feat: add Prometheus metric for agent first connection duration (#24179)

## Summary

Add `coderd_agents_first_connection_seconds` histogram metric that
records the
duration from workspace agent creation to first connection. This fills
an
observability gap — provisioner job timings and startup script metrics
exist,
but the agent connection phase (which can take several minutes) was not
exposed
to Prometheus.

Closes https://github.com/coder/coder/issues/21282

## Changes

- **`coderd/prometheusmetrics/prometheusmetrics.go`** — Define and
register a
  `HistogramVec` in the existing `Agents()` polling loop. Observe
`first_connected_at - created_at` exactly once per agent via a
deduplication
  map, pruned each tick to prevent unbounded memory growth.
- **`coderd/prometheusmetrics/prometheusmetrics_test.go`** — Update
`TestAgents`
to set `first_connected_at` on the test agent and assert the histogram
is
  collected with correct labels, sample count, and sample sum.
- **`docs/admin/integrations/prometheus.md`**,
**`scripts/metricsdocgen/generated_metrics`** —
  Auto-generated documentation updates from `make gen`.

## Metric details

| Property | Value |
|---|---|
| Name | `coderd_agents_first_connection_seconds` |
| Type | histogram |
| Labels | `template_name`, `agent_name`, `username`, `workspace_name` |
| Buckets | 1s, 10s, 30s, 1m, 2m, 5m, 10m, 30m, 1h |

## Example PromQL

```promql
# P95 agent connection time by template
histogram_quantile(0.95,
  sum(rate(coderd_agents_first_connection_seconds_bucket[1h])) by (le, template_name)
)
```

<details>
<summary>Implementation notes</summary>

### Design decisions

- **Histogram over gauge**: Enables `histogram_quantile()` for
percentile queries.
- **Observe in `Agents()` polling loop**: All required data is already
fetched by
  `GetWorkspaceAgentsForMetrics()` — no new DB queries.
- **Dedup via `map[uuid.UUID]struct{}`**: Prevents re-observing the same
agent
  across polling ticks. Pruned each cycle to bound memory.
- **Buckets**: Aligned with
`coderd_provisionerd_workspace_build_timings_seconds`
  range (1s–1h).

### Overhead at scale (100k active workspaces)

The deduplication map (`observedFirstConnection`) and per-tick pruning
map
(`currentAgentIDs`) are both `map[[16]byte]struct{}`. At 100k agents:

- **Memory**: ~2.25 MB persistent + ~2.25 MB transient per tick = **~4.5
MB peak**.
- **CPU**: ~25 ms of map operations per tick (one tick per minute) =
**<0.05% of one core**.

Both are negligible relative to the existing cost of the `Agents()` loop
(the DB
query, per-agent `GetWorkspaceAppsByAgentID` calls, and coordinator node
lookups
dominate).

</details>

> 🤖 Generated by Coder Agents

scripts/metricsdocgen/generated_metrics

@@ -157,6 +157,9 @@ coderd_agents_connection_latencies_seconds{agent_name="",username="",workspace_n
 # HELP coderd_agents_connections Agent connections with statuses.
 # TYPE coderd_agents_connections gauge
 coderd_agents_connections{agent_name="",username="",workspace_name="",status="",lifecycle_state="",tailnet_node=""} 0
+# HELP coderd_agents_first_connection_seconds Duration from agent creation to first connection to the control plane in seconds.
+# TYPE coderd_agents_first_connection_seconds histogram
+coderd_agents_first_connection_seconds{template_name="",agent_name="",username="",workspace_name=""} 0
 # HELP coderd_agents_up The number of active agents per workspace.
 # TYPE coderd_agents_up gauge
 coderd_agents_up{username="",workspace_name="",template_name="",template_version=""} 0