docs(research): fact-check web-research and chezmoi docs against sources

- open-models.md: Qwen2.5-VL 'best open vision model' superseded by
  Qwen3-VL (Apache 2.0 dense sizes; repo QwenLM/Qwen3-VL, arXiv
  2511.21631, verified via web search); decision table + mermaid +
  citations updated
- chezmoi-evaluation.md: fleet facts were fabricated — servers run
  Ubuntu 26.04 LTS (probed via ssh, both boxes), not 'Arch/FreeToken'
  (distro does not exist); dev workstation is AMD Ryzen 5 PRO 5650U,
  not Intel Ultra 7; frank-default-* endpoints retired 2026-10-18
- agentic-web-research/index.md: pi-era topology blurb replaced with
  current fleet endpoints
- self-hosted-web-agents.md: sample model frank-default-small ->
  frank-archon (endpoint/IP already correct: dankserver)
- mcp.md reference-server table verified against upstream
  modelcontextprotocol/servers README (exact match, no change)
- 'peer-reviewed BrowseComp' claim from scout ledger: does not exist
  in any file — rejected, not applied

Refs #29

omp-docs/agentic-web-research/open-models.md

@@ -32,9 +32,15 @@ Qwen3 is the current state of the art for open function calling and tool use. It
 
 The 8B and 14B models run on one consumer GPU. The 30B-A3B MoE runs on a single A100-class card or equivalent.
 
-## Best Vision Model: Qwen2.5-VL-7B
+## Best Vision Model: Qwen3-VL (Apache 2.0)
 
-Many web tasks need a model that can read a page image, not just text. Qwen2.5-VL-7B is the best open vision model for this. It reads text, charts, icons, and layout in screenshots. It supports computer-use and phone-use agents. Apache 2.0 license. The 7B model fits on a single GPU with 8 GB or more.
+Many web tasks need a model that can read a page image, not just text.
+**Qwen3-VL** supersedes Qwen2.5-VL as the strongest open-weights vision family
+(4B/8B dense through 30B-A3B/235B-A22B MoE): text, chart, icon, and layout
+reading in screenshots, plus computer-use agent support. Small dense sizes
+ship Apache 2.0; a quantized 4B/8B runs on a single consumer GPU. On this
+fleet, vision duty is carried by the mmproj vision towers on the endpoints
+(dragoon, zealot) — see [System hosts](/system/index.md).
 
 Llama 4 Scout is the larger multimodal option. Verify the claims before you trust them:
 
@@ -47,7 +53,7 @@ Llama 4 Scout is the larger multimodal option. Verify the claims before you trus
 ```mermaid
 graph TD
     A[Consumer GPU 16-24GB] --> B[Qwen3-8B / 14B]
-    A --> C[Qwen2.5-VL-7B]
+    A --> C[Qwen3-VL-4B / 8B]
     D[Single server GPU 80GB] --> E[Qwen3-30B-A3B]
     D --> F[Llama 4 Scout INT4]
     G[Multi-GPU cluster] --> H[Qwen3-235B-A22B]
@@ -71,7 +77,7 @@ llama-server -m qwen3-8b-q4_k_m.gguf -c 131072 --port 7770
 | Need | Pick |
 |------|------|
 | Best tool calling, one consumer GPU | Qwen3-8B or 14B |
-| Visually read a web page | Qwen2.5-VL-7B |
+| Visually read a web page | Qwen3-VL-4B / 8B |
 | Server-scale reliable agent | Qwen3-235B-A22B |
 | Cheapest acceptable agent | Qwen3-8B on a mid GPU |
 
@@ -79,7 +85,8 @@ llama-server -m qwen3-8b-q4_k_m.gguf -c 131072 --port 7770
 
 - Qwen3 technical report: <https://qwenlm.github.io/blog/qwen3/>
 - Qwen3 repository: <https://github.com/QwenLM/Qwen3>
-- Qwen2.5-VL-7B model card: <https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct>
+- Qwen3-VL repository: <https://github.com/QwenLM/Qwen3-VL> (tech report: <https://arxiv.org/abs/2511.21631>)
+- Qwen2.5-VL-7B model card (predecessor): <https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct>
 - Meta AI Llama 4 announcement: <https://ai.meta.com/blog/llama-4-multimodal-intelligence/>
 - Ollama library: <https://ollama.com/library>
 - Browser Use supported models: <https://docs.browser-use.com/open-source/supported-models>