diff --git a/python/aisimulate/collector/sglang/README.md b/python/aisimulate/collector/sglang/README.md
index 3f72e5760e..4d2d33c9c9 100644
--- a/python/aisimulate/collector/sglang/README.md
+++ b/python/aisimulate/collector/sglang/README.md
@@ -163,3 +163,22 @@ communication. Use `collector/wideep/sglang/collect_deepep_moe.py` for
 Large-EP local expert compute; it publishes the dedicated `moe_ep` table.
 Stock `moe_perf` is a modeled fallback only when a matching `moe_ep` row is
 not available.
+
+## GLM agentic decode campaign
+
+`agentx_dsa_shards.yaml` selects the full-indexer and skip-indexer DSA module
+groups for `nvidia/GLM-5.2-NVFP4`, TP8, BF16 projections and FP8 KV on B300.
+The auto-collector also requires `AISIM_MODEL_FILTER=nvidia/GLM-5.2-NVFP4`
+and `AISIM_SHARDS_PER_JOB=1`. Shared sweep defaults belong in
+`cases/base_ops/mla_module.yaml`; this campaign file only selects the groups.
+
+The SGLang 0.5.21 collection used AISimulate commit
+[`0bba6709ed4ef3a0fcae878d2ad2fb61bbd11a04`](https://github.com/ai-dynamo/aisimulate/commit/0bba6709ed4ef3a0fcae878d2ad2fb61bbd11a04),
+with 250 shapes per group, through past-KV length 720,896. Reproduction must
+pin that collector revision, the runtime image digest recorded in the data
+sidecar, and the campaign's B300 capacity. Current defaults may generate a
+different plan. See collection jobs
+[full-indexer](https://gitlab-master.nvidia.com/dl/ai-dynamo/aisim-auto-collector/-/jobs/523211485)
+and [skip-indexer](https://gitlab-master.nvidia.com/dl/ai-dynamo/aisim-auto-collector/-/jobs/523211486).
+The packaged 0.5.21 table preserves previous rows and appends both collection
+events with their original source revision and plan hashes.
diff --git a/python/aisimulate/collector/sglang/agentx_dsa_shards.yaml b/python/aisimulate/collector/sglang/agentx_dsa_shards.yaml
new file mode 100644
index 0000000000..292b496c79
--- /dev/null
+++ b/python/aisimulate/collector/sglang/agentx_dsa_shards.yaml
@@ -0,0 +1,15 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+# Select two SGLang 0.5.21 module groups; 250 raw pairs per shard before the device-memory filter.
+# Historical source 3d41164034624251209588ee0284694e86a13bd8 used 110.
+# Auto-collector campaign plan. Each job must also receive
+# AISIM_MODEL_FILTER=nvidia/GLM-5.2-NVFP4 and AISIM_SHARDS_PER_JOB=1.
+backend: sglang
+sm: 103
+shards:
+  - op: dsa_generation_module
+    name: glm52_agentx_tp8_fp8
+    case_filter: "[0, 0, 8, 'fp8', 'bfloat16', 'bfloat16', 'nvidia/GLM-5.2-NVFP4', 'dsa', None, 8, 'trtllm',"
+  - op: dsa_generation_module_skip_indexer
+    name: glm52_agentx_tp8_fp8
+    case_filter: "[0, 0, 8, 'fp8', 'bfloat16', 'bfloat16', 'nvidia/GLM-5.2-NVFP4', 'dsa', None, 8, 'trtllm',"
diff --git a/python/aisimulate/src/aisimulate_core/systems/data/b300_sxm/sparse_attention/sglang/0.5.21/collection_meta.yaml b/python/aisimulate/src/aisimulate_core/systems/data/b300_sxm/sparse_attention/sglang/0.5.21/collection_meta.yaml
index 4fd57944c8..62d244c523 100644
--- a/python/aisimulate/src/aisimulate_core/systems/data/b300_sxm/sparse_attention/sglang/0.5.21/collection_meta.yaml
+++ b/python/aisimulate/src/aisimulate_core/systems/data/b300_sxm/sparse_attention/sglang/0.5.21/collection_meta.yaml
@@ -37,7 +37,7 @@ tables:
       rows: 19710
       status: complete
   dsa_generation_module_perf:
-    rows: 6120
+    rows: 6620
     status: complete
     collections:
     - collector_ref: ee219cc60e13e9f60db50b63f13bab536c598781
@@ -52,6 +52,28 @@ tables:
       collected_at: '2026-10-08'
       rows: 2464
       status: complete
+    - collector_ref: 0bba6709ed4ef3a0fcae878d2ad2fb61bbd11a04
+      collector_hash: sha256:da3ffe2ecaf850e18c082c3f0e7a218ae93150ac9e2b6ef2942e3c4365dee4e6
+      case_plan_hash: sha256:9657dad4b6bda474f3e6eb0bd463ccc54b8d3870d43f31a47414e0128c0813bc
+      collected_at: '2026-11-02'
+      rows: 250
+      status: complete
+      runtime:
+        framework: sglang
+        version: 0.5.21
+        image: lmsysorg/sglang:v0.5.21
+        image_digest: sha256:b1259f3ea3275f66237c498ea388919729018bc9f01c3d638391e06e2cf3f469
+    - collector_ref: 0bba6709ed4ef3a0fcae878d2ad2fb61bbd11a04
+      collector_hash: sha256:da3ffe2ecaf850e18c082c3f0e7a218ae93150ac9e2b6ef2942e3c4365dee4e6
+      case_plan_hash: sha256:4c84107fcf115fd4099931bbad0cfb1bbc5dc69430e60f3cebc6d38ef594ad99
+      collected_at: '2026-11-02'
+      rows: 250
+      status: complete
+      runtime:
+        framework: sglang
+        version: 0.5.21
+        image: lmsysorg/sglang:v0.5.21
+        image_digest: sha256:b1259f3ea3275f66237c498ea388919729018bc9f01c3d638391e06e2cf3f469
   dsv4_csa_context_module_perf:
     rows: 47456
     status: complete
diff --git a/python/aisimulate/src/aisimulate_core/systems/data/b300_sxm/sparse_attention/sglang/0.5.21/dsa_generation_module_perf.parquet b/python/aisimulate/src/aisimulate_core/systems/data/b300_sxm/sparse_attention/sglang/0.5.21/dsa_generation_module_perf.parquet
index f43caf1a89..6b31e2fe14 100644
Binary files a/python/aisimulate/src/aisimulate_core/systems/data/b300_sxm/sparse_attention/sglang/0.5.21/dsa_generation_module_perf.parquet and b/python/aisimulate/src/aisimulate_core/systems/data/b300_sxm/sparse_attention/sglang/0.5.21/dsa_generation_module_perf.parquet differ