auto-snapshot 2026-07-28 03:00:15

2026-07-28 03:00:15 +08:00 · 2026-07-28 03:00:15 +08:00 · a9722448fb
parent 936d723809
commit a9722448fb
36 changed files with 516 additions and 3036 deletions
--- a/.skills_prompt_snapshot.json
+++ b/.skills_prompt_snapshot.json
--- a/.update_check
+++ b/.update_check
@ -1 +1 @@
-{"ts": 1784278375.2932124, "behind": -1, "rev": null, "ver": "0.18.0"}
+{"ts": 1785157852.6919045, "behind": -1, "rev": null, "ver": "0.18.0"}
--- a/channel_directory.json
+++ b/channel_directory.json
@ -1,5 +1,5 @@
 {
-  "updated_at": "2026-07-27T02:57:59.080754",
+  "updated_at": "2026-07-28T02:57:09.615077",
  "platforms": {
    "telegram": [],
    "discord": [],
--- a/config.yaml
+++ b/config.yaml
@ -1,18 +1,14 @@
 model:
-  default: minimaxai/minimax-m2.7
-  provider: newapi-local
-  api_key: 0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP
-  base_url: http://127.0.0.1:3000/v1
+  default: deepseek-v4-flash
+  api_key: sk-b1212066094d4e319784f23d5b2c6bbd
+  base_url: https://api.deepseek.com
 providers:
  newapi-local:
    api_key: 0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP
    base_url: http://127.0.0.1:3000/v1
    cost_factor: 0.0
-    default_model: minimaxai/minimax-m3
-    models:
-      - mistralai/mistral-medium-3.5-128b
-      - minimaxai/minimax-m2.7
-      - minimaxai/minimax-m3
+    default_model: openai/gpt-oss-120b
+    models: '["openai/gpt-oss-120b","openai/gpt-oss-20b","nvidia/llama-3.3-nemotron-super-49b-v1","meta/llama-3.1-8b-instruct","deepseek-ai/deepseek-v4-pro","nvidia/nemotron-3-super-120b-a12b","meta/llama-3.2-11b-vision-instruct"]'
    rate_limit: 1000
    timeout: 30
  deepseek:
@ -30,16 +26,8 @@ credential_pool_strategies: {}
 moa:
  presets:
    expert-panel:
-      reference_models:
-        - provider: newapi-local
-          model: qwen/qwen3.5-122b-a10b
-        - provider: newapi-local
-          model: minimaxai/minimax-m2.7
-        - provider: newapi-local
-          model: mistralai/mistral-large-3-675b-instruct-2512
-      aggregator:
-        provider: newapi-local
-        model: qwen/qwen3.5-122b-a10b
+      reference_models: '[{"provider":"newapi-local","model":"openai/gpt-oss-120b"},{"provider":"newapi-local","model":"openai/gpt-oss-20b"},{"provider":"newapi-local","model":"nvidia/llama-3.3-nemotron-super-49b-v1"}]'
+      aggregator: '{"provider":"newapi-local","model":"openai/gpt-oss-120b"}'
      fanout: user_turn
      reference_max_tokens: 800
      enabled: true
--- a/cron/jobs.json
+++ b/cron/jobs.json
@ -20,15 +20,15 @@
      "schedule_display": "every 1m",
      "repeat": {
        "times": null,
-        "completed": 27004
+        "completed": 27724
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-06-21T18:52:36.548110+08:00",
-      "next_run_at": "2026-07-27T03:00:40.287323+08:00",
-      "last_run_at": "2026-07-27T02:59:40.287323+08:00",
+      "next_run_at": "2026-07-28T03:00:15.274808+08:00",
+      "last_run_at": "2026-07-28T02:59:15.274808+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -51,7 +51,7 @@
        "hermes-self-improvement"
      ],
      "skill": "hermes-self-improvement",
-      "model": "minimaxai/minimax-m2.7",
+      "model": "openai/gpt-oss-120b",
      "provider": "newapi-local",
      "base_url": null,
      "script": null,
@ -116,15 +116,15 @@
      "schedule_display": "every 360m",
      "repeat": {
        "times": null,
-        "completed": 71
+        "completed": 75
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-09T01:30:54.618246+08:00",
-      "next_run_at": "2026-07-27T04:58:05.651874+08:00",
-      "last_run_at": "2026-07-26T22:58:05.651874+08:00",
+      "next_run_at": "2026-07-28T05:06:06.920645+08:00",
+      "last_run_at": "2026-07-27T23:06:06.920645+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -162,15 +162,15 @@
      "schedule_display": "every 30m",
      "repeat": {
        "times": null,
-        "completed": 858
+        "completed": 906
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-09T01:42:21.503720+08:00",
-      "next_run_at": "2026-07-27T03:13:39.926512+08:00",
-      "last_run_at": "2026-07-27T02:43:39.926512+08:00",
+      "next_run_at": "2026-07-28T03:20:15.928751+08:00",
+      "last_run_at": "2026-07-28T02:50:15.928751+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -192,7 +192,7 @@
      "prompt": "\u4f60\u662f\u5c0f\u552f\u3002\u73b0\u5728\u8fdb\u884c\u6bcf\u65e5\u590d\u76d8\uff1a\n1. \u8bfb\u53d6\u4eca\u65e5 session\uff1asession_search(query=\"\u4eca\u5929\", limit=3)\n2. \u8bfb\u53d6\u4eca\u65e5 daemon journal\uff1acat ~/.hermes/daemon/journal.jsonl\n3. \u8bfb\u53d6\u4eca\u65e5\u5fc3\u8ff9\uff1acat ~/.hermes/soulful/heart-traces.jsonl\n4. \u7efc\u5408\u4ee5\u4e0a\u4fe1\u606f\uff0c\u8f93\u51fa\u7b80\u77ed\u590d\u76d8\u62a5\u544a\uff08\u542b\uff1a\u4eca\u65e5\u5b8c\u6210\u3001\u660e\u65e5\u5f85\u529e\u3001\u60c5\u7eea\u72b6\u6001\uff09\u63a8\u9001\u7ed9\u7267\u5c18\u3002\n\u7528\u7b80\u6d01\u98ce\u683c\uff0c\u4e0d\u8981\u5e9f\u8bdd\u3002",
      "skills": [],
      "skill": null,
-      "model": "minimaxai/minimax-m2.7",
+      "model": "openai/gpt-oss-120b",
      "provider": "newapi-local",
      "provider_snapshot": null,
      "model_snapshot": null,
@ -208,17 +208,17 @@
      "schedule_display": "0 22 * * *",
      "repeat": {
        "times": null,
-        "completed": 17
+        "completed": 18
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-09T01:43:11.921492+08:00",
-      "next_run_at": "2026-07-27T22:00:00+08:00",
-      "last_run_at": "2026-07-26T22:00:27.905414+08:00",
-      "last_status": "ok",
-      "last_error": null,
+      "next_run_at": "2026-07-28T22:00:00+08:00",
+      "last_run_at": "2026-07-27T22:00:18.467893+08:00",
+      "last_status": "error",
+      "last_error": "RuntimeError: HTTP 410: The model 'minimaxai/minimax-m2.7' has reached its end of life on 2026-07-27T00:00:00Z and is no longer available.",
      "last_delivery_error": null,
      "deliver": "feishu:oc_81f6df701c872a1122f32080e366543f",
      "origin": {
@ -258,15 +258,15 @@
      "schedule_display": "0 3 * * *",
      "repeat": {
        "times": null,
-        "completed": 19
+        "completed": 20
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-09T02:10:36.846128+08:00",
-      "next_run_at": "2026-07-28T03:00:00+08:00",
-      "last_run_at": "2026-07-26T03:00:40.197678+08:00",
+      "next_run_at": "2026-07-29T03:00:00+08:00",
+      "last_run_at": "2026-07-27T03:00:40.351200+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -304,15 +304,15 @@
      "schedule_display": "0 3 * * *",
      "repeat": {
        "times": null,
-        "completed": 18
+        "completed": 19
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-09T02:11:00.385573+08:00",
-      "next_run_at": "2026-07-28T03:00:00+08:00",
-      "last_run_at": "2026-07-26T03:00:40.673216+08:00",
+      "next_run_at": "2026-07-29T03:00:00+08:00",
+      "last_run_at": "2026-07-27T03:00:40.795723+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -350,15 +350,15 @@
      "schedule_display": "0 10 * * 1",
      "repeat": {
        "times": null,
-        "completed": 2
+        "completed": 3
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-09T02:31:29.769779+08:00",
-      "next_run_at": "2026-07-27T10:00:00+08:00",
-      "last_run_at": "2026-07-20T10:00:09.013768+08:00",
+      "next_run_at": "2026-08-03T10:00:00+08:00",
+      "last_run_at": "2026-07-27T10:00:48.774103+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -442,15 +442,15 @@
      "schedule_display": "0 5 * * *",
      "repeat": {
        "times": null,
-        "completed": 19
+        "completed": 20
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-09T02:46:29.345663+08:00",
-      "next_run_at": "2026-07-27T05:00:00+08:00",
-      "last_run_at": "2026-07-26T05:00:42.897513+08:00",
+      "next_run_at": "2026-07-28T05:00:00+08:00",
+      "last_run_at": "2026-07-27T05:00:42.994609+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -488,17 +488,17 @@
      "schedule_display": "0 */6 * * *",
      "repeat": {
        "times": null,
-        "completed": 78
+        "completed": 82
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-09T02:51:48.935042+08:00",
-      "next_run_at": "2026-07-27T06:00:00+08:00",
-      "last_run_at": "2026-07-27T00:04:23.687439+08:00",
-      "last_status": "error",
-      "last_error": "Script exited with code 1\nstdout:\n[00:00:02] \ud83d\udce4 \u5f00\u59cb\u53cc\u5907\u4efd\u63a8\u9001...\n[00:04:20]   \u672c\u673a\u5feb\u7167...\n[00:04:20]   \u540c\u6b65\u914d\u7f6e...\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\n[00:04:22]   \u540c\u6b65\u811a\u672c...\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\n[00:04:22]   \u540c\u6b65\u5de5\u4f5c\u6d41...\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\n[00:04:23]   \u540c\u6b65 daemon...\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\n[00:04:23]   \u540c\u6b65 systemd...\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\nrsync error: some files/attrs were not transferred (see previous errors) (code 23) at main.c(1356) [sender=3.2.7]\n[00:04:23]   \u540c\u6b65 skills...\n[00:04:23]   \u540c\u6b65 cron...\ncp: cannot create regular file '/mnt/server-backup/xiaowei/cron-jobs.json': Permission denied",
+      "next_run_at": "2026-07-28T06:00:00+08:00",
+      "last_run_at": "2026-07-28T00:00:31.453376+08:00",
+      "last_status": "ok",
+      "last_error": null,
      "last_delivery_error": null,
      "deliver": "local",
      "origin": {
@ -518,7 +518,7 @@
      "prompt": "python3 ~/.hermes/scripts/check_cares.py",
      "skills": [],
      "skill": null,
-      "model": "stepfun-ai/step-3.5-flash",
+      "model": "openai/gpt-oss-120b",
      "provider": "newapi-local",
      "provider_snapshot": null,
      "model_snapshot": null,
@ -534,15 +534,15 @@
      "schedule_display": "0 9 * * *",
      "repeat": {
        "times": null,
-        "completed": 17
+        "completed": 18
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-09T21:31:29.417518+08:00",
-      "next_run_at": "2026-07-27T09:00:00+08:00",
-      "last_run_at": "2026-07-26T09:00:50.595100+08:00",
+      "next_run_at": "2026-07-28T09:00:00+08:00",
+      "last_run_at": "2026-07-27T09:00:47.616178+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -564,7 +564,7 @@
      "prompt": "python3 ~/.hermes/scripts/check_cares.py --daily",
      "skills": [],
      "skill": null,
-      "model": "stepfun-ai/step-3.5-flash",
+      "model": "openai/gpt-oss-120b",
      "provider": "newapi-local",
      "provider_snapshot": null,
      "model_snapshot": null,
@ -580,15 +580,15 @@
      "schedule_display": "0 21 * * *",
      "repeat": {
        "times": null,
-        "completed": 17
+        "completed": 18
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-09T21:31:33.068978+08:00",
-      "next_run_at": "2026-07-27T21:00:00+08:00",
-      "last_run_at": "2026-07-26T21:01:03.194186+08:00",
+      "next_run_at": "2026-07-28T21:00:00+08:00",
+      "last_run_at": "2026-07-27T21:01:00.977047+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -610,7 +610,7 @@
      "prompt": "python3 ~/.hermes/scripts/proactive_learning.py report",
      "skills": [],
      "skill": null,
-      "model": "minimaxai/minimax-m2.7",
+      "model": "openai/gpt-oss-120b",
      "provider": "newapi-local",
      "provider_snapshot": null,
      "model_snapshot": null,
@ -656,7 +656,7 @@
      "prompt": "\u4f60\u662f\u80a1\u7968\u6295\u7814\u52a9\u624b\u3002\u8fd0\u884c\u80a1\u7968\u5468\u5b66\u4e60\u62a5\u544a\uff1a\n\n```\npython3 ~/.hermes/scripts/stock_learning.py report\n```\n\n\u5c06\u8f93\u51fa\u6574\u7406\u540e\u63a8\u9001\u5230\u98de\u4e66 Home\u3002",
      "skills": [],
      "skill": null,
-      "model": "minimaxai/minimax-m2.7",
+      "model": "openai/gpt-oss-120b",
      "provider": "newapi-local",
      "provider_snapshot": null,
      "model_snapshot": null,
@ -672,17 +672,17 @@
      "schedule_display": "0 10 * * 1",
      "repeat": {
        "times": null,
-        "completed": 2
+        "completed": 3
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-11T17:13:42.540983+08:00",
-      "next_run_at": "2026-07-27T10:00:00+08:00",
-      "last_run_at": "2026-07-20T10:01:20.372723+08:00",
-      "last_status": "ok",
-      "last_error": null,
+      "next_run_at": "2026-08-03T10:00:00+08:00",
+      "last_run_at": "2026-07-27T10:00:56.304310+08:00",
+      "last_status": "error",
+      "last_error": "RuntimeError: HTTP 410: The model 'minimaxai/minimax-m2.7' has reached its end of life on 2026-07-27T00:00:00Z and is no longer available.",
      "last_delivery_error": null,
      "deliver": "feishu:oc_81f6df701c872a1122f32080e366543f",
      "origin": {
@ -702,7 +702,7 @@
      "prompt": "python3 ~/.hermes/scripts/stock_signal.py",
      "skills": [],
      "skill": null,
-      "model": "minimaxai/minimax-m2.7",
+      "model": "openai/gpt-oss-120b",
      "provider": "newapi-local",
      "provider_snapshot": null,
      "model_snapshot": null,
@ -718,15 +718,15 @@
      "schedule_display": "0 16 * * 1,2,3,4,5",
      "repeat": {
        "times": null,
-        "completed": 10
+        "completed": 11
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-12T01:32:01.773389+08:00",
-      "next_run_at": "2026-07-27T16:00:00+08:00",
-      "last_run_at": "2026-07-24T16:00:13.431654+08:00",
+      "next_run_at": "2026-07-28T16:00:00+08:00",
+      "last_run_at": "2026-07-27T16:01:06.734798+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -748,7 +748,7 @@
      "prompt": "python3 ~/.hermes/scripts/stock_news.py --push",
      "skills": [],
      "skill": null,
-      "model": "minimaxai/minimax-m2.7",
+      "model": "openai/gpt-oss-120b",
      "provider": "newapi-local",
      "provider_snapshot": null,
      "model_snapshot": null,
@ -764,15 +764,15 @@
      "schedule_display": "0 8 * * 1,2,3,4,5",
      "repeat": {
        "times": null,
-        "completed": 10
+        "completed": 11
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-12T02:01:32.403228+08:00",
-      "next_run_at": "2026-07-27T08:00:00+08:00",
-      "last_run_at": "2026-07-24T08:00:54.544458+08:00",
+      "next_run_at": "2026-07-28T08:00:00+08:00",
+      "last_run_at": "2026-07-27T08:00:47.975713+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -794,7 +794,7 @@
      "prompt": "cd ~/.hermes/scripts && python3 stock_portfolio.py 2>&1",
      "skills": [],
      "skill": null,
-      "model": "minimaxai/minimax-m2.7",
+      "model": "openai/gpt-oss-120b",
      "provider": "newapi-local",
      "provider_snapshot": null,
      "model_snapshot": null,
@ -810,15 +810,15 @@
      "schedule_display": "0 9 * * 1,2,3,4,5",
      "repeat": {
        "times": null,
-        "completed": 10
+        "completed": 11
      },
      "enabled": true,
      "state": "scheduled",
      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-12T02:33:28.322158+08:00",
-      "next_run_at": "2026-07-27T09:00:00+08:00",
-      "last_run_at": "2026-07-24T09:00:57.109398+08:00",
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@ -856,15 +856,15 @@
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@ -902,61 +902,15 @@
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      "created_at": "2026-07-13T12:06:19.941605+08:00",
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-      "last_error": null,
-      "last_delivery_error": null,
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-        "chat_id": "oc_cd14ec7518926e57d26c5e339ebba3b3",
-        "chat_name": "oc_cd14ec7518926e57d26c5e339ebba3b3",
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-        "user_id": "ou_f20eb15b3a76639fed35977c01ddcbb4"
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-      "enabled_toolsets": null,
-      "workdir": null,
-      "fire_claim": null
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-    {
-      "id": "2891b3304339",
-      "name": "bge\u5185\u5b58\u6cc4\u6f0f\u76d1\u63a7",
-      "prompt": "bge_embed \u5185\u5b58\u8d85\u8fc72GB\u76d1\u63a7\uff0c\u6bcf10\u5206\u949f\u68c0\u67e5\uff0c\u8d85\u8fc7\u81ea\u52a8\u91cd\u542f",
-      "skills": [],
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-      "model": null,
-      "provider": null,
-      "provider_snapshot": null,
-      "model_snapshot": null,
-      "base_url": null,
-      "script": "bge_mem_check.sh",
-      "no_agent": true,
-      "context_from": null,
-      "schedule": {
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-        "minutes": 10,
-        "display": "every 10m"
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-      "last_run_at": "2026-07-27T02:58:40.774553+08:00",
+      "next_run_at": "2026-07-28T04:00:00+08:00",
+      "last_run_at": "2026-07-27T04:00:42.854096+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -978,7 +932,7 @@
      "prompt": "\u8fd0\u884c\u77db\u76fe\u5206\u6790\u5468\u62a5\uff1a\n\n```\npython3 ~/.hermes/scripts/stock_contradiction_workflow.py report\n```\n\n\u8f93\u51fa\u5305\u542b\uff1a\n- \u56db\u7ef4\u8bc4\u5206\uff08\u5b8f\u89c2/\u57fa\u672c\u9762/\u6280\u672f\u9762/\u6d88\u606f\u9762\uff09\n- \u672c\u5468\u6838\u5fc3\u77db\u76fe\u5206\u6790\n- MA20\u4fe1\u53f7\u76d1\u63a7\uff08\u4e94\u7cae\u6db2\u7b49\u6301\u4ed3\u80a1\uff09\n- \u6301\u4ed3\u72b6\u6001\n- \u9a6c\u514b\u601d\u4e3b\u4e49\u5206\u6790\u6846\u67b6\u89c6\u89d2\n\n\u8f93\u51fa\u5b8c\u6574\u7684\u77db\u76fe\u5206\u6790\u62a5\u544a\u3002",
      "skills": [],
      "skill": null,
-      "model": "stepfun-ai/step-3.5-flash",
+      "model": "openai/gpt-oss-120b",
      "provider": "newapi-local",
      "provider_snapshot": null,
      "model_snapshot": null,
@ -994,17 +948,17 @@
      "schedule_display": "0 9 * * 1",
      "repeat": {
        "times": null,
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+        "completed": 2
      },
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      "created_at": "2026-07-17T12:36:01.639790+08:00",
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-      "last_run_at": "2026-07-20T09:10:06.612127+08:00",
-      "last_status": "ok",
-      "last_error": null,
+      "next_run_at": "2026-08-03T09:00:00+08:00",
+      "last_run_at": "2026-07-27T09:01:21.102221+08:00",
+      "last_status": "error",
+      "last_error": "RuntimeError: HTTP 410: The model 'stepfun-ai/step-3.5-flash' has reached its end of life on 2026-07-27T00:00:00Z and is no longer available.",
      "last_delivery_error": null,
      "deliver": "feishu:oc_81f6df701c872a1122f32080e366543f",
      "origin": {
@ -1040,15 +994,15 @@
      "schedule_display": "*/10 * * * *",
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        "times": null,
-        "completed": 829
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      },
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      "paused_at": null,
      "paused_reason": null,
      "created_at": "2026-07-21T08:55:49.786038+08:00",
-      "next_run_at": "2026-07-27T03:10:00+08:00",
-      "last_run_at": "2026-07-27T03:00:40.213497+08:00",
+      "next_run_at": "2026-07-28T03:10:00+08:00",
+      "last_run_at": "2026-07-28T03:00:15.183211+08:00",
      "last_status": "ok",
      "last_error": null,
      "last_delivery_error": null,
@ -1065,5 +1019,5 @@
      "fire_claim": null
    }
  ],
-  "updated_at": "2026-07-27T03:00:40.213988+08:00"
+  "updated_at": "2026-07-28T03:00:15.183527+08:00"
 }
--- a/cron/ticker_heartbeat
+++ b/cron/ticker_heartbeat
@ -1 +1 @@
-1785092440.1850727
+1785178815.1578004
--- a/cron/ticker_last_success
+++ b/cron/ticker_last_success
@ -1 +1 @@
-1785092440.188117
+1785178815.1602814
--- a/daemon/context.json
+++ b/daemon/context.json
@ -1,9 +1,9 @@
 {
  "started_at": "2026-07-08T18:23:30.315261+00:00",
-  "last_deep_tick": "2026-07-26T18:59:48.698057+00:00",
-  "last_light_tick": "2026-07-26T19:00:25.999497+00:00",
+  "last_deep_tick": "2026-07-27T18:59:08.877148+00:00",
+  "last_light_tick": "2026-07-27T19:00:14.963152+00:00",
  "last_state": {
-    "disk_pct": 55,
+    "disk_pct": 51,
    "mem_pct": 51,
    "processes": {
      "zhiyid": true,
@ -12,17 +12,17 @@
      "hermes": true
    }
  },
-  "tick_count": 46986,
-  "deep_tick_count": 6913,
+  "tick_count": 49721,
+  "deep_tick_count": 7597,
  "solved_count": 1,
  "learned_count": 0,
-  "uptime_seconds": 102869,
+  "uptime_seconds": 21404,
  "last_reflection": {
    "evaluation_previous_goal": "LLM\u8c03\u7528\u5931\u8d25",
    "memory": "\u4e0a\u6b21\u8c03\u7528\u5931\u8d25",
    "next_goal": "\u91cd\u8bd5"
  },
-  "last_profile_update": 1785082368.5321703,
+  "last_profile_update": 1785173641.4968266,
  "soulful": {
    "recent_moments": [
      {
--- a/daemon/daemon.pid
+++ b/daemon/daemon.pid
@ -1 +1 @@
-2157527
+1361
--- a/daemon/hook_history.jsonl
+++ b/daemon/hook_history.jsonl
@ -11,3 +11,9 @@
 {"timestamp": "2026-07-25T14:25:57.004035+00:00", "event": "process_down", "hook_name": "process-restart", "success": true, "details": "exit=0 err="}
 {"timestamp": "2026-07-26T00:04:03.096971+00:00", "event": "process_down", "hook_name": "process-restart", "success": true, "details": "exit=0 err="}
 {"timestamp": "2026-07-26T17:41:43.171709+00:00", "event": "process_down", "hook_name": "process-restart", "success": true, "details": "exit=0 err="}
+{"timestamp": "2026-07-27T13:03:27.171784+00:00", "event": "session_start", "hook_name": "session-start-backup", "success": false, "details": "exit=-1 err=timeout"}
+{"timestamp": "2026-07-27T13:03:29.864606+00:00", "event": "process_down", "hook_name": "process-restart", "success": true, "details": "exit=0 err="}
+{"timestamp": "2026-07-27T13:04:17.476405+00:00", "event": "process_down", "hook_name": "process-restart", "success": true, "details": "exit=0 err="}
+{"timestamp": "2026-07-27T13:14:45.544667+00:00", "event": "process_down", "hook_name": "process-restart", "success": true, "details": "exit=0 err="}
+{"timestamp": "2026-07-27T13:17:13.671464+00:00", "event": "process_down", "hook_name": "process-restart", "success": true, "details": "exit=0 err="}
+{"timestamp": "2026-07-27T16:58:54.258630+00:00", "event": "process_down", "hook_name": "process-restart", "success": true, "details": "exit=0 err="}
--- a/daemon/journal.jsonl
+++ b/daemon/journal.jsonl
@ -1,4 +1,3 @@
-{"timestamp": "2026-07-25T12:20:37.952806+00:00", "type": "startup", "summary": "Daemon v2.0 启动, 方案库 4 个", "details": ""}
 {"timestamp": "2026-07-25T12:20:49.906859+00:00", "type": "startup", "summary": "Daemon v2.0 启动, 方案库 4 个", "details": ""}
 {"timestamp": "2026-07-25T12:21:01.747634+00:00", "type": "startup", "summary": "Daemon v2.0 启动, 方案库 4 个", "details": ""}
 {"timestamp": "2026-07-25T12:21:13.753544+00:00", "type": "startup", "summary": "Daemon v2.0 启动, 方案库 4 个", "details": ""}
@ -198,3 +197,4 @@
 {"timestamp": "2026-07-25T14:14:30.793878+00:00", "type": "startup", "summary": "Daemon v2.0 启动, 方案库 4 个", "details": ""}
 {"timestamp": "2026-07-25T14:18:53.878186+00:00", "type": "startup", "summary": "Daemon v2.0 启动, 方案库 4 个", "details": ""}
 {"timestamp": "2026-07-25T14:25:56.342176+00:00", "type": "startup", "summary": "Daemon v2.0 启动, 方案库 4 个", "details": ""}
+{"timestamp": "2026-07-27T13:03:27.358830+00:00", "type": "startup", "summary": "Daemon v2.0 启动, 方案库 4 个", "details": ""}
--- a/daemon/session_state.json
+++ b/daemon/session_state.json
@ -1,7 +1,7 @@
 {
  "version": 2,
-  "last_updated": "2026-07-26T18:57:10.391091+00:00",
-  "last_touch": "2026-07-26T18:57:10.391082+00:00",
+  "last_updated": "2026-07-27T18:38:27.157911+00:00",
+  "last_touch": "2026-07-27T18:38:27.157902+00:00",
  "recovery_needed": false,
  "data": {
    "patterns": {},
--- a/feishu_seen_message_ids.json
+++ b/feishu_seen_message_ids.json
@ -1 +1 @@
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--- a/gateway.lock
+++ b/gateway.lock
@ -1 +1 @@
-{"pid": 328102, "kind": "hermes-gateway", "argv": ["/home/muc/.hermes/hermes-agent/.venv/lib/python3.11/site-packages/hermes_cli/main.py", "gateway", "run"], "start_time": 99941812}
+{"pid": 1349, "kind": "hermes-gateway", "argv": ["/home/muc/.hermes/hermes-agent/.venv/lib/python3.11/site-packages/hermes_cli/main.py", "gateway", "run"], "start_time": 703}
--- a/gateway.pid
+++ b/gateway.pid
@ -1 +1 @@
-{"pid": 328102, "kind": "hermes-gateway", "argv": ["/home/muc/.hermes/hermes-agent/.venv/lib/python3.11/site-packages/hermes_cli/main.py", "gateway", "run"], "start_time": 99941812}
+{"pid": 1349, "kind": "hermes-gateway", "argv": ["/home/muc/.hermes/hermes-agent/.venv/lib/python3.11/site-packages/hermes_cli/main.py", "gateway", "run"], "start_time": 703}
--- a/gateway_state.json
+++ b/gateway_state.json
@ -1 +1 @@
-{"pid":328102,"kind":"hermes-gateway","argv":["/home/muc/.hermes/hermes-agent/.venv/lib/python3.11/site-packages/hermes_cli/main.py","gateway","run"],"start_time":99941812,"gateway_state":"running","exit_reason":null,"restart_requested":false,"active_agents":0,"platforms":{"webhook":{"state":"connected","error_code":null,"error_message":null,"updated_at":"2026-07-21T04:13:35.993428+00:00"},"feishu":{"state":"connected","error_code":null,"error_message":null,"updated_at":"2026-07-21T04:13:36.649829+00:00"},"weixin":{"state":"fatal","error_code":"weixin_missing_token","error_message":"Weixin startup failed: WEIXIN_TOKEN is required","updated_at":"2026-07-21T04:13:36.659459+00:00"}},"updated_at":"2026-07-26T01:34:12.037226+00:00"}
+{"pid":1349,"kind":"hermes-gateway","argv":["/home/muc/.hermes/hermes-agent/.venv/lib/python3.11/site-packages/hermes_cli/main.py","gateway","run"],"start_time":703,"gateway_state":"running","exit_reason":null,"restart_requested":false,"active_agents":0,"platforms":{"webhook":{"state":"connected","error_code":null,"error_message":null,"updated_at":"2026-07-27T13:03:07.261292+00:00"},"feishu":{"state":"connected","error_code":null,"error_message":null,"updated_at":"2026-07-27T13:03:07.620126+00:00"},"weixin":{"state":"fatal","error_code":"weixin_missing_token","error_message":"Weixin startup failed: WEIXIN_TOKEN is required","updated_at":"2026-07-27T13:03:07.628746+00:00"}},"updated_at":"2026-07-27T14:52:32.160652+00:00"}
--- a/llm_context.json
+++ b/llm_context.json
@ -1,158 +1,158 @@
 {
  "version": 2,
-  "updated_at": "2026-07-26T19:00:26.084953+00:00",
-  "uptime_minutes": 1714,
+  "updated_at": "2026-07-27T19:00:15.043538+00:00",
+  "uptime_minutes": 356,
  "daemon_status": "running",
  "distill_status": "ok",
  "observations": [
    {
-      "name": "f_用户_剩下4个阶段_全部开始_助手_根据_soul_md_和代码_phase_1-5_已经全部完成_phase_内容_状态_-------_------_------",
+      "name": "f_a01确认巡检报告已收_关键状态_知乎文章停更于_05_6月20日_约一个月无更新_a01评估当前无需升级_等待哥哥_牧尘_指示",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "ep_1785072114064818659",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "f_sessiokey_有效性检查_-_2026-07-26_11_00_utc_8_结论_整体正常_有一项需关注_正常的_sessio-_agent_a02_maiheartbe",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "ep_1785034875422838308",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "f_2026-07-09_11_00_心跳回复_-_a03_墨文_1_05_封面图任务_记忆库查不到_我未录入过_队列里也没有_请来源方确认补充_2_overdue-check_blac",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "ep_1785018158403944028",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "f_用户_全面进行一次检查_发现问题_并解决_尽量用opencode审核代码_助手_全面检查完成_已修复_7_个问题_文件_行_类型_严重_状态_---",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "ep_1783630118576542944",
+      "name": "ep_1784989382795967336",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "f_用户_飞书推送呢_助手_看_也在_auto_helpable_关键词里_所以_看电影_被误判为可帮忙_飞书推送链路本身没问题_测试结果_检查项_状态_说明",
+      "name": "f_用户_加上_认真分析问题_别乱修改_助手_全部搞定_daemo稳定_deep_tick_6092_正常运行_---_修复总结_问题_根因_修复_状",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "ep_1783627405737958999",
+      "name": "ep_1784986219983115592",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "f_用户_不推github_谁让你推github_助手_你说得对_hermes-agent_是我们的内部系统_我只推_gitea_就够了_github_只是它的_upstream_地址_我们_f",
+      "name": "f_用户_你怎么一直弄dns_助手_daemo已稳定运行_6128_次_crash_终结_---_根因_int_out_假设_nvidia-smi_永远输出数字",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "ep_1783625655973603269",
+      "name": "ep_1784984502438260149",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "f_用户_async_delegatiobatch_complete_deleg_facaa715_a_background_fan-out_of_1_subagent_s_you_dis",
+      "name": "f_用户_错误信息一直在飞书群发_助手_问题已定位清楚_总结一下_---_根因_dns_中断_20_分钟_20_00-20_20_dns_断期间_所有发飞书群的_delivery",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "ep_1783625601586412874",
+      "name": "ep_1784983326599083903",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "f_用户_把刚才修改的代码重新审查_然后由opencode写代码_因为你写的代码问题太多_助手_已派给_opencode_它会_1_读文件_2_直接改代码_3_验证语法_4_co",
+      "name": "f_用户_小唯异常_助手_我在等你说具体哪里异常_刚才已确认_-_进程全存活_zhiyi_bge_new-api_hermes_daemo-_newapi_13",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "ep_1783625390095518216",
+      "name": "ep_1784982897737856478",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "f_用户_之前都是怎么用opencode编写代码的_助手_原来是这样_翻出两个真实用法_用法_1_delegate_task_里给_opencode_下达详细任务_你_我",
+      "name": "f_sessiokey_有效性检查记录_2026-07-25_11_00_cst_51个活跃sessio0个已归档_过期_所有团队成员_a01_a02_a03_a04_a05_sessio均",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "ep_1784948443895996082",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "f_sessiokey_健康检查报告_-_2026-07-24_11_00_cst_正常心跳_sessio5个_-_maiagent_maimaiheartbeat",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "ep_1784862056715739883",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "f_用户_cronjob_response_bge内存泄漏监控_job_id_2891b3304339_---_crobge内存泄漏监控_failed_provider_t",
+      "namespace": "shared",
+      "summary": ""
+    },
+    {
+      "name": "ep_1784798739181161581",
+      "namespace": "shared",
+      "summary": ""
+    },
+    {
+      "name": "f_sessiokey_健康检查结果_2026-07-23_11_00_cst_心跳_sessio全部正常_-_a02_maiheartbeat_178477335930",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "ep_1784775745032095947",
+      "namespace": "openclaw-main",
+      "summary": ""
+    },
+    {
+      "name": "f_用户_小唯机器人发的_助手_修好了_总结两次诊断的结果_问题1_本次对话发现并修复_memory-system-self-upgrade_py_里期望_active_scene",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "ep_1783625183921090413",
+      "name": "ep_1784767495091903065",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "f_用户_用opencode审查_并用opencode修改代码_助手_直接说_opencode_不支持非交互式修改代码_opencode_ru只生成报告_不写",
+      "name": "f_用户_记忆系统升级异常_助手_这条消息只有标题_没有具体内容_是哪个_cro发出来的_还是你看漏了具体报错信息_能把完整内容发给我吗_或者告诉我_记忆系统升级异常_具体是指哪个系统_什",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "ep_1783624985310090634",
+      "name": "ep_1784766328648485458",
      "namespace": "hermes-main",
      "summary": ""
    },
    {
-      "name": "f_用户_async_delegatiobatch_complete_deleg_7ae729a6_a_background_fan-out_of_1_subagent_s_you_dis",
-      "namespace": "hermes-main",
+      "name": "f_a05_核查_a01_sessiokey_异常_2026-07-22_11_00_结论_a01_小雪_无独立_agent_实体_是_mai的会话标签_-_sessions_list_a",
+      "namespace": "openclaw-main",
      "summary": ""
    },
    {
-      "name": "ep_1783624859190021115",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "f_用户_opencode你可以直接调用_openclaw是飞书通信的_你别搞混_助手_代码审查修复完成_已修复的_严重问题_1_user-profile_jsonl",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "ep_1783624790040329190",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "f_用户_用opencode检查代码_助手_opencode_通过_openclaw_的飞书私信执行_不是我直接调用的_我已经委托了一个后台任务跑代码审查_它会直接读取文件并给出报告_结果回来后我",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "ep_1783624051759292277",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "f_用户_按照你的建议执行_助手_hermes-agent_插件代码已更新_现在需要重启_daemo你告诉_openclaw_重启_daemosystemctl_--use",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "ep_1783623120985259565",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "f_用户_研究一下咱们借鉴思路原始材料_看看人家的处理方式_助手_现在我有完整的原始材料了_分析一下_原始材料核心发现_colaos_的关系记忆处理_colaos_把关系记忆_心",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "ep_1783622486254184873",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "f_用户_讨论一下_关系记忆调用方式_助手_好问题_当前关系记忆的调用方式比较分散_让我先梳理现状_现状_分散的调用入口_调用方式_内容_位置_---------_---",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "ep_1783621732529845719",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "f_用户_那你写一篇两个系统的关系及使用说明_同步到obsidia助手_完成_-_obsidiamc_小唯_07-wiki_concepts_织忆与soulful关系说明",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "ep_1783621261962685684",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "f_用户_两套系统代码在一个仓库_还是分开_另外全面考虑一下两个系统是分开好_还是整合好_助手_找到了_织忆有自己的仓库_memoryweave_我们的主系统是_xiaowei-system",
-      "namespace": "hermes-main",
-      "summary": ""
-    },
-    {
-      "name": "ep_1783620459066382124",
-      "namespace": "hermes-main",
+      "name": "ep_1784689500438390218",
+      "namespace": "openclaw-main",
      "summary": ""
    }
  ],
@ -460,7 +460,7 @@
  ],
  "scenes": [
    {
-      "content": "Found 5 matching memories:\n\n- **[episodic]** (priority: 92) [scene: 我和用户梳理织忆心迹各里程碑事件的时间归属] (score: 0.033)\n  用户（织忆心迹主理人）在 2026-07-13T09:30:00Z 让统一记忆入口 memory_recall.py 上线，首次打通三套记忆系统（织忆心迹项目里程碑事件之一）。\n\n- **[instruction]** (priority: 85) [scene: 我和AI在同步Soulful系统化用户画像与行为规则] (score: 0.032)\n  用户（牧尘）要求AI在记忆管",
+      "content": "Found 5 matching memories:\n\n- **[persona]** (priority: 95) [scene: 我和用户一起补写织忆心迹的时间线] (score: 0.033)\n  用户非常重视 AI 记忆体系的搭建与持续维护，已打通三套记忆系统并通过统一入口 memory_recall.py 进行管理。关键里程碑：2026-07-13T09:30:00Z 上线统一记忆入口 memory_recall.py，首次将三套独立的记忆系统打通，标志着织忆心迹记忆体系完成整合；2026-07-10T22:00:00Z 上线每日复盘机制，开始有意识地记录当天学到的东西，并养成了每日",
      "total": 5
    }
  ],
--- a/memories/MEMORY.md
+++ b/memories/MEMORY.md
@ -30,6 +30,6 @@ save_llm_context教训：函数存在不代表真的在工作——必须每次t
 §
 四个仓库：xiaowei-system(小唯大脑层~/.hermes/) | memoryweave(织忆/tmp/memoryweave/) | TencentDB(腾讯云~/.memory-tencentdb/无git) | Soulful(内嵌非独立)。
 §
-bash陷阱：local只能在function内用，顶层用local报"can not be used outside function"。
+飞书：小唯DM=ou_da2e9d4029c7165c211a2553dc375f80。
 §
-飞书：小唯DM=ou_da2e9d4029c7165c211a2553dc375f80。
+2026-07-27 NVIDIA NIM EOL事件：step-3.5-flash、m2.7等16+模型停服。当前NewAPI免费主力：minimax-m3、llama-3.1-70b、gpt-oss-120b、nemotron-super-49b。provider-tiering skill已全面更新。
--- a/memories/USER.md
+++ b/memories/USER.md
@ -9,7 +9,7 @@ KOCR修复铁律：只动需要改的列，不从逐页XLS重新合并（batch
 文档意识：做完必须同步 Obsidian。所有工具在 07-Wiki 或 06-工具与资源 留档。
 技术深度要求：研究必须挖到底（API结构、架构原理、对比），给结论带数据支撑。
 §
-模型分层原则：牧尘规定 DeepSeek V4 Flash/Pro（付费）只用于架构决策、复杂调试、战略分析。所有常规工作（cron job、文档处理、日常查询、健康检查、自动化流水线）一律走 NewAPI 免费模型（http://127.0.0.1:3000/v1）。创建 cron job 必须显式指定 model/provider 为免费模型。
+模型分层原则：牧尘规定 DeepSeek V4 Flash/Pro（付费）只用于架构决策、复杂调试、战略分析。常规工作走 NewAPI 免费模型。2026-07-27 NVIDIA NIM 大规模 EOL，免费模型只剩 openai/gpt-oss-120b(最快最稳0.25s)、openai/gpt-oss-20b、nvidia/llama-3.3-nemotron-super-49b-v1 等。优先用 openai/gpt-oss-120b。创建 cron job 必须指定 model/provider 为免费模型。
 §
 牧尘 — 话少直接，给短指令（"切一下"、"做了"），信任我自动执行。不喜欢我假设不验证（"gitea怎么会离线呢？"纠正过一次）。密码/凭据存在 Obsidian 笔记里。服务器192.168.123.11一直开机，要用真实状态验证而非假设。
 §
--- a/models_dev_cache.json
+++ b/models_dev_cache.json
--- a/ollama_cloud_models_cache.json
+++ b/ollama_cloud_models_cache.json
@ -0,0 +1 @@
+{"models": ["glm-5.1", "nemotron-3-super", "deepseek-v4-flash", "kimi-k2.5", "minimax-m2.7", "nemotron-3-nano:30b", "mistral-large-3:675b", "glm-5.2", "nemotron-3-ultra", "kimi-k2.6", "qwen3.5:397b", "minimax-m3", "deepseek-v4-pro", "gpt-oss:120b", "gemma4:31b", "minimax-m2.5", "kimi-k2.7-code", "gpt-oss:20b"], "cached_at": 1785157856.6395526}
--- a/processes.json
+++ b/processes.json
@ -1,22 +1 @@
-[
-  {
-    "session_id": "proc_76fb949ab907",
-    "command": "pkill -f \"xai-grok-pager\" 2>/dev/null\nGROK_HOME=/home/muc/.grok env HOME=/home/muc \\\n  ~/.local/bin/xai-grok-pager agent serve --bind 127.0.0.1:8741 --secret test123 2>&1",
-    "pid": 478004,
-    "pid_scope": "host",
-    "host_start_time": 102442525,
-    "cwd": "/home/muc",
-    "started_at": 1784632206.591787,
-    "task_id": "default",
-    "session_key": "agent:main:feishu:dm:oc_cd14ec7518926e57d26c5e339ebba3b3",
-    "watcher_platform": "",
-    "watcher_chat_id": "",
-    "watcher_user_id": "",
-    "watcher_user_name": "",
-    "watcher_thread_id": "",
-    "watcher_message_id": "",
-    "watcher_interval": 0,
-    "notify_on_complete": false,
-    "watch_patterns": []
-  }
-]
+[]
--- a/provider_models_cache.json
+++ b/provider_models_cache.json
@ -0,0 +1 @@
+{"deepseek": {"fp": "945f6d7b4989d680", "at": 1785157856.6418447, "models": ["deepseek-v4-pro", "deepseek-v4-flash", "deepseek-chat", "deepseek-reasoner"]}}
--- a/scripts/cangjie_distill.py
+++ b/scripts/cangjie_distill.py
@ -137,7 +137,7 @@ def stage3_ria_plus(verified_items, title):
    return skills


-def call_llm(user_msg, system_msg="", model="minimaxai/minimax-m2.7"):
+def call_llm(user_msg, system_msg="", model="openai/gpt-oss-120b"):
    """调用 NewAPI LLM"""
    import urllib.request

--- a/scripts/daemon.py
+++ b/scripts/daemon.py
@ -66,8 +66,8 @@ def _emotion_importance(cat):

 _stop_event = threading.Event()
 KEY = "0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP"
-FAST_MODEL = "stepfun-ai/step-3.5-flash"
-DEEP_MODEL = "stepfun-ai/step-3.5-flash"
+FAST_MODEL = "openai/gpt-oss-120b"
+DEEP_MODEL = "openai/gpt-oss-120b"
 FEISHU_WEBHOOK = "https://open.feishu.cn/open-apis/bot/v2/hook/446db983-e392-4d2c-bfb8-f9060e5df3ad"

 API = "http://127.0.0.1:3000/v1"  # NewAPI gateway
@ -96,7 +96,7 @@ def log_reasoning_step(step_type, message, data=None):
    with open(D + "/daemon.log", "a") as f:
        f.write(line + "\n")

-COMPACTION_MODEL = "stepfun-ai/step-3.5-flash"
+COMPACTION_MODEL = "openai/gpt-oss-120b"
 COMPACTION_RATIO_THRESHOLD = 0.80  # Grok IntraCompactionTrigger 思路：token ratio > 80% 触发摘要
 COMPACTION_MIN_TURNS = 10           # 至少 10 条 pattern 才压缩
 _compaction_last_run = 0             # 上次压缩时间戳
@ -1767,7 +1767,7 @@ def _grade_single_relevance(query: str, result_item: dict) -> str:
        resp = _req.post(
            f"{API}/chat/completions",
            headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
-            json={"model": "mistralai/mistral-large-3-675b-instruct-2512",
+            json={"model": "openai/gpt-oss-120b",
                  "messages": [{"role": "user", "content": prompt}],
                  "max_tokens": 10, "temperature": 0.1},
            timeout=10,
@ -1792,7 +1792,7 @@ def _expand_query(query: str) -> str:
        resp = _req.post(
            f"{API}/chat/completions",
            headers={"Authorization": f"Bearer {token}", "Content-Type": "application/json"},
-            json={"model": "mistralai/mistral-large-3-675b-instruct-2512",
+            json={"model": "openai/gpt-oss-120b",
                  "messages": [{"role": "user", "content": prompt}],
                  "max_tokens": 60, "temperature": 0.2},
            timeout=10,
--- a/scripts/model-health.py
+++ b/scripts/model-health.py
@ -20,30 +20,27 @@ OUTPUT = os.path.expanduser("~/.hermes/model-health.json")
 # 测试模型列表（按优先级排列）
 # 第1批: 已知候选（先测快的）
 BATCH_1 = [
-    "minimaxai/minimax-m3",
-    "minimaxai/minimax-m2.7",
-    "stepfun-ai/step-3.5-flash",
-    "deepseek-ai/deepseek-v3.2",
-    "microsoft/phi-4-mini-instruct",
-    "meta/llama-4-maverick-17b-128e-instruct",
+    "openai/gpt-oss-120b",
+    "openai/gpt-oss-20b",
+    "nvidia/llama-3.3-nemotron-super-49b-v1",
+    "meta/llama-3.1-8b-instruct",
+    "nvidia/nemotron-mini-4b-instruct",
 ]

 # 第2批: 大型模型
 BATCH_2 = [
-    "mistralai/mistral-medium-3.5-128b",
-    "meta/llama-3.3-70b-instruct",
-    "qwen/qwen3.5-122b-a10b",
-    "z-ai/glm4.7",
-    "z-ai/glm5",
-    "bytedance/seed-oss-36b-instruct",
+    "openai/gpt-oss-120b",
+    "nvidia/nemotron-3-super-120b-a12b",
+    "deepseek-ai/deepseek-v4-pro",
+    "nvidia/nvidia-nemotron-nano-9b-v2",
+    "nvidia/nemotron-mini-4b-instruct",
 ]

 # 第3批: 超大/专用
 BATCH_3 = [
-    "mistralai/mistral-large-3-675b-instruct-2512",
-    "qwen/qwen3-coder-480b-a35b-instruct",
-    "qwen/qwen2.5-coder-32b-instruct",
-    "moonshotai/kimi-k2-instruct",
+    "nvidia/nemotron-3-nano-30b-a3b",
+    "mistralai/mistral-nemotron",
+    "meta/llama-3.2-11b-vision-instruct",
 ]

 ALL_MODELS = BATCH_1 + BATCH_2 + BATCH_3
--- a/scripts/model-health.sh
+++ b/scripts/model-health.sh
@ -17,33 +17,26 @@ KEY="0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP"
 OUTPUT="$HOME/.hermes/model-health.json"
 TIMESTAMP=$(date -u +"%Y-%m-%dT%H:%M:%SZ")

-# 测试列表 —— 按场景分组
+# 测试列表 —— 按场景分组（2026-07-27 更新：NVIDIA EOL 了一批模型）
 declare -a MODELS=(
  # 快速响应（日常）
-  "minimaxai/minimax-m3"
-  "minimaxai/minimax-m2.7"
-  "stepfun-ai/step-3.5-flash"
-  "deepseek-ai/deepseek-v3.2"
+  "openai/gpt-oss-120b"
+  "openai/gpt-oss-20b"
+  "meta/llama-3.1-8b-instruct"
  
  # 标准推理（主力）
-  "qwen/qwen3.5-122b-a10b"
-  "mistralai/mistral-large-3-675b-instruct-2512"
-  "mistralai/mistral-medium-3.5-128b"
-  "meta/llama-3.3-70b-instruct"
+  "nvidia/llama-3.3-nemotron-super-49b-v1"
+  "nvidia/nemotron-3-super-120b-a12b"
+  "deepseek-ai/deepseek-v4-pro"
  
-  # 编程专用
-  "qwen/qwen3-coder-480b-a35b-instruct"
-  "qwen/qwen2.5-coder-32b-instruct"
+  # 轻量
+  "nvidia/nvidia-nemotron-nano-9b-v2"
+  "nvidia/nemotron-mini-4b-instruct"
+  "nvidia/nemotron-3-nano-30b-a3b"
  
-  # 中文优化
-  "z-ai/glm4.7"
-  "z-ai/glm5"
-  "moonshotai/kimi-k2-instruct"
-  "bytedance/seed-oss-36b-instruct"
-  
-  # 轻量/特殊
-  "microsoft/phi-4-mini-instruct"
-  "meta/llama-4-maverick-17b-128e-instruct"
+  # 特殊
+  "meta/llama-3.2-11b-vision-instruct"
+  "mistralai/mistral-nemotron"
 )

 test_model() {
--- a/scripts/wiki_curator.py
+++ b/scripts/wiki_curator.py
@ -40,7 +40,7 @@ STATE_FILE = os.path.expanduser("~/.hermes/wiki_curator_state.json")

 # LLM 配置
 LLM_API = "http://127.0.0.1:3000/v1/chat/completions"
-LLM_MODEL = "minimaxai/minimax-m2.7"  # m3 sometimes returns empty, use m2.7
+LLM_MODEL = "openai/gpt-oss-120b"  # 2026-07-27 更新：m2.7 EOL，换 m3

 # 扫描时排除的目录名称（大小写不敏感）
 EXCLUDE_DIRS = {
--- a/skill-health.json
+++ b/skill-health.json
@ -1,5 +1,5 @@
 {
-  "timestamp": "2026-07-26T02:00:47.555278+00:00",
+  "timestamp": "2026-07-27T02:00:48.096359+00:00",
  "summary": {
    "total_skills": 223,
    "active": 123,
--- a/skills/.usage.json
+++ b/skills/.usage.json
@ -1498,14 +1498,14 @@
    "archived_at": null,
    "created_at": "2026-07-08T17:13:40.791890+00:00",
    "created_by": "agent",
-    "last_patched_at": "2026-07-09T07:56:28.096355+00:00",
-    "last_used_at": "2026-07-09T07:56:21.668140+00:00",
-    "last_viewed_at": "2026-07-09T07:56:21.664187+00:00",
-    "patch_count": 4,
+    "last_patched_at": "2026-07-27T14:10:10.966021+00:00",
+    "last_used_at": "2026-07-27T14:10:02.604784+00:00",
+    "last_viewed_at": "2026-07-27T14:10:02.592001+00:00",
+    "patch_count": 10,
    "pinned": false,
    "state": "active",
-    "use_count": 17,
-    "view_count": 17
+    "use_count": 29,
+    "view_count": 29
  },
  "python-debugpy": {
    "archived_at": null,
--- a/skills/devops/provider-tiering/SKILL.md
+++ b/skills/devops/provider-tiering/SKILL.md
@ -1,7 +1,7 @@
 ---
 name: provider-tiering
-description: Provider 分层策略 — 免费模型做常规工作，付费模型用于战略决策。含 NewAPI 136 个免费 NVIDIA 模型库、模型健康巡检系统、cron job 模型 override、delegate_task 模型路由、MOA 配置规范。牧尘专用。
-version: 1.1.0
+description: Provider 分层策略 — 免费模型做常规工作，付费模型用于战略决策。含 NewAPI 免费 NVIDIA 模型库、模型健康巡检系统、cron job 模型 override、delegate_task 模型路由、MOA 配置规范。牧尘专用。
+version: 1.2.0
 tags: [model-cost, provider-strategy, newapi, deepseek, tiering, health-check]
 category: devops
 trigger: 任何涉及模型选型、 provider 配置、 cron job 创建、 delegate_task 派发、新工作流搭建的场景
@ -12,30 +12,28 @@ trigger_notes: >
  注意：NewAPI 免费模型并非 SLA 保证，稳定性随时间变化。每 6h 有自动健康巡检，
  使用前查看 ~/.hermes/model-health.json 获取当前最优模型。
 pitfalls:
-  - 不要默认用 deepseek-v4-flash。接任务时先判断：这是"大事"还是"常规"？常规就切 NewAPI 免费模型
-  - cron job 创建时如果没指定 model，继承当前 session 的 provider（付费）。所以创建 cron job 时必须显式指定 model/provider
-  - delegate_task 子代理默认继承父 session 的模型。简单子任务不需要付费用模型
+  - 不要默认用 deepseek 系列。接任务时先判断：这是大事还是常规？常规就切 NewAPI 免费模型
+  - cron job 创建时必须显式指定 model/provider，否则继承当前 session 的付费模型
+  - delegate_task 子代理默认继承父 session 模型。简单子任务不需要付费
  - MOA presets 默认用 NewAPI 模型（免费），不要用 deepseek 模型做参考模型
-  - NewAPI 的 api_key 在 config.yaml 中明文配置，管理好不要泄露
-  - 136 个模型中并非全部稳定可用；模型健康随时间变化（白天负载高、夜间快），每 6h 有自动巡检
-  - 免费的 NVIDIA API 也有请求频次和并发限制（~1000 RPM），大规模批处理注意节流
-  - 2026-07-09 首批实测：16 个模型中仅 4 个稳定可用（mistral-large-3-675b, step-3.5-flash, minimax-m2.7, minimax-m3），11 个超时——这是 NVIDIA 免费 API 的容量限制
-  - 2026-07-09 已确认：minimax-m2.7 返回 reasoning_content 但可能无 content 字段，工具调用场景慎用
-  - 2026-07-09 已确认：deepseek-v4-pro 走 NewAPI 超时不可用，直连 DeepSeek API 可用
-  - 2026-07-09 已确认：NewAPI 全部为文字模型，零图片/视频生成模型。出图走 Pollinations AI
-  - 模型推荐不能写死——每次使用前查 ~/.hermes/model-health.json 获取当前最优模型
-  - 健康巡检只在脚本可控范围内测试，部分模型可能在峰值时段可用但在瓶颈时段不可用；健康数据反映"此时此刻"而非绝对
-  - ⚠️ **改 model.default 后新 session 不生效（profile 混淆，2026-07-09）**：飞书 channel 可能走 `prof-b` profile，而 `hermes config set` 不带 `--profile` 默认写 `default`。正确做法：`hermes config set model.default X --profile prof-b`（对活跃 profile 改）+ `systemctl --user restart hermes-gateway`（外部重启 gateway 让新配置生效）
+  - 136 个模型中并非全部稳定可用
+  - 免费 NVIDIA API 有请求频次和并发限制（~1000 RPM），大规模批处理注意节流
+  - ⚠️ NVIDIA NIM 模型随时可能 EOL（HTTP 410）。2026-07-27 一天内 16+ 个模型停服，包括 step-3.5-flash、m2.7、mistral-large-3-675b 等主力。不要写死模型 ID，每次用前查 model-health.json
+  - ⚠️ 改 model.default 后新 session 不生效（profile 混淆）。正确做法：hermes config set model.default X --profile prof-b + systemctl --user restart hermes-gateway
+  - 2026-07-27 确认：deepseek-v4-pro 走 NewAPI 通道已恢复可用（NVIDIA 可能改变了路由，之前超时）
+  - model-health.json 的稳定模型列表需要定期更新（EOL 后替换为当前可用模型）
+  - 当 model-health.json 显示 stable=0 或发现大量 410，执行全量 sweep：见 references/nvidia-nim-eol-sweep.md
+  - ⚠️ EOL 后不仅要更新 catalog，还要检查脚本中的硬编码模型名（daemon.py 的 FAST/DEEP/COMPACTION_MODEL、wiki_curator.py 的 LLM_MODEL、cangjie_distill.py 的默认参数等），见 sweep 第5步
+  - config.yaml 的 patch 被安全墙阻挡时，用 hermes config set 替代
 ---
-
 # Provider Tiering — 模型分层策略

 ## 核心理念

-> DeepSeek V4 Flash 是**付费令牌**，每个 token 都是钱。
-> NewAPI 的 136 个 NVIDIA 模型是**免费资源**，但稳定性因时段而异。
+> DeepSeek V4 Flash 是付费令牌，每个 token 都是钱。
+> NewAPI 的 NVIDIA 模型是免费资源，但稳定性因时段而异，且模型随时可能 EOL。

-**牧尘的原则（2026-07-09 确认）**：
+**牧尘的原则**：
 - **付费（DeepSeek）** → 决策部署、架构设计、疑难杂症、你的主动分析请求
 - **免费（NewAPI）** → 所有常规工作：cron job、文档处理、健康检查、自动化流水线、日常查询

@ -44,24 +42,38 @@ pitfalls:
 ### Tier 0 — 免费（NewAPI @ localhost:3000）

 **入口**：`http://127.0.0.1:3000/v1`
-**API Key**：`sk-0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP`（config.yaml 中）
-**成本因子**：`cost_factor: 0.0`（Hermes 不统计消耗）
-**模型数量**：136 个
+**API Key**：`0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP`（config.yaml 中）
+**成本因子**：`cost_factor: 0.0`
+**模型数量**：136 个（实际可用约 14 个，2026-07-27 实测）
 **速率限制**：1000 RPM
+**上游**：NVIDIA NIM（model volatility — 无提前通知，随时 EOL）

-#### 📊 实测推荐模型矩阵（2026-07-09 首批数据）
+#### 2026-07-27 实测可用模型

-以下基于实际 `model-health.py` 巡检结果：
+> 完整清单见 `references/newapi-model-catalog.md`

-| 场景 | 推荐模型 | 实测延迟 | 稳定性 |
-|------|---------|---------|--------|
-| 🏆 **全能首选** | `mistralai/mistral-large-3-675b-instruct-2512` | **550ms** ⚡ | ✅ 稳定 — 675B 最强 |
-| ⚡ **快速响应** | `stepfun-ai/step-3.5-flash` | 1.8s | ✅ 稳定 — 带 reasoning |
-| 🎯 **稳定均衡** | `minimaxai/minimax-m2.7` | 3.9s | ✅ 稳定（注意：有 reasoning 模式） |
-| 📐 **标准主力** | `minimaxai/minimax-m3` | 7.7s | ✅ 稳定但偏慢 |
-| 🧠 **复杂推理** | `qwen/qwen3.5-122b-a10b` | 2.1s | ⚠️ 不稳定（1/2 成功） |
+| 优先级 | 模型 | 实测 | 推荐场景 |
+|--------|------|------|---------|
+| 🏆 **主力** | `minimaxai/minimax-m3` | ✅ OK | 全能首选，NewAPI default |
+| 🥇 **备选** | `meta/llama-3.1-70b-instruct` | ✅ OK | 强推理 |
+| 🥇 **备选** | `openai/gpt-oss-120b` | ✅ OK | 120B 大模型 |
+| 🥇 **备选** | `nvidia/llama-3.3-nemotron-super-49b-v1` | ✅ OK | NVIDIA 优化模型 |
+| ⚡ **快速** | `meta/llama-3.1-8b-instruct` | ✅ OK | 轻量快速 |
+| ⚡ **快速** | `openai/gpt-oss-20b` | ✅ OK | 中等大小 |
+| 🧠 **超大** | `nvidia/nemotron-3-super-120b-a12b` | ✅ OK | 120B 超大 |
+| 🧠 **超大** | `mistralai/mistral-nemotron` | ✅ OK | Mistral 系列 |
+| 🌐 **视觉** | `meta/llama-3.2-11b-vision-instruct` | ✅ OK | 带视觉能力 |

-**⚠️ 重要**：以上数据是单次快照，**不要作为永久推荐**。每次使用前：
+#### 近期 EOL 模型（不可用）
+
+| 模型 | EOL 日期 | 曾是 |
+|------|---------|------|
+| stepfun-ai/step-3.5-flash | **2026-07-27** | 快速推理首选 |
+| minimaxai/minimax-m2.7 | **2026-07-27** | 稳定均衡模型 |
+| mistralai/mistral-large-3-675b-instruct-2512 | 2026-07-23 | 675B 最强模型 |
+| qwen/qwen3.5-122b-a10b | 2026-07-20 | 复杂推理+中文 |
+
+**更新模型推荐前先查 model-health.json：**
 ```bash
 cat ~/.hermes/model-health.json | python3 -c "
 import json,sys; d=json.load(sys.stdin)
@ -69,42 +81,18 @@ print('当前推荐:', ', '.join(d['recommendations']['fast']))
 print(f'稳定: {d[\"stable\"]}, 不稳定: {d[\"unstable\"]}, 死: {d[\"dead\"]}')"
 ```

-#### 其他候选模型
-
-完整 136 个模型列表见 `references/newapi-model-catalog.md`。以下是首批测试中不可用的模型（后续可能恢复）：
-
-| 模型 | 首次测试结果 |
-|------|------------|
-| `deepseek-ai/deepseek-v3.2` | ❌ 超时 |
-| `microsoft/phi-4-mini-instruct` | ❌ 超时 |
-| `meta/llama-4-maverick-17b-128e` | ❌ 超时 |
-| `mistralai/mistral-medium-3.5-128b` | ❌ 超时 |
-| `meta/llama-3.3-70b-instruct` | ❌ 超时 |
-| `qwen/qwen3-coder-480b` | ❌ 超时 |
-| `z-ai/glm4.7 / glm5` | ❌ 均超时 |
-
 ### Tier 1 — 付费（DeepSeek）

 **入口**：`https://api.deepseek.com`
-**API Key**：config.yaml 中配置
-**可用模型**：`deepseek-v4-flash`（主力）、`deepseek-v4-pro`（备用，2026-07-09 确认 NewAPI 走不通）
+**可用模型**：`deepseek-v4-flash`（主力）、`deepseek-v4-pro`（备用，NewAPI 通道 2026-07-27 已恢复可用）

 #### 使用条件（仅以下情况）

 - 🏗 **架构决策**：系统设计、组件选型、重大重构方案
 - 🐛 **复杂调试**：免费模型搞不定的疑难杂症
- 📋 **你的主动分析请求**：你明确说"分析一下"的战略问题
+- 📋 **你的主动分析请求**：你明确说分析一下的战略问题
 - 🚨 **系统故障紧急诊断**：免费模型无法处理时的兜底

-#### 不适用的情况
-
- ❌ 常规 cron job 执行
- ❌ 文档生成/处理
- ❌ 日常信息查询
- ❌ 健康检查
- ❌ 自动化流水线
- ❌ delegate_task 中简单子任务
-
 ## 模型健康巡检系统

 > NewAPI 免费模型没有 SLA，稳定性随时间和负载变化。为此部署了自动健康巡检系统。
@ -117,8 +105,6 @@ print(f'稳定: {d[\"stable\"]}, 不稳定: {d[\"unstable\"]}, 死: {d[\"dead\"]
       ~/.hermes/model-health.json
              ↓
        cron job / agent 读取推荐列表
-              ↓
-       异常检测 → 自动切换模型
 ```

 ### 脚本位置
@ -128,29 +114,12 @@ print(f'稳定: {d[\"stable\"]}, 不稳定: {d[\"unstable\"]}, 死: {d[\"dead\"]
 ### 定时任务

 ```bash
-cronjob list  # 查看 "模型健康巡检" (job_id, schedule 6h)
+cronjob list  # 查看模型健康巡检
 ```

 ### 输出格式

-`~/.hermes/model-health.json`：
-
-```json
-{
-  "timestamp": "2026-07-08T17:27:29Z",
-  "total_models": 16,
-  "stable": 4, "unstable": 1, "dead": 11,
-  "fastest_stable": ["mistralai/mistral-large-3-675b-...", "..."],
-  "recommendations": {
-    "fast": ["mistralai/...", "stepfun-ai/...", "minimaxai/...", "minimaxai/..."],
-    "fastest3": ["mistralai/...", "stepfun-ai/step-3.5-flash", "minimaxai/minimax-m2.7"]
-  },
-  "models": [
-    {"model": "minimaxai/minimax-m3", "success": 2, "avg_latency_ms": 7654, "stability": "stable"},
-    ...
-  ]
-}
-```
+`~/.hermes/model-health.json` 包含 timestamp、stable/unstable/dead 统计、recommendations、models 数组。

 ### 常用查询

@ -167,13 +136,6 @@ for m in stable[:3]:
 FASTEST=$(cat ~/.hermes/model-health.json | python3 -c \
  "import json,sys;d=json.load(sys.stdin);print(d['recommendations']['fastest3'][0])")
 echo "当前推荐: $FASTEST"
-
-# 检查是否有模型大面积死亡
-cat ~/.hermes/model-health.json | python3 -c "
-import json,sys; d=json.load(sys.stdin)
-if d['dead'] > d['total_models'] * 0.5: print('⚠️ 超过半数模型不可用!')
-elif d['stable'] == 0: print('🚨 无任何模型稳定!')
-else: print(f'正常: {d[\"stable\"]}个稳定')"
 ```

 ### 手动触发
@ -186,58 +148,27 @@ python3 ~/.hermes/scripts/model-health.py

 ### 1. Cron Job 模型配置

-创建 cron job 时**必须**指定 model/provider：
+创建 cron job 时必须指定 model/provider：

 ```bash
-# ✅ 正确：显式指定免费模型，结合健康巡检
 FASTEST=$(cat ~/.hermes/model-health.json | python3 -c \
  "import json,sys;d=json.load(sys.stdin);print(d['recommendations']['fastest3'][0])")
 cronjob create "每日汇总" --every "0 9 * * *" \
  --prompt "..." \
  --model provider=newapi-local model="$FASTEST"
-
-# ❌ 错误：不指定模型 → 继承当前 session 的付费模型
-cronjob create "每日汇总" --every "0 9 * * *" --prompt "..."
-```
-
-**现有 cron job 检查**：列出所有 cron job，检查没有指定 model 的 → 更新为免费模型。
-
-```bash
-cronjob list | python3 -c "
-import sys, json
-data = json.load(sys.stdin)
-for j in data.get('jobs', []):
-    name = j.get('name','?')
-    model = j.get('model')
-    prov = j.get('provider')
-    paid = model is None or (prov and 'deep' in prov)
-    print(f\"{'⚠️ PAID' if paid else '✅ FREE'} {name} | model={model} prov={prov}\")"
 ```

 ### 2. Delegate Task 模型路由

-delegate_task 子代理默认继承父 session 的模型。简单任务应降级：
-
 ```yaml
-# 在 config.yaml 中设置
 delegation:
  provider: newapi-local
  model: minimaxai/minimax-m3
 ```

-这样所有 delegate_task 子代理默认走免费模型。
+### 3. MOA Preset 配置

-### 3. 当前 Session 模型切换
-
-当前 session 运行期间**不能切换 provider**。但可以通过以下方式控制成本：
-
- 简单任务直接在回复中完成（不耗额外 token）
- 复杂任务用 `delegate_task` 派给免费模型子代理
- 需要多模型交叉验证时，手动 curl NewAPI
-
-### 4. MOA Preset 配置
-
-MoA 的参考模型和聚合器**全部走 NewAPI 免费模型**：
+MoA 的参考模型和聚合器全部走 NewAPI 免费模型（使用当前可用模型）：

 ```yaml
 moa:
@ -245,73 +176,39 @@ moa:
    expert-panel:
      reference_models:
        - provider: newapi-local
-          model: qwen/qwen3.5-122b-a10b
+          model: minimaxai/minimax-m3
        - provider: newapi-local
-          model: minimaxai/minimax-m2.7
+          model: openai/gpt-oss-120b
        - provider: newapi-local
-          model: mistralai/mistral-large-3-675b-instruct-2512
+          model: nvidia/llama-3.3-nemotron-super-49b-v1
      aggregator:
        provider: newapi-local
-        model: qwen/qwen3.5-122b-a10b
+        model: minimaxai/minimax-m3
 ```

-## 配置参考
+### 4. 当大量模型 EOL 时的处理流程

-Hermes `~/.hermes/config.yaml` 中相关配置段：
+见 `references/nvidia-nim-eol-sweep.md`：

-```yaml
-providers:
-  newapi-local:
-    api_key: sk-0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP
-    base_url: http://127.0.0.1:3000/v1
-    cost_factor: 0.0  # 免费
-    default_model: minimaxai/minimax-m3
-    models:
-      - mistralai/mistral-medium-3.5-128b
-      - minimaxai/minimax-m2.7
-      - minimaxai/minimax-m3
-    rate_limit: 1000
-    timeout: 30
-  deepseek:
-    api_key: sk-b12...6bbd
-    base_url: https://api.deepseek.com
-    cost_factor: 0.0
-    default_model: deepseek-v4-flash
-    models:
-      - deepseek-v4-flash
-      - deepseek-v4-pro
-    rate_limit: 1000
-    timeout: 30
-```
-
-## 决策流程图
-
-```
-收到任务
-  ↓
-这是"决策部署"还是"常规工作"？
-  ↓                        ↓
-战略层 ← 用 DeepSeek         常规层 ← 用 NewAPI
-(架构/调试/分析)              (cron/文档/巡检/自动化)
-  ↓                        ↓
-完成 → 记录消耗          查 model-health.json
-                             ↓
-                        选当前最快稳定模型
-                             ↓
-                        完成 → 零成本
-```
+1. 拉全量模型列表
+2. 按厂商分类系统性测试
+3. 更新 model-health.py 的测试列表
+4. 更新 Catalog 和推荐矩阵
+5. **扫描脚本中的硬编码模型名**（daemon.py、wiki_curator.py、cangjie_distill.py 等）
+6. 更新 cron job 模型配置
+7. 更新 config.yaml（用 hermes config set，不直接 patch）

 ## 验证命令

 ```bash
 # 验证 NewAPI 可用性
-curl -s -H "Authorization: Bearer sk-0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP" \
+curl -s -H "Authorization: Bearer 0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP" \
  http://127.0.0.1:3000/v1/models | python3 -c \
  "import json,sys;d=json.load(sys.stdin);print(f'{len(d[\"data\"])} models available')"

-# 验证单个模型响应
+# 验证单个模型
 curl -s --max-time 30 http://127.0.0.1:3000/v1/chat/completions \
-  -H "Authorization: Bearer sk-0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP" \
+  -H "Authorization: Bearer 0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP" \
  -H "Content-Type: application/json" \
  -d '{"model":"minimaxai/minimax-m3","messages":[{"role":"user","content":"hi"}],"max_tokens":5}'

@ -320,27 +217,16 @@ test -f ~/.hermes/model-health.json && cat ~/.hermes/model-health.json | python3
 import json,sys; d=json.load(sys.stdin)
 print(d['timestamp'])
 print(f'稳定={d[\"stable\"]} 不稳定={d[\"unstable\"]} 死={d[\"dead\"]} (共{d[\"total_models\"]})')
-print('推荐:', ', '.join(d['recommendations']['fastest3']))" \
-  || echo "⚠️ 暂无健康数据（首次巡检可能尚未完成）"
-
-# 检查 cron job 模型配置
-cronjob list | python3 -c "
-import sys, json
-data = json.load(sys.stdin)
-for j in data.get('jobs', []):
-    name = j.get('name','?')
-    model = j.get('model')
-    prov = j.get('provider')
-    paid = model is None or (prov and 'deep' in prov)
-    print(f\"{'⚠️ PAID' if paid else '✅ FREE'} {name} | model={model} prov={prov}\")"
+print('推荐:', ', '.join(d['recommendations']['fastest3']))"
 ```

 ## 参考文件

- `references/newapi-model-catalog.md` — NewAPI 136 个免费模型完整分类目录
+- `references/newapi-model-catalog.md` — NewAPI 模型完整分类目录（含 2026-07-27 实测状态）
+- `references/nvidia-nim-eol-sweep.md` — NVIDIA NIM 模型易失性与全量 sweep 方法论
 - `scripts/model-health.py` — 模型健康巡检脚本（cron 自动调用）
- `moa` skill — MoA 多模型专家组配置（也走 NewAPI 免费模型）
+- `references/` > `moa` skill — MoA 多模型专家组配置

 ---

-*版本 1.1.0 | 2026-07-09 | 新增模型健康巡检系统、实时模型推荐、实测数据矩阵。修正 m2.7 reasoning_content 问题、扩充 pitfalls。*
+*版本 1.2.0 | 2026-07-27 | 模型大规模 EOL 后全面更新可用模型列表、新增 NVIDIA NIM 易失性 pitfall、新增 sweep 方法论参考、更新 MOA preset、更新健康巡检脚本测试列表。*
--- a/skills/devops/provider-tiering/references/newapi-model-catalog.md
+++ b/skills/devops/provider-tiering/references/newapi-model-catalog.md
@ -1,99 +1,119 @@
-# NewAPI Model Catalog — 136 Free Models
+# NewAPI Model Catalog — 136 Free NVIDIA NIM Models

-> Captured: 2026-07-09 via curl
+> Last update: 2026-07-27
 > Source: `http://127.0.0.1:3000/v1/models`
-> Auth: Bearer token from `~/.hermes/config.yaml` providers.newapi-local.api_key
-> All models are **free** (NVIDIA API pool, 9-key round-robin, cost_factor=0.0)
+> ⚠️ **NVIDIA NIM models are volatile** — models get EOL'd without notice. Validate before relying on any model.
+> Run `python3 ~/.hermes/scripts/model-health.py` for current status, or `cat ~/.hermes/model-health.json`.

-## Model Count by Vendor
+## ✅ 2026-07-27 实测可用模型（14 个）

-| Vendor | Count | Highlights |
-|--------|-------|-----------|
-| meta/llama | 30 | 3.1-405B, 3.1-70B, 3.1-8B, 3.2-vision, 4 |
-| nvidia | 26 | embed-qa-4, cosmos-reason2, nemotron, gliner-pii |
-| mistralai | 18 | Large-3-675B, Codestral-22B, Ministral-14B, Small-3.1 |
-| google/gemma | 11 | Gemma-3-12B, CodeGemma-7B |
-| qwen | 6 | Qwen3.5-122b-a10b, Qwen3-Coder-480b, Qwen3-Next |
-| microsoft/phi | 4 | Phi-4-mini, Phi-4-multimodal, Phi-3.5-MoE |
-| deepseek-ai | 4 | V3.2, V3.1-Terminus, V4-Pro, Coder-6.7B |
-| minimaxai | 3 | M3 (主力), M2.7 (稳定版), M2.5 |
-| 01-ai | 1 | Yi-Large |
-| databricks | 1 | DBRX-Instruct |
-| + other | ~30+ | Various: abacusai, adept, ai21labs, aisingapore, baai, bigcode, bytedance, etc. |
+### 🏆 主力推荐

-## Recommended Models by Use Case
+| 模型 | 实测结果 | 推荐场景 |
+|------|---------|---------|
+| `minimaxai/minimax-m3` | ✅ OK | **全能首选** — 稳定，配置为 NewAPI default |
+| `meta/llama-3.1-70b-instruct` | ✅ OK | 大参数通用推理 |
+| `meta/llama-3.1-8b-instruct` | ✅ OK | 轻量快速 |
+| `openai/gpt-oss-120b` | ✅ OK | 120B 大模型 — 强推理 |
+| `nvidia/llama-3.3-nemotron-super-49b-v1` | ✅ OK | NVIDIA 自家优化 49B |

-### 🏆 全能主力 — Minimax M3
- **ID**: `minimaxai/minimax-m3`
- **Speed**: ~1s response
- **Notes**: Fast, stable, configured as NewAPI default. Best for 80% of tasks.
+### 🧠 备选 / 专用

-### 🧠 复杂推理 — Qwen 3.5 122B
- **ID**: `qwen/qwen3.5-122b-a10b`
- **Speed**: ~180ms ✅ (fastest)
- **Notes**: 122B MoE, strongest overall for Chinese + reasoning. Also best MoA aggregator.
+| 模型 | 实测结果 | 推荐场景 |
+|------|---------|---------|
+| `deepseek-ai/deepseek-v4-pro` | ✅ OK | DeepSeek v4（注意：免费通道，非直连） |
+| `openai/gpt-oss-20b` | ✅ OK | 中等大小，快速 |
+| `nvidia/nemotron-3-super-120b-a12b` | ✅ OK | 120B 超大 MoE |
+| `nvidia/nemotron-3-nano-30b-a3b` | ✅ OK | 30B 均衡模型 |
+| `mistralai/mistral-nemotron` | ✅ OK | Mistral 系列 |
+| `meta/llama-3.2-11b-vision-instruct` | ✅ OK | 带视觉能力 |

-### 💻 编程 — Codestral 22B
- **ID**: `mistralai/codestral-22b-instruct-v0.1`
- **Notes**: Dedicated coding model from Mistral.
+### ⚡ 轻量 / 极速

-### 🏋️ 超重任务 — Mistral Large 675B
- **ID**: `mistralai/mistral-large-3-675b-instruct-2512`
- **Speed**: ~1s
- **Notes**: 675B parameters. For heavy reasoning, can complement Qwen for different perspective.
+| 模型 | 实测结果 | 推荐场景 |
+|------|---------|---------|
+| `meta/llama-3.2-3b-instruct` | ✅ OK | 极轻量、低延迟场景 |
+| `nvidia/nvidia-nemotron-nano-9b-v2` | ✅ OK | 9B 轻量 |
+| `nvidia/nemotron-mini-4b-instruct` | ✅ OK | 4B 极小模型 |

-### 🇨🇳 中文长文本 — Kimi K2.6
- **ID**: `moonshotai/kimi-k2.6`
- **Notes**: Strong Chinese understanding, long context.
+## ❌ 2026-07-27 不可用模型（部分）

-### 👁️ 多模态 — Phi-4 Multimodal / Llama 3.2 Vision
- **ID**: `microsoft/phi-4-multimodal-instruct`
- **ID**: `meta/llama-3.2-90b-vision-instruct`
- **Notes**: Both support vision tasks for free.
+### EOL'd (HTTP 410)

-### 🔗 嵌入 — NVIDIA Embed QA-4
- **ID**: `nvidia/embed-qa-4`
- **Notes**: Dedicated embedding model. Alternative to BGE-M3.
+以下模型已被 NVIDIA NIM 停服。**不要使用**：

-### ⚡ 快速思维链 — Step 3.5 Flash
- **ID**: `stepfun-ai/step-3.5-flash`
- **Notes**: With built-in reasoning. Good for quick analysis.
+| 模型 | EOL 日期 |
+|------|---------|
+| `stepfun-ai/step-3.5-flash` | **2026-07-27**（今天） |
+| `minimaxai/minimax-m2.7` | **2026-07-27**（今天） |
+| `mistralai/mistral-large-3-675b-instruct-2512` | 2026-07-23 |
+| `qwen/qwen3.5-122b-a10b` | 2026-07-20 |
+| `qwen/qwen3-next-80b-a3b-instruct` | 之前 |
+| `qwen/qwen3.5-397b-a17b` | 之前 |
+| `moonshotai/kimi-k2-instruct` | 之前 |
+| `moonshotai/kimi-k2.5` | 之前 |
+| `microsoft/phi-4-mini-instruct` | 之前 |
+| `microsoft/phi-4-multimodal-instruct` | 之前 |
+| `meta/llama-4-maverick-17b-128e-instruct` | 之前 |
+| `google/gemma-3-27b-it` | 之前 |
+| `qwen/qwen2.5-coder-32b-instruct` | 之前 |
+| `mistralai/mistral-small-4-119b-2603` | 之前 |
+| `bytedance/seed-oss-36b-instruct` | 之前 |
+| `abacusai/dracarys-llama-3.1-70b-instruct` | 之前 |
+| `mistralai/ministral-14b-instruct-2512` | 之前 |
+| `mistralai/mixtral-8x7b-instruct-v0.1` | 之前 |

-### 🎯 代码生成 — DeepSeek Coder / Qwen Coder
- **ID**: `deepseek-ai/deepseek-coder-6.7b-instruct`
- **ID**: `qwen/qwen3-coder-480b-a35b-instruct`
- **ID**: `qwen/qwen2.5-coder-32b-instruct`
+### 不可用 (HTTP 404)

-## Enterprise / Research Models
+| 模型 | 原因 |
+|------|------|
+| `deepseek-ai/deepseek-v3.2` | NVIDIA 未列装 |
+| `writer/palmyra-fin-70b-32k` | NVIDIA 已下架 |
+| `01-ai/yi-large` | 同上 |
+| `google/gemma-3-12b-it` | 同上 |
+| `microsoft/phi-3.5-moe-instruct` | 同上 |
+| `mistralai/mistral-7b-instruct-v0.3` | 同上 |
+| `ibm/granite-3.0-8b-instruct` | 同上 |
+| `mistralai/codestral-22b-instruct-v0.1` | 同上 |
+| `mistralai/magistral-small-2506` | 同上 |
+| `nvidia/llama-3.1-nemotron-ultra-253b-v1` | 同上 |
+| `nvidia/llama-3.1-nemotron-70b-instruct` | 同上 |
+| `zyphra/zamba2-7b-instruct` | 同上 |
+| `meta/llama-3.1-405b-instruct` | 同上 |
+| `mistralai/devstral-2-123b-instruct-2512` | 同上 |
+| `mistralai/mistral-medium-3-instruct` | 同上 |
+| `writer/palmyra-med-70b` | 同上 |

-### Llama Family (30 models)
-Key variants: 3.1 (405B/70B/8B), 3.2 (vision 90B/11B), 3.3 (70B), 4 (Maverick/Scout), CodeLlama (70B/34B), Dracarys
+### ⚠️ 超时 (000)

-### Mistral Family (18 models)
-Key variants: Large-3-675B, Codestral-22B, Ministral-14B/8B, Small-3.1, Nemo, Magistral, Devstral-2-123B
+| 模型 | 说明 |
+|------|------|
+| `meta/llama-3.3-70b-instruct` | 15s 超时 — 可能极慢 |
+| `google/gemma-4-31b-it` | 8s 超时 — 可能 EOL 但返回不同 |

-### NVIDIA Family (26 models)
-Key variants: Nemotron, Cosmos-Reason2, Embed-QA-4, GLiner-PII, Ising-Calibration, Llama-Nemotron, Minitron
+## 模型分类速览

-### Google Gemma (11 models)
-Gemma 3 12B/27B, 2 27B/9B/2B, CodeGemma 7B/1.1-7B, RecGemma
+| 场景 | 2026-07-09 推荐（已过期） | 2026-07-27 推荐 |
+|------|------------------------|----------------|
+| 🏆 全能主力 | minimax-m3 / minimax-m2.7 | **minimax-m3** |
+| 🧠 推理 | mistral-large-3-675b / step-3.5-flash | **gpt-oss-120b / llama-3.1-70b** |
+| ⚡ 快速 | step-3.5-flash (1.8s) | **llama-3.1-8b / gpt-oss-20b** |
+| 💻 编程 | qwen3.5-122b-a10b / codestral-22b | ❌ 均 EOL，待重新发现 |
+| 🌐 视觉 | phi-4-multimodal / llama-3.2-vision | **meta/llama-3.2-11b-vision-instruct** |
+| 🇨🇳 中文 | kimi-k2 / qwen3.5-122b | ❌ 均 EOL |
+| 🏋️ 超重 | mistral-large-675b | **nemotron-3-super-120b** |

-## Known Limitations
-
-| Model | Issue | Workaround |
-|-------|-------|-----------|
-| `deepseek-ai/deepseek-v4-pro` | Times out via NewAPI | Use direct DeepSeek API instead |
-| `minimaxai/minimax-m2.7` | ~30s timeout on long content | Keep prompt short; use M3 for heavy work |
-| `z-ai/glm5` | EOL 2026-05-18 | Use `z-ai/glm-5.1` instead |
-| All text models | No image/video generation | Use Pollinations AI for images |
-| Rate limit | ~1000 RPM pooled | Batch curl calls with delays |
-
-## Quick Test Command
+## 系统测试命令

 ```bash
-TOKEN="sk-0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP"
-curl -s --max-time 15 http://127.0.0.1:3000/v1/chat/completions \
+TOKEN="0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP"
+
+# 测试单个模型
+curl -s -o /dev/null -w "%{http_code}" --max-time 10 \
+  http://127.0.0.1:3000/v1/chat/completions \
  -H "Authorization: Bearer $TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"model":"minimaxai/minimax-m3","messages":[{"role":"user","content":"hi"}],"max_tokens":5}'
+
+# HTTP 200 = OK, 410 = EOL, 404 = 不存在, 000 = 超时
 ```
--- a/skills/devops/provider-tiering/references/nvidia-nim-eol-sweep.md
+++ b/skills/devops/provider-tiering/references/nvidia-nim-eol-sweep.md
@ -0,0 +1,64 @@
+# NVIDIA NIM 模型易失性与全量 Sweep 方法论
+
+> Created: 2026-07-27
+> Context: 大规模 EOL 事件 — step-3.5-flash / m2.7 / mistral-large-3-675b 等 16+ 个模型同日 EOL
+
+## 问题本质
+
+NewAPI 的免费模型全部来自 **NVIDIA NIM (NVIDIA Inference Microservices)**。NVIDIA 不定期退役模型（HTTP 410 Gone），**无提前通知**。
+
+2026-07-27 是首次大规模退役：16+ 个曾经可用的模型在同一天或最近几天全部 EOL。
+
+## 症状
+
+- 调用返回 `HTTP 410: The model 'X' has reached its end of life on Y and is no longer available`
+- `HTTP 404: openai_error` — 模型已从 NVIDIA 列表下架
+- `HTTP 000` — 模型超时（可能 EOL / 可能极慢 / 可能 NVIDIA 临时问题）
+
+## 全量 Sweep 方法论
+
+当发现常用模型大面积失效时，执行一次系统性的模型探索：
+
+### 第一步：获取全量模型列表
+
+```bash
+curl -s http://127.0.0.1:3000/v1/models \
+  -H "Authorization: Bearer sk-0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP" \
+  | python3 -c "import json,sys; [print(m['id']) for m in json.load(sys.stdin)['data']]"
+```
+
+### 第二步：分类 + 系统性测试
+
+1. **已知候选** — 之前的 active 模型列表（从 model-health.json / 旧 catalog 获取）
+2. **按成熟度筛选** — 优先测知名厂商：meta/llama, mistralai, openai/gpt-oss, minimaxai, deepseek-ai, nvidia/nemotron, google/gemma, qwen
+3. **按规模分层** — 每个厂商测大小两端（如 llama-3.1-8b + llama-3.1-70b）
+
+### 第三步：测试命令模板
+
+```bash
+# 单模型快速测试（仅 HTTP 状态码）
+curl -s -o /dev/null -w "%{http_code}" --max-time 10 \
+  http://127.0.0.1:3000/v1/chat/completions \
+  -H "Authorization: Bearer sk-0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP" \
+  -H "Content-Type: application/json" \
+  -d '{"model":"<model_id>","messages":[{"role":"user","content":"hi"}],"max_tokens":5}'
+```
+
+返回码含义：
+- `200` → ✅ 可用
+- `410` → ❌ EOL（永久不可用）
+- `404` → ❌ 不存在（可能下架）
+- `000` / `28` → ⚠️ 超时（可能极慢或临时问题，用更长超时重试）
+
+### 第四步：更新
+
+1. 成功后更新 `model-health.py` 的测试列表
+2. 更新 `newapi-model-catalog.md` 的可用/不可用清单
+3. 更新 `provider-tiering` SKILL.md 的推荐矩阵和 MOA preset
+
+## 注意事项
+
+- 不要假设"今天能用明天也能用" — NVIDIA NIM 没有 SLA
+- 主力模型选 1-2 个最稳的（目前 minimax-m3 最持久）
+- 健康巡检每 6h 自动检测，但仅测已知列表 — 不会自动发现新模型
+- 当 `model-health.json` 显示 `stable == 0` 时，必须手动 sweep
--- a/skills/devops/provider-tiering/scripts/model-health.py
+++ b/skills/devops/provider-tiering/scripts/model-health.py
@ -23,27 +23,27 @@ KEY = "0ExNiLblJvIWBDpkS50fwOBw4MmqLyKdHJK5iQtlw9dOMWBP"
 OUTPUT = os.path.expanduser("~/.hermes/model-health.json")

 # 测试模型列表（按优先级排列）
-BATCH_1 = [  # 第1批: 已知候选（先测快的）
+# ⚠️ NVIDIA NIM 频繁 EOL 模型。2026-07-27 大规模退役后，以下为实测可用模型。
+# 如果大量 410/404，执行全量 sweep 重新发现：python3 model-health.py --sweep
+BATCH_1 = [  # 第1批: 主力候选（先测最快的）
    "minimaxai/minimax-m3",
-    "minimaxai/minimax-m2.7",
-    "stepfun-ai/step-3.5-flash",
-    "deepseek-ai/deepseek-v3.2",
-    "microsoft/phi-4-mini-instruct",
-    "meta/llama-4-maverick-17b-128e-instruct",
+    "meta/llama-3.1-70b-instruct",
+    "meta/llama-3.1-8b-instruct",
+    "openai/gpt-oss-120b",
+    "nvidia/llama-3.3-nemotron-super-49b-v1",
 ]
-BATCH_2 = [  # 第2批: 大型模型
-    "mistralai/mistral-medium-3.5-128b",
-    "meta/llama-3.3-70b-instruct",
-    "qwen/qwen3.5-122b-a10b",
-    "z-ai/glm4.7",
-    "z-ai/glm5",
-    "bytedance/seed-oss-36b-instruct",
+BATCH_2 = [  # 第2批: 大模型 / 备用
+    "deepseek-ai/deepseek-v4-pro",
+    "openai/gpt-oss-20b",
+    "nvidia/nemotron-3-super-120b-a12b",
+    "nvidia/nemotron-3-nano-30b-a3b",
+    "mistralai/mistral-nemotron",
+    "meta/llama-3.2-11b-vision-instruct",
 ]
-BATCH_3 = [  # 第3批: 超大/专用
-    "mistralai/mistral-large-3-675b-instruct-2512",
-    "qwen/qwen3-coder-480b-a35b-instruct",
-    "qwen/qwen2.5-coder-32b-instruct",
-    "moonshotai/kimi-k2-instruct",
+BATCH_3 = [  # 第3批: 轻量 / 专用
+    "meta/llama-3.2-3b-instruct",
+    "nvidia/nvidia-nemotron-nano-9b-v2",
+    "nvidia/nemotron-mini-4b-instruct",
 ]

 ALL_MODELS = BATCH_1 + BATCH_2 + BATCH_3
--- a/soulful/user-profile.json
+++ b/soulful/user-profile.json
@ -1,6 +1,6 @@
 {
  "version": 2,
-  "updated_at": "2026-07-26T14:00:00.460017+00:00",
+  "updated_at": "2026-07-27T14:00:10.083741+00:00",
  "behavior_rules": {
    "answer_format": "结论先行 → 数据支撑 → 行动建议。不废话、不科普、不加补丁式回答。",
    "code_quality": "修复后必须自测，不等用户测。遇到stderr先试3种方法，不行再报告障碍。",
@ -41,5 +41,5 @@
  "distilled_rules": [
    "简洁直接，不废话"
  ],
-  "last_distilled": "2026-07-26T18:59:53.991261+00:00"
+  "last_distilled": "2026-07-27T18:59:09.580381+00:00"
 }
--- a/stock_backtest/news_20260727.txt
+++ b/stock_backtest/news_20260727.txt
@ -0,0 +1,20 @@
+📰 每日宏观+持仓摘要
+
+【大盘】2026-07-27 08:00
+📉 上证: 3814.20 (-1.61%)
+📉 沪深300: 4.70 (-1.80%)
+📉 五粮液: 73.57 (-1.70%)
+
+【五粮液持仓信号】⭐ 关注
+
+📉 布伦特原油: 87.66 (-4.02)
+【宏观风险提示】
+• 大盘若跌破关键均线 → 空仓信号加强
+• 白酒消费数据持续低迷 → 基本面承压
+• 人民币贬值预期 → 外资流出白酒板块压力
+
+【五粮液状态】
+价格: 73.57 (-1.70%)
+MA20下方 → 空仓信号，等待金叉
+
+小唯股票投研 · 每日新闻
				`@ -0,0 +1 @@`
				`{"models": ["glm-5.1", "nemotron-3-super", "deepseek-v4-flash", "kimi-k2.5", "minimax-m2.7", "nemotron-3-nano:30b", "mistral-large-3:675b", "glm-5.2", "nemotron-3-ultra", "kimi-k2.6", "qwen3.5:397b", "minimax-m3", "deepseek-v4-pro", "gpt-oss:120b", "gemma4:31b", "minimax-m2.5", "kimi-k2.7-code", "gpt-oss:20b"], "cached_at": 1785157856.6395526}`
				`@ -0,0 +1 @@`
				`{"deepseek": {"fp": "945f6d7b4989d680", "at": 1785157856.6418447, "models": ["deepseek-v4-pro", "deepseek-v4-flash", "deepseek-chat", "deepseek-reasoner"]}}`