chore(llm): fix low-hanging lint warnings

packages/llm/src/llm.ts

@@ -12,7 +12,6 @@ import {
   ToolChoice,
   ToolDefinition,
   type ContentPart,
-  type Protocol,
   type ModelID as ModelIDType,
   type ProviderID as ProviderIDType,
   type ReasoningEffort,
@@ -50,7 +49,7 @@ export type ToolChoiceInput =
   | string
 
 export type ToolResultInput = Omit<ToolResultPart, "type" | "result"> & {
-  readonly result: ToolResultValue | unknown
+  readonly result: unknown
   readonly resultType?: ToolResultValue["type"]
 }
 
@@ -106,7 +105,7 @@ export const model = (input: ModelInput) => {
     ...rest,
     id: ModelID.make(input.id),
     provider: ProviderID.make(input.provider),
-    protocol: input.protocol as Protocol,
+    protocol: input.protocol,
     capabilities: modelCapabilities instanceof ModelCapabilities ? modelCapabilities : capabilities(modelCapabilities),
     limits: modelLimits instanceof ModelLimits ? modelLimits : limits(modelLimits),
   })
@@ -119,8 +118,14 @@ export const tool = (input: ToolDefinition | ConstructorParameters<typeof ToolDe
 
 export const toolCall = (input: Omit<ToolCallPart, "type">): ToolCallPart => ({ type: "tool-call", ...input })
 
-const toolResultValue = (value: ToolResultValue | unknown, type: ToolResultValue["type"] = "json"): ToolResultValue => {
-  if (typeof value === "object" && value !== null && "type" in value && "value" in value) return value as ToolResultValue
+const isRecord = (value: unknown): value is Record<string, unknown> =>
+  typeof value === "object" && value !== null && !Array.isArray(value)
+
+const isToolResultValue = (value: unknown): value is ToolResultValue =>
+  isRecord(value) && (value.type === "text" || value.type === "json" || value.type === "error") && "value" in value
+
+const toolResultValue = (value: unknown, type: ToolResultValue["type"] = "json"): ToolResultValue => {
+  if (isToolResultValue(value)) return value
   return { type, value }
 }
 

packages/llm/src/provider/anthropic-messages.ts

@@ -1,4 +1,4 @@
-import { Effect, Schema, Stream } from "effect"
+import { Effect, Schema } from "effect"
 import type { HttpClientResponse } from "effect/unstable/http"
 import { Adapter } from "../adapter"
 import { capabilities, model as llmModel, type ModelInput } from "../llm"
@@ -8,7 +8,6 @@ import {
   type FinishReason,
   type LLMEvent,
   type LLMRequest,
-  type TextPart,
   type ToolCallPart,
   type ToolDefinition,
   type ToolResultPart,

packages/llm/src/provider/gemini.ts

@@ -1,4 +1,4 @@
-import { Effect, Schema, Stream } from "effect"
+import { Effect, Schema } from "effect"
 import type { HttpClientResponse } from "effect/unstable/http"
 import { Adapter } from "../adapter"
 import { capabilities, model as llmModel, type ModelInput } from "../llm"

packages/llm/src/provider/openai-chat.ts

@@ -1,11 +1,10 @@
-import { Effect, Schema, Stream } from "effect"
+import { Effect, Schema } from "effect"
 import type { HttpClientResponse } from "effect/unstable/http"
 import { Adapter } from "../adapter"
 import { capabilities, model as llmModel, type ModelInput } from "../llm"
 import {
   Usage,
   type FinishReason,
-  type ContentPart,
   type LLMEvent,
   type LLMRequest,
   type TextPart,

packages/llm/src/provider/openai-responses.ts

@@ -1,4 +1,4 @@
-import { Effect, Schema, Stream } from "effect"
+import { Effect, Schema } from "effect"
 import type { HttpClientResponse } from "effect/unstable/http"
 import { Adapter } from "../adapter"
 import { capabilities, model as llmModel, type ModelInput } from "../llm"
@@ -322,7 +322,7 @@ const hostedToolResult = (item: OpenAIResponsesStreamItem) => {
 }
 
 const hostedToolEvents = (item: OpenAIResponsesStreamItem & { id: string }): ReadonlyArray<LLMEvent> => {
-  const name = HOSTED_TOOL_NAMES[item.type]!
+  const name = HOSTED_TOOL_NAMES[item.type]
   return [
     { type: "tool-call", id: item.id, name, input: hostedToolInput(item), providerExecuted: true },
     { type: "tool-result", id: item.id, name, result: hostedToolResult(item), providerExecuted: true },

packages/llm/src/provider/shared.ts

@@ -51,6 +51,15 @@ export const toolResultText = (part: ToolResultPart) => {
   return encodeJson(part.result.value)
 }
 
+const errorText = (error: unknown) => {
+  if (error instanceof Error) return error.message
+  if (typeof error === "string") return error
+  if (typeof error === "number" || typeof error === "boolean" || typeof error === "bigint") return String(error)
+  if (error === null) return "null"
+  if (error === undefined) return "undefined"
+  return "Unknown stream error"
+}
+
 const streamError = (adapter: string, message: string, cause: Cause.Cause<unknown>) => {
   const failed = cause.reasons.find(Cause.isFailReason)?.error
   if (failed instanceof ProviderChunkError) return failed
@@ -85,7 +94,7 @@ export const framed = <Frame, Chunk, State, Event>(input: {
   readonly onHalt?: (state: State) => ReadonlyArray<Event>
 }): Stream.Stream<Event, ProviderChunkError> => {
   const bytes = input.response.stream.pipe(
-    Stream.mapError((error) => chunkError(input.adapter, input.readError, String(error))),
+    Stream.mapError((error) => chunkError(input.adapter, input.readError, errorText(error))),
   )
   return input.framing(bytes).pipe(
     Stream.mapEffect(input.decodeChunk),

packages/llm/src/tool-runtime.ts

@@ -43,6 +43,21 @@ export interface RunOptions<T extends Tools> {
   readonly stopWhen?: (state: RuntimeState) => boolean
 }
 
+const requestInput = (request: LLMRequest): ConstructorParameters<typeof LLMRequest>[0] => ({
+  id: request.id,
+  model: request.model,
+  system: request.system,
+  messages: request.messages,
+  tools: request.tools,
+  toolChoice: request.toolChoice,
+  generation: request.generation,
+  reasoning: request.reasoning,
+  cache: request.cache,
+  responseFormat: request.responseFormat,
+  metadata: request.metadata,
+  native: request.native,
+})
+
 /**
  * Run a model with a typed tool record. The runtime streams the model, on
  * each `tool-call` event decodes the input against the tool's `parameters`
@@ -64,7 +79,7 @@ export const run = <T extends Tools>(
   const tools = options.tools as Tools
   const runtimeTools = toDefinitions(tools)
   const initialRequest = new LLMRequest({
-    ...options.request,
+    ...requestInput(options.request),
     tools: [
       ...options.request.tools.filter((tool) => !runtimeTools.some((runtimeTool) => runtimeTool.name === tool.name)),
       ...runtimeTools,
@@ -92,7 +107,7 @@ export const run = <T extends Tools>(
               { concurrency },
             )
             const followUp = new LLMRequest({
-              ...request,
+              ...requestInput(request),
               messages: [
                 ...request.messages,
                 LLM.assistant(state.assistantContent),