already 8 chars, the
`let short_id = &agent_id[..8.min(agent_id.len())]` pattern is
eliminated and `{agent_id}` is used directly in all format strings
- No test changes required — existing tests use hardcoded IDs like
`"sa-1"` and don't assert on ID length or format
<details>
<summary>Full plan</summary>
````md
The plan has been written to `/home/daytona/workspace/plan.md`.
It covers:
- **4 files to modify**: `fabro-agent/Cargo.toml` (add `rand` dep), `subagent.rs` (replace UUID with 8-char hex), `cli.rs` (remove 5 `short_id` truncations), `run_progress.rs` (remove 2 `short_id` truncations)
- **Step-by-step implementation** with exact line references and before/after code
- **Verification commands** to confirm correctness
- **Test case analysis** explaining why no test changes are needed
````
</details>
### Fabro Details
<details>
<summary>Ran 3 stages in 18m 46s for $0.57</summary>
| Stage | Duration | Cost | Retries |
|---|---|---|---|
| start | 0s | – | 0 |
| plan | 1m 28s | $0.57 | 0 |
| implement | 17m 6s | – | 0 |
| **Total** | **18m 46s** | **$0.57** | **0** |
</details>
<details>
<summary>Ran <code>GhImplement.fabro</code> (4 nodes and 3
edges)</summary>
```dot
digraph GhImplement {
graph [
goal="Implement a GitHub issue",
model_stylesheet="
* { model: claude-opus-4-6; }
"
]
rankdir=LR
start [shape=Mdiamond, label="Start"]
exit [shape=Msquare, label="Exit"]
plan [label="Plan", prompt="Fetch the GitHub issue from the goal using: gh issue view $goal --json title,body,labels,comments\n\nRead the issue title, description, and any comments carefully. Analyze what code changes are needed to resolve the issue.\n\nWrite a detailed implementation plan to plan.md that includes:\n- Summary of the issue\n- Files to create or modify\n- Step-by-step implementation approach\n- Test cases to add or update\n\nThe plan should be specific enough for another agent to implement without seeing the original issue.\n\nRespond with the location of the plan file (plan.md)."]
implement [label="Implement", shape=house, stack.child_workflow="fabro/workflows/implement/workflow.fabro", manager.max_cycles=100]
start -> plan
plan -> implement [fidelity="summary:high"]
implement -> exit
}
```
</details>
⚒️ Generated with [Fabro](https://fabro.sh)
---------
Co-authored-by: Fabro <noreply@fabro.sh>
