feat(models): strong/cheap/vision model slots + multi-provider engine federation

Model slots wave (2026-09-20), chunk B:

- settings: new `models` section {strong, cheap, vision} slots (each
  field independent, same shape as a role override); ROLE_SLOT maps all
  nine roles to tiers (strong=prober+teacher, cheap=researcher/
  demoBuilder/extractor/auditor/labeler, vision=visualMaker+pdfReader);
  resolution chain per role: override → slot → factory pin.
- config: ModelSpec gains provider (all pins openrouter, the BYOK
  default); MODEL_PINS in stores.ts now spans all nine roles (the strong
  slot's factory rep IS the prober pin).
- engine: piModels() registers EVERY builtin provider catalog;
  piEngineForSpec(resolved spec) is the new engine factory (pi-ai
  resolves per-provider keys from env itself); piEngineFor stays as the
  config-pin fallback. chat-handler resolves the conversation chain
  (chat override → strong slot → pin) and injects engineFor into the job
  runner, closing the old gap where per-role overrides never reached
  job engines.
- /api/models: models federate ONLY keyed providers (providers surface
  with keyPresent, env-wins, fresh per call); slots (resolved tier pins)
  join rolePins; catalogDefaultsFor inherits the strong slot; the models
  settings section gets the same catalog gate as chat.
- pricing: PRICES/CONTEXT_LIMITS uniformly keyed provider:id
  (regenerated from ALL pi-ai catalogs, 1354 keys); usage stamps
  (TurnUsage, JobUsage, extraction stages) switch to provider:id —
  owner decision: no legacy compat, old stamps render unpriced.

tests/render-activity-dock.test.tsx

@@ -48,7 +48,7 @@ describe("activity dock pure layer", () => {
 	it("folds cost with jobCost; absent usage is null, never zero", () => {
 		const priced = job({
 			usage: {
-				model: "z-ai/glm-5.3-flash",
+				model: "openrouter:z-ai/glm-5.3-flash",
 				inputTokens: 10_000,
 				outputTokens: 1000,
 				cacheReadTokens: 5000,
@@ -67,7 +67,7 @@ describe("activity dock pure layer", () => {
 
 	it("context line = LAST step's tokens vs the model limit, never a cumulative sum", () => {
 		const base = {
-			model: "z-ai/glm-5.3-flash",
+			model: "openrouter:z-ai/glm-5.3-flash",
 			inputTokens: 400_000, // running total (much bigger — must NOT feed the line)
 			outputTokens: 8_000,
 			cacheReadTokens: 0,
@@ -166,7 +166,7 @@ describe("activity section render", () => {
 
 	it("shows total running cost when jobs are priced", () => {
 		const usage = {
-			model: "z-ai/glm-5.3-flash",
+			model: "openrouter:z-ai/glm-5.3-flash",
 			inputTokens: 10_000,
 			outputTokens: 1000,
 			cacheReadTokens: 0,