OpenAI /v1/chat/completions tool rounds never hit live continuation (match=tool-output-ids); live slot discarded despite full-prompt common

On the Anthropic endpoint, tool rounds continue the live KV slot cheaply (`anthropic live continuation match=tool-output-ids`, delta-only prefill — see #500 for a working example at 85K context with 400–900 token deltas). On the OpenAI chat/completions endpoint, the equivalent never happens: every tool round logs a live miss where `common` equals the entire previous prompt, the live slot is discarded, and prefill restarts from the oldest disk checkpoint.

Example (Open WebUI, native function calling, OpenAI protocol — four consecutive tool rounds in one conversation):

```
live kv cache miss live=6034 prompt=6128 common=5817 reason=token-mismatch
kv cache stored tokens=6034 trimmed=0 reason=evict key=token-text size=102.08 MiB save=16.6 ms
chat ctx=5779..6128:349 TOOLS prompt done 1.857s
live kv cache miss live=6213 prompt=8238 common=6128 reason=token-mismatch
kv cache stored tokens=6213 trimmed=0 reason=evict key=token-text size=104.43 MiB save=16.5 ms
chat ctx=5779..8238:2459 TOOLS prompt done 9.231s
live kv cache miss live=8633 prompt=14903 common=8238 reason=token-mismatch
kv cache stored tokens=8633 trimmed=0 reason=evict key=token-text size=136.21 MiB save=15.1 ms
chat ctx=5779..14903:9124 TOOLS prompt done 31.253s
live kv cache miss live=15139 prompt=20460 common=14903 reason=token-mismatch
kv cache stored tokens=15139 trimmed=0 reason=evict key=token-text size=221.61 MiB save=25.7 ms
```

Note the pattern: `common` always reaches exactly the previous prompt's end (6128, 8238, 14903), because the only divergence is the re-serialised assistant tool-call turn — the client strips thinking to an empty `` and re-encodes the tool call in OpenAI JSON format. Instead of rolling back to `common` and prefilling the delta, the live slot is discarded and prefill restarts from the system-prompt disk checkpoint (5779), so each round pays (context − 5779) tokens. At ~90K context this compounds to ~6-minute tool rounds.

The evicted snapshots store the divergent generated tail untrimmed (`trimmed=0` — this persists with `--kv-cache-boundary-trim-tokens 1024`, which appears to only affect cold-path saves), so they accumulate with `hits=0` and evict each other; only the system-prompt checkpoint ever hits.

Exact DSML tool replay is active and reports healthy: tool-call lines show `raw_tool_text=1`, and `--trace` shows `tool_replay: mem=N disk=0 canonical=0 missing_ids=0` with correct `call_*` IDs present in the replayed request.

A rollback-to-common on the live slot, or an OpenAI-path equivalent of the `tool-output-ids` continuation matching on `tool_call_id`, would reduce these rounds to delta-only prefill like the Anthropic path.

**Environment**

- ds4: main @ 0a7ad77
- macOS 26.5.2, Apple M5 Max, 128 GB
- Model: `DeepSeek-V4-Flash-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-chat-v2.gguf` (fully resident, no SSD streaming)
- Launch: `./ds4-server -m --ctx 100000 --kv-disk-dir ~/.cache/ds4-kv --kv-disk-space-mb 8192 --kv-cache-boundary-trim-tokens 1024 --host 127.0.0.1 --port 8300`
- Client: Open WebUI 0.10.2, Native function calling, streaming, `stream_options.include_usage`

Happy to test a branch — this setup reproduces the pattern on every multi-round tool conversation.