Add commit-pinned reproducible sweep manifests

README.md

@@ -61,12 +61,15 @@ Run all targets without downloading model weights:
 ```bash
 toolcall-lint-sweep benchmarks/transformers-45419.json \
   --json-output reports/transformers-45419.json \
-  --markdown-output reports/transformers-45419.md
+  --markdown-output reports/transformers-45419.md \
+  --lock-output reports/transformers-45419.lock.json
 ```
 
 Each model is isolated: gated, missing, or incompatible repositories become
 `load_error` rows and do not abort the dataset. Contract failures are recorded
 separately. Use `--strict` when either condition should fail CI.
+The regular manifest tracks current Hub state; the generated lock manifest pins
+resolved commits for an exact rerun.
 
 ### Measured baseline (2026-08-19)
 
@@ -85,7 +88,9 @@ Key observations:
 
 See the compact [compatibility matrix](data/baseline-2026-08-19.md) and the
 [full machine-readable evidence](data/baseline-2026-08-19.json). Every loaded
-row records the resolved Hub commit and the chat-template SHA-256.
+row records the resolved Hub commit and the chat-template SHA-256. The
+[commit-pinned manifest](benchmarks/transformers-45419.lock.json) reproduces
+the accessible portion of this baseline exactly.
 
 ## Hugging Face Space
 

benchmarks/transformers-45419.lock.json

@@ -0,0 +1,105 @@
+{
+  "description": "Commit-pinned manifest generated by toolcall-lint-sweep.",
+  "contract_version": "2026-08-mvp1",
+  "generated_at": "2026-08-19T10:56:59.206374+00:00",
+  "models": [
+    {
+      "label": "DeepSeekV3",
+      "model_id": "deepseek-ai/DeepSeek-R1",
+      "revision": "56d4cbbb4d29f4355bab4b9a39ccb717a14ad5ad"
+    },
+    {
+      "label": "DeepSeekV3-0528",
+      "model_id": "deepseek-ai/DeepSeek-R1-0528",
+      "revision": "4236a6af538feda4548eca9ab308586007567f52"
+    },
+    {
+      "label": "EXAONE-4.5",
+      "model_id": "LGAI-EXAONE/EXAONE-4.5-33B",
+      "revision": "570aa4b15a4f45ba1133072b45f50198f6e3b4fd"
+    },
+    {
+      "label": "Gemma4",
+      "model_id": "google/gemma-4-E2B-it",
+      "revision": "3e22461f65e89153144f8adb70e3b8c2cc9845a7"
+    },
+    {
+      "label": "GLM-5.1",
+      "model_id": "zai-org/GLM-5.1",
+      "revision": "26e1bd6e011feb778d25ae34b09b07074139d92d"
+    },
+    {
+      "label": "GLM4MOE",
+      "model_id": "zai-org/GLM-4.5",
+      "revision": "cbb2c7cfb52fa128a9660cb1a7a78e017899e115"
+    },
+    {
+      "label": "GptOSS",
+      "model_id": "openai/gpt-oss-20b",
+      "revision": "6cee5e81ee83917806bbde320786a8fb61efebee"
+    },
+    {
+      "label": "Holo3",
+      "model_id": "Hcompany/Holo3-35B-A3B",
+      "revision": "208d5ae3a03f99d561f32ab5e606f73397a390ea"
+    },
+    {
+      "label": "LFM2.5-VL",
+      "model_id": "LiquidAI/LFM2.5-VL-450M",
+      "revision": "fc6221ca597f3315e4f82fc2df606783267b34ba"
+    },
+    {
+      "label": "Llama3.1",
+      "model_id": "meta-llama/Llama-3.1-8B-Instruct"
+    },
+    {
+      "label": "Llama3.2",
+      "model_id": "meta-llama/Llama-3.2-1B-Instruct"
+    },
+    {
+      "label": "Marco-Mini",
+      "model_id": "AIDC-AI/Marco-Mini-Instruct",
+      "revision": "a85af582f1a2384e1eb3b3c8b03466e190403879"
+    },
+    {
+      "label": "MiniMax-M2.5",
+      "model_id": "MiniMaxAI/MiniMax-M2.5",
+      "revision": "f710177d938eff80b684d42c5aa84b382612f21f"
+    },
+    {
+      "label": "MiniMax-M2.7",
+      "model_id": "MiniMaxAI/MiniMax-M2.7",
+      "revision": "d494266a4affc0d2995ba1fa35c8481cbd84294b"
+    },
+    {
+      "label": "Qwen2.5",
+      "model_id": "Qwen/Qwen2.5-32B-Instruct",
+      "revision": "5ede1c97bbab6ce5cda5812749b4c0bdf79b18dd"
+    },
+    {
+      "label": "Qwen3",
+      "model_id": "Qwen/Qwen3-8B",
+      "revision": "b968826d9c46dd6066d109eabc6255188de91218"
+    },
+    {
+      "label": "Qwen3-Coder",
+      "model_id": "Qwen/Qwen3-Coder-Next",
+      "revision": "a7fbcb5c0e12d62a448eaa0e260346bf5dcc0feb"
+    },
+    {
+      "label": "Qwen3MOE",
+      "model_id": "Qwen/Qwen3-30B-A3B",
+      "revision": "ad44e777bcd18fa416d9da3bd8f70d33ebb85d39"
+    },
+    {
+      "label": "Qwen3VL",
+      "model_id": "Qwen/Qwen3-VL-2B-Instruct",
+      "revision": "89644892e4d85e24eaac8bacfd4f463576704203"
+    },
+    {
+      "label": "Qwen3.5",
+      "model_id": "Qwen/Qwen3.5-0.8B",
+      "revision": "2fc06364715b967f1860aea9cf38778875588b17"
+    }
+  ]
+}

data/baseline-2026-08-19.json

@@ -1,8 +1,14 @@
 {
   "schema_version": "1.0",
   "contract_version": "2026-08-mvp1",
-  "generated_at": "2026-08-19T10:50:18.474746+00:00",
+  "generated_at": "2026-08-19T10:56:59.206374+00:00",
   "loads_model_weights": false,
+  "environment": {
+    "python": "3.14.4",
+    "platform": "macOS-26.4.1-arm64-arm-64bit-Mach-O",
+    "toolcall_lint": "0.1.0",
+    "transformers": "5.15.0"
+  },
   "summary": {
     "targets": 20,
     "loaded": 18,
@@ -16,7 +22,7 @@
       "model_id": "deepseek-ai/DeepSeek-R1",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "56d4cbbb4d29f4355bab4b9a39ccb717a14ad5ad",
       "template_sha256": "563b1ce7d61d50a9b4c7439a912a1116f095b712df5b5e4d3e1116049874eb64",
       "status": "contract_fail",
       "score": 20,
@@ -38,7 +44,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "563b1ce7d61d50a9b4c7439a912a1116f095b712df5b5e4d3e1116049874eb64",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "56d4cbbb4d29f4355bab4b9a39ccb717a14ad5ad",
           "tokenizer_class": "TokenizersBackend",
           "transformers_version": "5.15.0"
         },
@@ -123,14 +129,14 @@
           }
         ]
       },
-      "elapsed_seconds": 4.003
+      "elapsed_seconds": 4.103
     },
     {
       "label": "DeepSeekV3-0528",
       "model_id": "deepseek-ai/DeepSeek-R1-0528",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "4236a6af538feda4548eca9ab308586007567f52",
       "template_sha256": "53671bac29bcb3e1f95f51b8c77d85a6011b66dc38bd23dce64eef04384a976b",
       "status": "contract_fail",
       "score": 20,
@@ -152,7 +158,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "53671bac29bcb3e1f95f51b8c77d85a6011b66dc38bd23dce64eef04384a976b",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "4236a6af538feda4548eca9ab308586007567f52",
           "tokenizer_class": "TokenizersBackend",
           "transformers_version": "5.15.0"
         },
@@ -237,14 +243,14 @@
           }
         ]
       },
-      "elapsed_seconds": 1.63
+      "elapsed_seconds": 2.423
     },
     {
       "label": "EXAONE-4.5",
       "model_id": "LGAI-EXAONE/EXAONE-4.5-33B",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "570aa4b15a4f45ba1133072b45f50198f6e3b4fd",
       "template_sha256": "e4ece7acc79ba82121d4d57791fb7ecb796e39185087197377da5d2286bec0e5",
       "status": "contract_pass",
       "score": 98,
@@ -266,7 +272,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "e4ece7acc79ba82121d4d57791fb7ecb796e39185087197377da5d2286bec0e5",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "570aa4b15a4f45ba1133072b45f50198f6e3b4fd",
           "tokenizer_class": "TokenizersBackend",
           "transformers_version": "5.15.0"
         },
@@ -354,14 +360,14 @@
           }
         ]
       },
-      "elapsed_seconds": 1.825
+      "elapsed_seconds": 2.226
     },
     {
       "label": "Gemma4",
       "model_id": "google/gemma-4-E2B-it",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "3e22461f65e89153144f8adb70e3b8c2cc9845a7",
       "template_sha256": "0a2c8073c878ab1da004bee933a998606537bbb62016310352c7285c3f01c5b5",
       "status": "contract_pass",
       "score": 98,
@@ -383,7 +389,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "0a2c8073c878ab1da004bee933a998606537bbb62016310352c7285c3f01c5b5",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "3e22461f65e89153144f8adb70e3b8c2cc9845a7",
           "tokenizer_class": "GemmaTokenizer",
           "transformers_version": "5.15.0"
         },
@@ -469,14 +475,14 @@
           }
         ]
       },
-      "elapsed_seconds": 2.562
+      "elapsed_seconds": 3.132
     },
     {
       "label": "GLM-5.1",
       "model_id": "zai-org/GLM-5.1",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "26e1bd6e011feb778d25ae34b09b07074139d92d",
       "template_sha256": "03b1bbff20331e54647c68167e8ac7f0b5b7ceb40ead372f44826624a9ad79cd",
       "status": "contract_fail",
       "score": 79,
@@ -498,7 +504,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "03b1bbff20331e54647c68167e8ac7f0b5b7ceb40ead372f44826624a9ad79cd",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "26e1bd6e011feb778d25ae34b09b07074139d92d",
           "tokenizer_class": "TokenizersBackend",
           "transformers_version": "5.15.0"
         },
@@ -589,14 +595,14 @@
           }
         ]
       },
-      "elapsed_seconds": 2.036
+      "elapsed_seconds": 2.998
     },
     {
       "label": "GLM4MOE",
       "model_id": "zai-org/GLM-4.5",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "cbb2c7cfb52fa128a9660cb1a7a78e017899e115",
       "template_sha256": "44f815868bf02fa458dd2f741a338046f4bf45f398eb6d067766726b9d96cce3",
       "status": "contract_fail",
       "score": 79,
@@ -618,7 +624,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "44f815868bf02fa458dd2f741a338046f4bf45f398eb6d067766726b9d96cce3",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "cbb2c7cfb52fa128a9660cb1a7a78e017899e115",
           "tokenizer_class": "TokenizersBackend",
           "transformers_version": "5.15.0"
         },
@@ -710,14 +716,14 @@
           }
         ]
       },
-      "elapsed_seconds": 1.909
+      "elapsed_seconds": 2.757
     },
     {
       "label": "GptOSS",
       "model_id": "openai/gpt-oss-20b",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "6cee5e81ee83917806bbde320786a8fb61efebee",
       "template_sha256": "a4c9919cbbd4acdd51ccffe22da049264b1b73e59055fa58811a99efbd7c8146",
       "status": "contract_fail",
       "score": 74,
@@ -739,7 +745,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "a4c9919cbbd4acdd51ccffe22da049264b1b73e59055fa58811a99efbd7c8146",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "6cee5e81ee83917806bbde320786a8fb61efebee",
           "tokenizer_class": "TokenizersBackend",
           "transformers_version": "5.15.0"
         },
@@ -830,14 +836,14 @@
           }
         ]
       },
-      "elapsed_seconds": 2.086
+      "elapsed_seconds": 3.213
     },
     {
       "label": "Holo3",
       "model_id": "Hcompany/Holo3-35B-A3B",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "208d5ae3a03f99d561f32ab5e606f73397a390ea",
       "template_sha256": "a4aee8afcf2e0711942cf848899be66016f8d14a889ff9ede07bca099c28f715",
       "status": "contract_pass",
       "score": 98,
@@ -859,7 +865,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "a4aee8afcf2e0711942cf848899be66016f8d14a889ff9ede07bca099c28f715",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "208d5ae3a03f99d561f32ab5e606f73397a390ea",
           "tokenizer_class": "Qwen2Tokenizer",
           "transformers_version": "5.15.0"
         },
@@ -944,14 +950,14 @@
           }
         ]
       },
-      "elapsed_seconds": 1.574
+      "elapsed_seconds": 1.88
     },
     {
       "label": "LFM2.5-VL",
       "model_id": "LiquidAI/LFM2.5-VL-450M",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "fc6221ca597f3315e4f82fc2df606783267b34ba",
       "template_sha256": "309e586e2eda3d7f2db1e2a045bfb07f4c83798b23f7ac587954426302d508e9",
       "status": "contract_fail",
       "score": 79,
@@ -973,7 +979,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "309e586e2eda3d7f2db1e2a045bfb07f4c83798b23f7ac587954426302d508e9",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "fc6221ca597f3315e4f82fc2df606783267b34ba",
           "tokenizer_class": "TokenizersBackend",
           "transformers_version": "5.15.0"
         },
@@ -1060,7 +1066,7 @@
           }
         ]
       },
-      "elapsed_seconds": 1.097
+      "elapsed_seconds": 1.372
     },
     {
       "label": "Llama3.1",
@@ -1074,7 +1080,7 @@
         "message": "You are trying to access a gated repo.\nMake sure to have access to it at https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct.\n403 Client Error.\n\nCannot access gated repo for url https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct/resolve/main/config.json.\nAccess to model meta-llama/Llama-3.1-8B-Instruct is restricted and you are not in the authorized list. Visit https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct to ask for access."
       },
       "report": null,
-      "elapsed_seconds": 0.352
+      "elapsed_seconds": 0.336
     },
     {
       "label": "Llama3.2",
@@ -1088,14 +1094,14 @@
         "message": "You are trying to access a gated repo.\nMake sure to have access to it at https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct.\n403 Client Error.\n\nCannot access gated repo for url https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct/resolve/main/config.json.\nAccess to model meta-llama/Llama-3.2-1B-Instruct is restricted and you are not in the authorized list. Visit https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct to ask for access."
       },
       "report": null,
-      "elapsed_seconds": 0.304
+      "elapsed_seconds": 0.318
     },
     {
       "label": "Marco-Mini",
       "model_id": "AIDC-AI/Marco-Mini-Instruct",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "a85af582f1a2384e1eb3b3c8b03466e190403879",
       "template_sha256": "64f85b198065d0fba2a81f37e10ed68161ce2c19a754c7100e67e0ca2ee9c326",
       "status": "contract_pass",
       "score": 100,
@@ -1117,7 +1123,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "64f85b198065d0fba2a81f37e10ed68161ce2c19a754c7100e67e0ca2ee9c326",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "a85af582f1a2384e1eb3b3c8b03466e190403879",
           "tokenizer_class": "Qwen2Tokenizer",
           "transformers_version": "5.15.0"
         },
@@ -1198,14 +1204,14 @@
           }
         ]
       },
-      "elapsed_seconds": 1.97
+      "elapsed_seconds": 2.188
     },
     {
       "label": "MiniMax-M2.5",
       "model_id": "MiniMaxAI/MiniMax-M2.5",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "f710177d938eff80b684d42c5aa84b382612f21f",
       "template_sha256": "f83cec52bb3a7e5a3cb4d6fd1dfdd6f4fe13b06c5aaa39a1115e70a417fc75f5",
       "status": "contract_fail",
       "score": 79,
@@ -1227,7 +1233,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "f83cec52bb3a7e5a3cb4d6fd1dfdd6f4fe13b06c5aaa39a1115e70a417fc75f5",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "f710177d938eff80b684d42c5aa84b382612f21f",
           "tokenizer_class": "TokenizersBackend",
           "transformers_version": "5.15.0"
         },
@@ -1318,14 +1324,14 @@
           }
         ]
       },
-      "elapsed_seconds": 2.047
+      "elapsed_seconds": 2.456
     },
     {
       "label": "MiniMax-M2.7",
       "model_id": "MiniMaxAI/MiniMax-M2.7",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "d494266a4affc0d2995ba1fa35c8481cbd84294b",
       "template_sha256": "893d908f7b5cc65fdde270dcae5ea1a99647c6a7ce572ae874a57b7160069566",
       "status": "contract_fail",
       "score": 79,
@@ -1347,7 +1353,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "893d908f7b5cc65fdde270dcae5ea1a99647c6a7ce572ae874a57b7160069566",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "d494266a4affc0d2995ba1fa35c8481cbd84294b",
           "tokenizer_class": "TokenizersBackend",
           "transformers_version": "5.15.0"
         },
@@ -1438,14 +1444,14 @@
           }
         ]
       },
-      "elapsed_seconds": 2.292
+      "elapsed_seconds": 2.558
     },
     {
       "label": "Qwen2.5",
       "model_id": "Qwen/Qwen2.5-32B-Instruct",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "5ede1c97bbab6ce5cda5812749b4c0bdf79b18dd",
       "template_sha256": "cd8e9439f0570856fd70470bf8889ebd8b5d1107207f67a5efb46e342330527f",
       "status": "contract_pass",
       "score": 95,
@@ -1467,7 +1473,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "cd8e9439f0570856fd70470bf8889ebd8b5d1107207f67a5efb46e342330527f",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "5ede1c97bbab6ce5cda5812749b4c0bdf79b18dd",
           "tokenizer_class": "Qwen2Tokenizer",
           "transformers_version": "5.15.0"
         },
@@ -1550,14 +1556,14 @@
           }
         ]
       },
-      "elapsed_seconds": 1.189
+      "elapsed_seconds": 1.44
     },
     {
       "label": "Qwen3",
       "model_id": "Qwen/Qwen3-8B",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "b968826d9c46dd6066d109eabc6255188de91218",
       "template_sha256": "a55ee1b1660128b7098723e0abcd92caa0788061051c62d51cbe87d9cf1974d8",
       "status": "contract_pass",
       "score": 95,
@@ -1579,7 +1585,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "a55ee1b1660128b7098723e0abcd92caa0788061051c62d51cbe87d9cf1974d8",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "b968826d9c46dd6066d109eabc6255188de91218",
           "tokenizer_class": "Qwen2Tokenizer",
           "transformers_version": "5.15.0"
         },
@@ -1667,14 +1673,14 @@
           }
         ]
       },
-      "elapsed_seconds": 1.361
+      "elapsed_seconds": 1.824
     },
     {
       "label": "Qwen3-Coder",
       "model_id": "Qwen/Qwen3-Coder-Next",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "a7fbcb5c0e12d62a448eaa0e260346bf5dcc0feb",
       "template_sha256": "c79a833039a43602150cce0902403d6e376c50930c1b2a139b2964e1f0c322a0",
       "status": "contract_pass",
       "score": 100,
@@ -1696,7 +1702,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "c79a833039a43602150cce0902403d6e376c50930c1b2a139b2964e1f0c322a0",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "a7fbcb5c0e12d62a448eaa0e260346bf5dcc0feb",
           "tokenizer_class": "Qwen2Tokenizer",
           "transformers_version": "5.15.0"
         },
@@ -1775,14 +1781,14 @@
           }
         ]
       },
-      "elapsed_seconds": 1.392
+      "elapsed_seconds": 1.36
     },
     {
       "label": "Qwen3MOE",
       "model_id": "Qwen/Qwen3-30B-A3B",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "ad44e777bcd18fa416d9da3bd8f70d33ebb85d39",
       "template_sha256": "a55ee1b1660128b7098723e0abcd92caa0788061051c62d51cbe87d9cf1974d8",
       "status": "contract_pass",
       "score": 95,
@@ -1804,7 +1810,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "a55ee1b1660128b7098723e0abcd92caa0788061051c62d51cbe87d9cf1974d8",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "ad44e777bcd18fa416d9da3bd8f70d33ebb85d39",
           "tokenizer_class": "Qwen2Tokenizer",
           "transformers_version": "5.15.0"
         },
@@ -1892,14 +1898,14 @@
           }
         ]
       },
-      "elapsed_seconds": 1.227
+      "elapsed_seconds": 1.283
     },
     {
       "label": "Qwen3VL",
       "model_id": "Qwen/Qwen3-VL-2B-Instruct",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "89644892e4d85e24eaac8bacfd4f463576704203",
       "template_sha256": "3636d0f0bd6bef02654cdffdc447b79cb2cef8ab02cc75267345946291a489e4",
       "status": "contract_fail",
       "score": 81,
@@ -1921,7 +1927,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "3636d0f0bd6bef02654cdffdc447b79cb2cef8ab02cc75267345946291a489e4",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "89644892e4d85e24eaac8bacfd4f463576704203",
           "tokenizer_class": "Qwen2Tokenizer",
           "transformers_version": "5.15.0"
         },
@@ -2005,14 +2011,14 @@
           }
         ]
       },
-      "elapsed_seconds": 1.262
+      "elapsed_seconds": 1.141
     },
     {
       "label": "Qwen3.5",
       "model_id": "Qwen/Qwen3.5-0.8B",
       "template_name": null,
       "requested_revision": null,
-      "resolved_revision": null,
+      "resolved_revision": "2fc06364715b967f1860aea9cf38778875588b17",
       "template_sha256": "273d8e0e683b885071fb17e08d71e5f2a5ddfb5309756181681de4f5a1822d80",
       "status": "contract_pass",
       "score": 98,
@@ -2034,7 +2040,7 @@
           "contract_version": "2026-08-mvp1",
           "template_sha256": "273d8e0e683b885071fb17e08d71e5f2a5ddfb5309756181681de4f5a1822d80",
           "requested_revision": null,
-          "resolved_revision": null,
+          "resolved_revision": "2fc06364715b967f1860aea9cf38778875588b17",
           "tokenizer_class": "Qwen2Tokenizer",
           "transformers_version": "5.15.0"
         },
@@ -2119,7 +2125,7 @@
           }
         ]
       },
-      "elapsed_seconds": 1.756
+      "elapsed_seconds": 1.845
     }
   ],
   "manifest": {

src/toolcall_lint/adapters.py

@@ -2,11 +2,39 @@
 
 from __future__ import annotations
 
+import re
 from collections.abc import Sequence
 from importlib.metadata import version
+from pathlib import Path
 from typing import Any
 
 
+_SNAPSHOT_COMMIT = re.compile(r"(?:^|[/\\])snapshots[/\\]([0-9a-f]{40})(?:[/\\]|$)")
+
+
+def _commit_from_snapshot_path(path: str | Path | None) -> str | None:
+    if path is None:
+        return None
+    match = _SNAPSHOT_COMMIT.search(str(path))
+    return match.group(1) if match else None
+
+
+def _cached_commit(model_id: str, revision: str | None) -> str | None:
+    """Resolve the snapshot SHA already downloaded by ``from_pretrained``."""
+
+    try:
+        from huggingface_hub import try_to_load_from_cache
+
+        cached = try_to_load_from_cache(
+            model_id,
+            "tokenizer_config.json",
+            revision=revision or "main",
+        )
+    except Exception:
+        return None
+    return _commit_from_snapshot_path(cached if isinstance(cached, str) else None)
+
+
 class TransformersRenderer:
     """Render a Hub model's chat template through ``transformers``.
 
@@ -41,7 +69,12 @@ class TransformersRenderer:
 
     def source_metadata(self) -> dict[str, Any]:
         init_kwargs = getattr(self.tokenizer, "init_kwargs", {})
-        resolved_revision = getattr(self.tokenizer, "_commit_hash", None) or init_kwargs.get("_commit_hash")
+        resolved_revision = (
+            getattr(self.tokenizer, "_commit_hash", None)
+            or init_kwargs.get("_commit_hash")
+            or _commit_from_snapshot_path(getattr(self.tokenizer, "vocab_file", None))
+            or _cached_commit(self.model_id, self.revision)
+        )
         return {
             "requested_revision": self.revision,
             "resolved_revision": resolved_revision,

src/toolcall_lint/sweep.py

@@ -5,11 +5,13 @@ from __future__ import annotations
 import argparse
 import hashlib
 import json
+import platform
 import re
 import sys
 from collections import Counter
 from collections.abc import Callable, Sequence
 from datetime import datetime, timezone
+from importlib.metadata import PackageNotFoundError, version
 from pathlib import Path
 from time import perf_counter
 from typing import Any
@@ -114,6 +116,12 @@ def run_sweep(
         "contract_version": contract_version,
         "generated_at": datetime.now(timezone.utc).isoformat(),
         "loads_model_weights": False,
+        "environment": {
+            "python": platform.python_version(),
+            "platform": platform.platform(),
+            "toolcall_lint": _package_version("toolcall-lint"),
+            "transformers": _package_version("transformers"),
+        },
         "summary": {
             "targets": len(rows),
             "loaded": len(rows) - status_counts["load_error"],
@@ -152,6 +160,33 @@ def _stable_error_message(message: str) -> str:
     return re.sub(r"\s*\(Request ID: [^)]+\)", "", message).strip()
 
 
+def _package_version(name: str) -> str | None:
+    try:
+        return version(name)
+    except PackageNotFoundError:
+        return None
+
+
+def to_lock_manifest(dataset: dict[str, Any]) -> dict[str, Any]:
+    """Pin every successfully resolved Hub revision from a sweep dataset."""
+
+    models: list[dict[str, Any]] = []
+    for row in dataset["models"]:
+        target: dict[str, Any] = {"label": row["label"], "model_id": row["model_id"]}
+        if row.get("template_name"):
+            target["template_name"] = row["template_name"]
+        revision = row.get("resolved_revision") or row.get("requested_revision")
+        if revision:
+            target["revision"] = revision
+        models.append(target)
+    return {
+        "description": "Commit-pinned manifest generated by toolcall-lint-sweep.",
+        "contract_version": dataset.get("contract_version"),
+        "generated_at": dataset.get("generated_at"),
+        "models": models,
+    }
+
+
 def to_markdown(dataset: dict[str, Any]) -> str:
     """Render a compact, reviewable compatibility matrix."""
 
@@ -210,6 +245,7 @@ def build_parser() -> argparse.ArgumentParser:
     parser.add_argument("manifest", type=Path, help="JSON file containing a `models` list")
     parser.add_argument("--json-output", type=Path, required=True, help="Dataset output path")
     parser.add_argument("--markdown-output", type=Path, help="Optional summary table output path")
+    parser.add_argument("--lock-output", type=Path, help="Optional commit-pinned manifest output path")
     parser.add_argument(
         "--trust-remote-code",
         action="store_true",
@@ -243,6 +279,12 @@ def main(argv: list[str] | None = None) -> int:
         if args.markdown_output:
             args.markdown_output.parent.mkdir(parents=True, exist_ok=True)
             args.markdown_output.write_text(to_markdown(dataset) + "\n", encoding="utf-8")
+        if args.lock_output:
+            args.lock_output.parent.mkdir(parents=True, exist_ok=True)
+            args.lock_output.write_text(
+                json.dumps(to_lock_manifest(dataset), indent=2, ensure_ascii=False) + "\n",
+                encoding="utf-8",
+            )
     except Exception as exc:
         print(f"toolcall-lint-sweep: {type(exc).__name__}: {exc}", file=sys.stderr)
         return 2

tests/test_adapters.py

@@ -0,0 +1,20 @@
+from __future__ import annotations
+
+import unittest
+
+from toolcall_lint.adapters import _commit_from_snapshot_path
+
+
+class AdapterMetadataTests(unittest.TestCase):
+    def test_extracts_hub_snapshot_commit(self) -> None:
+        commit = "b968826d9c46dd6066d109eabc6255188de91218"
+        path = f"/cache/models--Qwen--Qwen3-8B/snapshots/{commit}/vocab.json"
+
+        self.assertEqual(_commit_from_snapshot_path(path), commit)
+
+    def test_ignores_non_snapshot_paths(self) -> None:
+        self.assertIsNone(_commit_from_snapshot_path("/local/model/vocab.json"))
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/test_sweep.py

@@ -6,7 +6,13 @@ import unittest
 from pathlib import Path
 
 from test_checks import FixtureRenderer
-from toolcall_lint.sweep import _stable_error_message, load_manifest, run_sweep, to_markdown
+from toolcall_lint.sweep import (
+    _stable_error_message,
+    load_manifest,
+    run_sweep,
+    to_lock_manifest,
+    to_markdown,
+)
 
 
 class SweepRenderer(FixtureRenderer):
@@ -75,6 +81,16 @@ class SweepTests(unittest.TestCase):
             "403 Client Error.\nCannot access gated repo",
         )
 
+    def test_lock_manifest_pins_resolved_revisions(self) -> None:
+        dataset = run_sweep(
+            [{"label": "Good", "model_id": "good/model"}],
+            renderer_factory=SweepRenderer,
+        )
+
+        locked = to_lock_manifest(dataset)
+
+        self.assertEqual(locked["models"][0]["revision"], "abc123")
+
 
 if __name__ == "__main__":
     unittest.main()