What changed: In the VLLM_CMD array construction (around lines 328-350 of benchmarks/single_node/agentic/dsv4_fp4_b200_vllm.sh), the diff removes --tool-call-parser deepseek_v4 and --enable-auto-tool-choice while keeping the adjacent --reasoning-parser deepseek_v4 flag. The pre-PR version of this exact file had both flags (visible as removed lines in the diff), so this is not a case of the recipe never having them — they were explicitly dropped during the VLLM_CMD rewrite that pulled in the #2224 tuned recipe.

Why this is inconsistent with the rest of the repo: Every other agentic-coding vLLM recipe sets both flags together: dsv4_fp4_b300_vllm.sh (lines 209-210), dsv4_fp4_mi355x_vllm.sh (lines 396/398), and dsv4_fp8_h200.sh (lines 63-64) — confirmed directly by grepping those files. The minimax and kimi vLLM agentic recipes follow the same pattern. The PR description states the b200 script 'adopts the #2224 tuned recipe verbatim,' but #2224's own b300 sibling keeps both flags, so this omission is specific to the b200 rewrite and not an intentional nightly-vLLM behavior change.

Why nothing else in the script prevents this from mattering: The workload driven by build_replay_cmd/run_agentic_replay_and_write_outputs is the inferencex-agentx-mvp coding-agent trace replay, which is fundamentally tool-calling — requests are reconstructed with a tools schema and tool_choice. vLLM does not enable auto tool-choice/parsing by default; when a request specifies tool_choice=auto and the server wasn't started with --enable-auto-tool-choice (paired with a --tool-call-parser), vLLM returns an HTTP 400 ('auto tool choice requires --enable-auto-tool-choice and --tool-call-parser'). This is a request-level rejection, independent of whether the replay's default pre-canned mode discards live assistant responses — the request still needs to succeed for aiperf to count it as a valid data point.

Step-by-step proof of impact:

1. The lmcache-arm (and every other arm: none/vllm-simple/mooncake) all share this single VLLM_CMD — none of the offload-backend case branches add tool-call flags.
2. vLLM starts successfully (these flags don't affect startup), so wait_for_server_ready passes and the sweep proceeds to the replay phase.
3. build_replay_cmd issues chat-completion requests for the AgentX coding-agent trace with a tools array and tool_choice=auto (required to reproduce realistic input-token counts for tool-augmented turns).
4. Because --enable-auto-tool-choice/--tool-call-parser are absent, vLLM rejects essentially all such requests with a 400.
5. aiperf's --failed-request-threshold (10%, per AIPERF_FAILED_REQUEST_THRESHOLD) is exceeded almost immediately, failing the run for all 14 lmcache sweep points plus the parent vllm-simple/mooncake points that share the same script.

Fix: Re-add --tool-call-parser deepseek_v4 and --enable-auto-tool-choice to the shared VLLM_CMD array (near --reasoning-parser deepseek_v4), matching the pre-PR file and every sibling recipe.

The bug: The new lmcache case in dsv4_fp4_b200_vllm.sh (lines 285-289) builds OFFLOAD_ARGS as:

"{\"kv_connector\":\"LMCacheMPConnector\",\"kv_role\":\"kv_both\",\"kv_connector_extra_config\":{...}}"

This is missing the kv_connector_module_path key. LMCacheMPConnector is shipped by the lmcache pip package (installed a few lines earlier via agentic_pip_install ... lmcache==$LMCACHE_VERSION), not by vLLM itself. vLLM'''s built-in KVConnectorFactory only knows connector classes it ships in-tree by bare name; to resolve an out-of-tree connector class, it needs to dynamically import the module named by kv_connector_module_path and then look up kv_connector as a class name inside that module. Without the module path, vLLM falls back to its built-in name registry, which has no entry for LMCacheMPConnector, and connector construction fails at vllm serve startup.

Why the existing sanity check doesn'''t catch it: The script runs python3 -c \"import lmcache.integration.vllm.lmcache_mp_connector\" >/dev/null a few lines before launching the server. That only proves the module is importable in a throwaway Python process — it does not register the connector with vLLM'''s factory in the actual vllm serve process, so it provides no protection against this specific misconfiguration.

Cross-script evidence: Both other scripts in this repo that wire up the identical LMCacheMPConnector include the field explicitly and consistently:

• benchmarks/single_node/agentic/kimik2.5_fp4_b200.sh:150: \"kv_connector\":\"LMCacheMPConnector\",\"kv_connector_module_path\":\"lmcache.integration.vllm.lmcache_mp_connector\",...
• benchmarks/single_node/agentic/dsv4_fp4_mi355x_vllm.sh:344: same field, same value, otherwise near byte-for-byte the same JSON shape (same lmcache.mp.host/lmcache.mp.port extra_config keys).

The new B200 arm is the only place in the codebase wiring LMCacheMPConnector without this field, strongly suggesting it was simply dropped rather than being some new supported invocation.

Impact: This is not a subtle perf regression — it'''s a hard startup crash. Every one of the 14 lmcache sweep points defined in configs/nvidia-master.yaml (dsv4-fp4-b200-vllm-agentic-lmcache: 3 TP8 points + 11 TP8-DEP8 points) launches vllm serve with this malformed --kv-transfer-config, so the server process would fail while constructing the KV connector, before any benchmark traffic is served. This defeats the entire purpose of the PR, which is to add this lmcache arm for comparison against vllm-simple and Mooncake.

Step-by-step proof:

1. KV_OFFLOAD_BACKEND=lmcache is set for a sweep point; the script enters the lmcache) case at line ~230.
2. The LMCache MP server starts and becomes healthy (this part is unaffected — it'''s a separate process from vLLM).
3. OFFLOAD_ARGS is built at line 285-289 as --kv-transfer-config '\''{\"kv_connector\":\"LMCacheMPConnector\",\"kv_role\":\"kv_both\",...}'\'' — no kv_connector_module_path.
4. vllm serve is launched with this flag (line ~372, via \"${OFFLOAD_ARGS[@]}\").
5. vLLM parses --kv-transfer-config, sees kv_connector=\"LMCacheMPConnector\" with no module path, and attempts to resolve it against its built-in registry (which contains e.g. LMCacheConnectorV1 but not LMCacheMPConnector).
6. Resolution fails, and vllm serve exits/crashes during connector construction, before the health-check endpoint ever comes up — wait_for_server_ready at the bottom of the script will time out and the whole benchmark point fails.

Why this wasn'''t caught: The PR description explicitly says validation was only bash -n (syntax check) and generate_sweep_configs.py full-sweep (config generation), neither of which launches an actual vLLM server, so this startup failure was never exercised.

Fix: add \"kv_connector_module_path\":\"lmcache.integration.vllm.lmcache_mp_connector\" to the JSON at line 288, matching the sibling scripts exactly.