Fine-tune the docs landing page, and say who wrote the test tasks

docs/README.md

@@ -9,9 +9,9 @@ folder `/docs`.
 
 | Path | What it is |
 | --- | --- |
-| `index.html` | Landing page: why the experiments were run, what System One models are, the four experiments, the protocol, the notebook log, the limits |
+| `index.html` | Landing page: why the experiments were run, the premise (what Jev is), the four experiments, the process, the notebook log, a note on the level of rigor |
 | `assets/` | Shared by every page: styles (`site.css`) and the theme toggle (`site.js`). Shared by the results pages: `results.css`, and `results.js` (tooltips, chart helpers, the side contents) |
-| `model-router/` | The 2026-10-08 model-router run: `index.html`, `app.js`, and generated `data.js` |
+| `model-router/` | The 2026-10-08 model-router run: `index.html`, `app.js`, generated `data.js`, and two captures of the page's route explorer (`screenshot-light.png`, `screenshot-dark.png`) that the landing page shows as a thumbnail |
 | `godot-jev/` | The 2026-10-08 three-model godot-jev run: `index.html`, `page.css`, `app.js`, a screenshot of the game, and generated `data.js` |
 | `tools/build-model-router-data.mjs` | Builds `model-router/data.js` |
 | `tools/build-godot-jev-data.gd` | Builds `godot-jev/data.js` |

docs/godot-jev/index.html

@@ -73,8 +73,9 @@ <h1>Three Jevs parse <em>16 lines of player slang.</em></h1>
             model, with the moves possible right now as the options of one Choice. I gave three Jevs, one hosted
             and two running on a laptop, the same 16 lines in the same game states, three times each. All three got
             the player to the crown without a wrong move. They differ in how sure they were, how often the game had
-            to ask what the player meant, and how long a turn took on this setup. This is a gut check on a small,
-            hand-written set of lines, not a benchmark: <a href="#caveats">what it does and doesn't show</a>.
+            to ask what the player meant, and how long a turn took on this setup. This is a gut check on a small
+            set of lines written for a recording, not a benchmark:
+            <a href="#caveats">what it does and doesn't show</a>.
           </p>
           <div class="hero-stats" id="hero-stats"></div>
           <div class="legend-models" id="legend-models"></div>

docs/model-router/app.js

@@ -50,7 +50,7 @@
     const offTop = runs.map((r) => N - atDefault(r).routes[ids[TOP]]);
     const sameOff = offTop.every((v) => v === offTop[0]);
     $("#hero-stats").innerHTML = `
-      <div class="stat"><div class="v">${N}<small> tasks</small></div><div class="k">hand-written sub-agent tasks, each asked once of ${runs.length} decision models</div></div>
+      <div class="stat"><div class="v">${N}<small> tasks</small></div><div class="k">sub-agent tasks written and labelled by Claude, each asked once of ${runs.length} decision models</div></div>
       <div class="stat"><div class="v">${under}</div><div class="k">tasks sent to a model too weak for them, by any of the three</div></div>
       <div class="stat"><div class="v">${sameOff ? pct(offTop[0]) : offTop.map(pct).join(" / ")}</div><div class="k">of tasks kept off the most capable model${sameOff ? ", by all three" : ""}. ${misses} miss in ${N * runs.length} decisions.</div></div>
       <div class="stat"><div class="v lat">${runs
@@ -73,7 +73,7 @@
         "1 · Routing",
         "On ≥ 100 real tasks, a bar where ≤ 5% go too low and ≥ 50% leave the top route",
         s.map((x) => `<span class="mark-na">${pct(x.under)} low · ${pct(N - x.routes[ids[TOP]])} off top</span>`),
-        `<span class="stamp">Not yet evidence</span><br><small>24 starter tasks, one author</small>`,
+        `<span class="stamp">Not yet evidence</span><br><small>24 starter tasks, all written by Claude</small>`,
       ],
       [
         "2 · Speed",

docs/model-router/index.html

@@ -71,7 +71,7 @@ <h1>Three Jevs pick the model for <em>24 sub-agent tasks.</em></h1>
             One request to a System One model decides whether a sub-agent runs on Haiku, Sonnet or Opus. I asked
             three Jevs, one hosted and two running on a laptop, to make that call for the same tasks. Their routes
             nearly match. They differ in how sure they were, and in how long an answer took on this setup. This is
-            a gut check on a small, hand-written set of tasks, not a benchmark:
+            a gut check on a small set of tasks that Claude wrote and labelled, not a benchmark:
             <a href="#caveats">what it does and doesn't show</a>.
           </p>
           <div class="hero-stats" id="hero-stats"></div>
@@ -462,7 +462,7 @@ <h2>What this does and doesn't show</h2>
               <span class="label">It doesn't show</span>
               <ul>
                 <li><b>24 tasks, asked once each.</b> One task is 4 percentage points.</li>
-                <li><b>One author wrote everything.</b> The tasks, their labels and the route descriptions came from one sitting, so tasks echo the wording they're judged against ("find the cause" against "a failure with an unknown cause").</li>
+                <li><b>One author wrote everything.</b> Claude wrote the tasks, their labels and the route descriptions in one sitting, so tasks echo the wording they're judged against ("find the cause" against "a failure with an unknown cause").</li>
                 <li><b>Labels are opinions.</b> Nobody ran these tasks on the three Claude models to see which was enough. That needs a harness (check 4).</li>
                 <li><b>Flash 9B's 24 of 24 has little margin.</b> On tasks 13 to 16 it was close to an even split between two routes.</li>
                 <li><b>The tasks don't separate the models.</b> All three are at or near 24 of 24, so this says nothing about which decides best.</li>

model-router/eval/results-2026-10-08.md

@@ -6,9 +6,10 @@ sources: `results-2026-10-08T16-41-27-867Z.json` (27B), `results-2026-10-08T18-4
 
 An agent harness has to pick a model each time its orchestrator spawns a sub-agent. model-router
 makes that choice with one request to a System One model (Jev), which returns probabilities, not
-text. This is the first live run: 24 hand-written tasks, each sent once to three decision models.
-One is TypeSafe's hosted Jev. The other two are [Open Jev](https://huggingface.co/openjev) models
-running locally: the 27B model, and Flash 9B, a smaller one released the day before.
+text. This is the first live run: 24 tasks that Claude wrote and labelled, each sent once to three
+decision models. One is TypeSafe's hosted Jev. The other two are
+[Open Jev](https://huggingface.co/openjev) models running locally: the 27B model, and Flash 9B, a
+smaller one released the day before.
 
 ## Result