docs(skill): retire the free JEV model

references/free-models.md

@@ -26,6 +26,3 @@ curl -sS -X POST https://api.beatapi.io/v1/capabilities/search \
   (its id is not always the free id minus `-free`).
 - Free models are a limited-time offer: callable right after signup, with no
   top-up and no card required.
-- A decision model is among them: `model:jev-1.13-free`. It takes `state` and
-  `questions` instead of a prompt:
-  <https://beatapi.io/skill-refs/recipes/decide-with-jev.md>.

references/recipes/decide-with-jev.md

@@ -4,15 +4,15 @@ JEV is a decision model: give it the current state and typed questions, get back
 typed answers with probabilities. It writes no prose, so there is nothing to
 parse. Use it to pick one option, score something on a scale, or answer yes/no.
 
-References: `model:jev-1.13-free` (free, rate limited until the account's first
-top-up) and `model:jev-1.13` (paid, billed per input token; output is free).
-Inspect either for the full schema.
+References: `model:jev-1.13` and `model:jev-1.14` (paid, billed per input token;
+output is free). Both follow the latest JEV release. Inspect either for the full
+schema. There is no free JEV model.
 
 ## Run
 
 ```json
 {
-  "reference": "model:jev-1.13-free",
+  "reference": "model:jev-1.13",
   "input": {
     "state": "We sell a $29/month writing tool. Three landing-page headlines are drafted below. Audience: freelance marketers.\n1) Write faster\n2) Your drafts, done by lunch\n3) AI writing for marketers",
     "questions": {

references/run.md

@@ -50,7 +50,7 @@ Over MCP, pass the same JSON to `capabilities_run`.
 - **Text models** run the same way: `{"reference":"model:<id>","input":{"input":"<prompt>"}}`
   returns `output_text`; `usage` token counts may include upstream system prompts
   and are not comparable across models. **Decision model** JEV:
-  `{"reference":"model:jev-1.13-free","input":{"state":"…","questions":{…}}}` returns
+  `{"reference":"model:jev-1.13","input":{"state":"…","questions":{…}}}` returns
   typed answers with probabilities (question types `noul`, `choice`, `score`;
   a `noul` needs `instructions`, the yes/no question; `score` takes
   at most 10 criteria). To rank many candidates use **one** call:

skills/beatapi-video/references/free-models.md

@@ -26,6 +26,3 @@ curl -sS -X POST https://api.beatapi.io/v1/capabilities/search \
   (its id is not always the free id minus `-free`).
 - Free models are a limited-time offer: callable right after signup, with no
   top-up and no card required.
-- A decision model is among them: `model:jev-1.13-free`. It takes `state` and
-  `questions` instead of a prompt:
-  <https://beatapi.io/skill-refs/recipes/decide-with-jev.md>.

skills/beatapi-video/references/recipes/decide-with-jev.md

@@ -4,15 +4,15 @@ JEV is a decision model: give it the current state and typed questions, get back
 typed answers with probabilities. It writes no prose, so there is nothing to
 parse. Use it to pick one option, score something on a scale, or answer yes/no.
 
-References: `model:jev-1.13-free` (free, rate limited until the account's first
-top-up) and `model:jev-1.13` (paid, billed per input token; output is free).
-Inspect either for the full schema.
+References: `model:jev-1.13` and `model:jev-1.14` (paid, billed per input token;
+output is free). Both follow the latest JEV release. Inspect either for the full
+schema. There is no free JEV model.
 
 ## Run
 
 ```json
 {
-  "reference": "model:jev-1.13-free",
+  "reference": "model:jev-1.13",
   "input": {
     "state": "We sell a $29/month writing tool. Three landing-page headlines are drafted below. Audience: freelance marketers.\n1) Write faster\n2) Your drafts, done by lunch\n3) AI writing for marketers",
     "questions": {

skills/beatapi-video/references/run.md

@@ -50,7 +50,7 @@ Over MCP, pass the same JSON to `capabilities_run`.
 - **Text models** run the same way: `{"reference":"model:<id>","input":{"input":"<prompt>"}}`
   returns `output_text`; `usage` token counts may include upstream system prompts
   and are not comparable across models. **Decision model** JEV:
-  `{"reference":"model:jev-1.13-free","input":{"state":"…","questions":{…}}}` returns
+  `{"reference":"model:jev-1.13","input":{"state":"…","questions":{…}}}` returns
   typed answers with probabilities (question types `noul`, `choice`, `score`;
   a `noul` needs `instructions`, the yes/no question; `score` takes
   at most 10 criteria). To rank many candidates use **one** call:

test/setup-walkthrough.test.mjs

@@ -82,7 +82,8 @@ test('one loop for every capability, driven by the next field', () => {
   // Text and decision models run through the same Run call.
   assert.match(run, /"reference":"model:<id>","input":\{"input":"<prompt>"\}/);
   assert.match(run, /output_text/);
-  assert.match(run, /model:jev-1\.13-free/);
+  assert.match(run, /model:jev-1\.13"/);
+  assert.doesNotMatch(run, /jev-1\.1[34]-free/);
   assert.match(run, /at most 10 criteria/);
   for (const [path, text] of everything) {
     assert.doesNotMatch(text, /\/v1\/capabilities\/run\/status/, path);
@@ -144,7 +145,7 @@ test('free models are discovered at run time, never hardcoded', () => {
   assert.match(free, /Read the numbers from Inspect/);
   assert.match(free, /rate_limit_exceeded/);
   assert.match(free, /limited-time offer/);
-  // The one id the page may name is the decision model its recipe covers.
+  // Free ids change; the page names none of them.
   const ids = new Set([...free.matchAll(/model:([a-z0-9.-]+-free)/g)].map((match) => match[1]));
-  assert.deepEqual([...ids], ['jev-1.13-free']);
+  assert.deepEqual([...ids], []);
 });