fix: improve model resolution with client API fallback and explicit model passing

- fetchAvailableModels now falls back to client.model.list() when cache is empty
- provider-models cache empty → models.json → client API (3-tier fallback)
- look-at tool explicitly passes registered agent's model to session.prompt
- Ensures multimodal-looker uses correctly resolved model (e.g., gemini-3-flash-preview)
- Add comprehensive tests for fuzzy matching and fallback scenarios

src/tools/delegate-task/tools.test.ts

@@ -302,6 +302,36 @@ describe("sisyphus-task", () => {
       expect(result).toBeNull()
     })
 
+    test("blocks requiresModel when availability is known and missing the required model", () => {
+      // #given
+      const categoryName = "deep"
+      const availableModels = new Set<string>(["anthropic/claude-opus-4-5"])
+
+      // #when
+      const result = resolveCategoryConfig(categoryName, {
+        systemDefaultModel: SYSTEM_DEFAULT_MODEL,
+        availableModels,
+      })
+
+      // #then
+      expect(result).toBeNull()
+    })
+
+    test("blocks requiresModel when availability is empty", () => {
+      // #given
+      const categoryName = "deep"
+      const availableModels = new Set<string>()
+
+      // #when
+      const result = resolveCategoryConfig(categoryName, {
+        systemDefaultModel: SYSTEM_DEFAULT_MODEL,
+        availableModels,
+      })
+
+      // #then
+      expect(result).toBeNull()
+    })
+
     test("returns default model from DEFAULT_CATEGORIES for builtin category", () => {
       // #given
       const categoryName = "visual-engineering"

src/tools/look-at/tools.test.ts

@@ -146,4 +146,62 @@ describe("look-at tool", () => {
       expect(result).toContain("Network connection failed")
     })
   })
+
+  describe("createLookAt model passthrough", () => {
+    // #given multimodal-looker agent has resolved model info
+    // #when LookAt 도구 실행
+    // #then session.prompt에 model 정보가 전달되어야 함
+    test("passes multimodal-looker model to session.prompt when available", async () => {
+      let promptBody: any
+
+      const mockClient = {
+        app: {
+          agents: async () => ({
+            data: [
+              {
+                name: "multimodal-looker",
+                mode: "subagent",
+                model: { providerID: "google", modelID: "gemini-3-flash" },
+              },
+            ],
+          }),
+        },
+        session: {
+          get: async () => ({ data: { directory: "/project" } }),
+          create: async () => ({ data: { id: "ses_model_passthrough" } }),
+          prompt: async (input: any) => {
+            promptBody = input.body
+            return { data: {} }
+          },
+          messages: async () => ({
+            data: [
+              { info: { role: "assistant", time: { created: 1 } }, parts: [{ type: "text", text: "done" }] },
+            ],
+          }),
+        },
+      }
+
+      const tool = createLookAt({
+        client: mockClient,
+        directory: "/project",
+      } as any)
+
+      const toolContext = {
+        sessionID: "parent-session",
+        messageID: "parent-message",
+        agent: "sisyphus",
+        abort: new AbortController().signal,
+      }
+
+      await tool.execute(
+        { file_path: "/test/file.png", goal: "analyze image" },
+        toolContext
+      )
+
+      expect(promptBody.model).toEqual({
+        providerID: "google",
+        modelID: "gemini-3-flash",
+      })
+    })
+  })
 })

src/tools/look-at/tools.ts

@@ -3,7 +3,7 @@ import { pathToFileURL } from "node:url"
 import { tool, type PluginInput, type ToolDefinition } from "@opencode-ai/plugin"
 import { LOOK_AT_DESCRIPTION, MULTIMODAL_LOOKER_AGENT } from "./constants"
 import type { LookAtArgs } from "./types"
-import { log } from "../../shared/logger"
+import { findByNameCaseInsensitive, log, promptWithModelSuggestionRetry } from "../../shared"
 
 interface LookAtArgsWithAlias extends LookAtArgs {
   path?: string
@@ -130,9 +130,34 @@ Original error: ${createResult.error}`
       const sessionID = createResult.data.id
       log(`[look_at] Created session: ${sessionID}`)
 
+      let agentModel: { providerID: string; modelID: string } | undefined
+      let agentVariant: string | undefined
+
+      try {
+        const agentsResult = await ctx.client.app?.agents?.()
+        type AgentInfo = {
+          name: string
+          mode?: "subagent" | "primary" | "all"
+          model?: { providerID: string; modelID: string }
+          variant?: string
+        }
+        const agents = ((agentsResult as { data?: AgentInfo[] })?.data ?? agentsResult) as AgentInfo[] | undefined
+        if (agents?.length) {
+          const matchedAgent = findByNameCaseInsensitive(agents, MULTIMODAL_LOOKER_AGENT)
+          if (matchedAgent?.model) {
+            agentModel = matchedAgent.model
+          }
+          if (matchedAgent?.variant) {
+            agentVariant = matchedAgent.variant
+          }
+        }
+      } catch (error) {
+        log("[look_at] Failed to resolve multimodal-looker model info", error)
+      }
+
       log(`[look_at] Sending prompt with file passthrough to session ${sessionID}`)
       try {
-        await ctx.client.session.prompt({
+        await promptWithModelSuggestionRetry(ctx.client, {
           path: { id: sessionID },
           body: {
             agent: MULTIMODAL_LOOKER_AGENT,
@@ -146,6 +171,8 @@ Original error: ${createResult.error}`
               { type: "text", text: prompt },
               { type: "file", mime: mimeType, url: pathToFileURL(args.file_path).href, filename },
             ],
+            ...(agentModel ? { model: { providerID: agentModel.providerID, modelID: agentModel.modelID } } : {}),
+            ...(agentVariant ? { variant: agentVariant } : {}),
           },
         })
       } catch (promptError) {