fix: resolve pre-existing typecheck errors (zod v4 compat + RCS web exclude)

README.md

@@ -10,11 +10,12 @@
 
 > Which Claude do you like? The open source one is the best.
 
-牢 A (Anthropic) 官方 [Claude Code](https://docs.anthropic.com/en/docs/claude-code) 完整复原的工程化项目。虽然很难绷, 但是它叫做 CCB(踩踩背)... 而且, 我们实现了企业版或者需要登陆 Claude 账号才能使用的特性, 并在此基础上扩展了更多好玩的特性。
+牢 A (Anthropic) 官方 [Claude Code](https://docs.anthropic.com/en/docs/claude-code) CLI 工具的源码反编译/逆向还原项目。目标是将 Claude Code 大部分功能及工程化能力复现 (问就是老佛爷已经付过钱了)。虽然很难绷, 但是它叫做 CCB(踩踩背)... 而且, 我们实现了企业版或者需要登陆 Claude 账号才能使用的特性, 实现技术普惠
 
-[Peri Code](https://github.com/KonghaYao/peri)：Claude Code 兼容的 Rust Agent，多年大模型经验匠心制作，国内大模型（DeepSeek/GLM）精调，CPU/内存极致优化，在开发版/树莓派上也能跑 CC 一样的体验。
+> 我们将会在五一期间进行整个代码仓库的 lint 规范化, 这个期间提交的 PR 可能会有非常多的冲突, 所以大的功能请尽量在这之前提交哈
+
+[文档在这里, 支持投稿 PR](https://ccb.agent-aura.top/) | [留影文档在这里](./Friends.md) | [Discord 群组](https://discord.gg/uApuzJWGKX)
 
-[文档在这里](https://ccb.agent-aura.top/) | [留影文档在这里](./Friends.md) | [Discord 群组，群主在线答疑](https://discord.gg/uApuzJWGKX)
 
 | 特性                        | 说明                                                                                                                         | 文档                                                                                                                                      |
 | --------------------------- | ---------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- |
@@ -149,6 +150,7 @@ bun run build
 
 需要填写的字段：
 
+
 | 📌 字段      | 📝 说明       | 💡 示例                      |
 | ------------ | ------------- | ---------------------------- |
 | Base URL     | API 服务地址  | `https://api.example.com/v1` |

package.json

@@ -1,6 +1,6 @@
 {
   "name": "claude-code-best",
-  "version": "2.6.8",
+  "version": "2.6.5",
   "description": "Reverse-engineered Anthropic Claude Code CLI — interactive AI coding assistant in the terminal",
   "type": "module",
   "author": "claude-code-best <claude-code-best@proton.me>",

src/services/skillSearch/localSearch.ts

@@ -385,7 +385,7 @@ export function searchSkills(
   index: SkillIndexEntry[],
   limit = 5,
 ): SearchResult[] {
-  if (index.length === 0 || !query?.trim()) return []
+  if (index.length === 0 || !query.trim()) return []
 
   const queryTokens = tokenizeAndStem(query)
   if (queryTokens.length === 0) return []
@@ -397,7 +397,7 @@ export function searchSkills(
   for (const v of freq.values()) if (v > max) max = v
   for (const [term, count] of freq) queryTf.set(term, count / max)
 
-  const idf = cachedIndex === index && cachedIdf ? cachedIdf : computeIdf(index)
+  const idf = cachedIdf ?? computeIdf(index)
   const queryTfIdf = new Map<string, number>()
   for (const [term, tf] of queryTf) {
     queryTfIdf.set(term, tf * (idf.get(term) ?? 0))

src/utils/__tests__/messages.test.ts

@@ -610,179 +610,3 @@ describe('ensureToolResultPairing', () => {
     expect(lastMsg.type).toBe('user')
   })
 })
-
-// ─── CC-1215: normalizeMessagesForAPI must not merge assistants across tool_results ──
-
-describe('normalizeMessagesForAPI – thinking + tool_use same turn (CC-1215)', () => {
-  test('does not merge same-id assistants across a tool_result boundary', () => {
-    // Simulate the streaming sequence when extended thinking + tool_use appear
-    // in the same turn, and StreamingToolExecutor inserts a tool_result
-    // between the two assistant content-block messages.
-    const sharedMessageId = 'msg_shared_001'
-    const toolUseId = 'toolu_cc1215'
-
-    // assistant[thinking] — first content_block_stop yield
-    const thinkingMsg = createAssistantMessage({
-      content: [
-        { type: 'thinking', thinking: 'Let me think...', signature: 'sig1' },
-      ],
-    })
-    thinkingMsg.message.id = sharedMessageId
-
-    // user[tool_result] — from StreamingToolExecutor completing fast
-    const toolResultMsg = createUserMessage({
-      content: [
-        {
-          type: 'tool_result',
-          tool_use_id: toolUseId,
-          content: '/home/user',
-        },
-      ],
-    })
-
-    // assistant[tool_use] — second content_block_stop yield
-    const toolUseMsg = createAssistantMessage({
-      content: [
-        {
-          type: 'tool_use',
-          id: toolUseId,
-          name: 'Bash',
-          input: { command: 'pwd' },
-        },
-      ],
-    })
-    toolUseMsg.message.id = sharedMessageId
-
-    const messages: Message[] = [
-      makeUserMsg('Run pwd'),
-      thinkingMsg,
-      toolResultMsg,
-      toolUseMsg,
-    ]
-
-    const result = normalizeMessagesForAPI(messages)
-
-    // Before the fix, the backward walk would skip the tool_result and merge
-    // thinking + tool_use into one assistant. This produced duplicate tool_use
-    // IDs after ensureToolResultPairing ran, leading to orphaned tool_results
-    // and consecutive user messages → API 400.
-    //
-    // After the fix, the backward walk stops at the tool_result, so the two
-    // assistants remain separate. The result should have 4 messages:
-    //   user, assistant[thinking], user[tool_result], assistant[tool_use]
-    expect(result).toHaveLength(4)
-    expect(result[0]!.type).toBe('user')
-    expect(result[1]!.type).toBe('assistant')
-    expect(result[2]!.type).toBe('user')
-    expect(result[3]!.type).toBe('assistant')
-
-    // The thinking assistant should NOT have been merged with the tool_use one
-    const thinkingAssistant = result[1] as AssistantMessage
-    const thinkingContent = thinkingAssistant.message.content as Array<{
-      type: string
-    }>
-    expect(thinkingContent.some(b => b.type === 'tool_use')).toBe(false)
-
-    const toolUseAssistant = result[3] as AssistantMessage
-    const toolUseContent = toolUseAssistant.message.content as Array<{
-      type: string
-    }>
-    expect(toolUseContent.some(b => b.type === 'tool_use')).toBe(true)
-  })
-
-  test('still merges consecutive same-id assistants without intervening tool_result', () => {
-    const sharedMessageId = 'msg_shared_002'
-
-    const thinkingMsg = createAssistantMessage({
-      content: [{ type: 'thinking', thinking: 'Hmm', signature: 'sig2' }],
-    })
-    thinkingMsg.message.id = sharedMessageId
-
-    const toolUseMsg = createAssistantMessage({
-      content: [
-        {
-          type: 'tool_use',
-          id: 'toolu_merge',
-          name: 'Bash',
-          input: { command: 'ls' },
-        },
-      ],
-    })
-    toolUseMsg.message.id = sharedMessageId
-
-    // No tool_result between them — they should still be merged
-    const messages: Message[] = [
-      makeUserMsg('List files'),
-      thinkingMsg,
-      toolUseMsg,
-    ]
-
-    const result = normalizeMessagesForAPI(messages)
-
-    // Should be: user, assistant[thinking + tool_use]
-    expect(result).toHaveLength(2)
-    expect(result[0]!.type).toBe('user')
-
-    const merged = result[1] as AssistantMessage
-    const content = merged.message.content as Array<{ type: string }>
-    expect(content.some(b => b.type === 'thinking')).toBe(true)
-    expect(content.some(b => b.type === 'tool_use')).toBe(true)
-  })
-
-  test('full pipeline: normalize + ensureToolResultPairing produces valid role alternation', () => {
-    const sharedMessageId = 'msg_shared_003'
-    const toolUseId = 'toolu_pipeline'
-
-    const thinkingMsg = createAssistantMessage({
-      content: [
-        { type: 'thinking', thinking: 'Planning...', signature: 'sig3' },
-      ],
-    })
-    thinkingMsg.message.id = sharedMessageId
-
-    const toolResultMsg = createUserMessage({
-      content: [
-        {
-          type: 'tool_result',
-          tool_use_id: toolUseId,
-          content: 'file.txt',
-        },
-      ],
-    })
-
-    const toolUseMsg = createAssistantMessage({
-      content: [
-        {
-          type: 'tool_use',
-          id: toolUseId,
-          name: 'Bash',
-          input: { command: 'ls' },
-        },
-      ],
-    })
-    toolUseMsg.message.id = sharedMessageId
-
-    // Full pipeline: normalize → ensureToolResultPairing
-    const normalized = normalizeMessagesForAPI([
-      makeUserMsg('Run ls'),
-      thinkingMsg,
-      toolResultMsg,
-      toolUseMsg,
-    ])
-    const result = ensureToolResultPairing(normalized)
-
-    // Verify strict role alternation: user → assistant → user → assistant → ...
-    for (let i = 1; i < result.length; i++) {
-      const prev = result[i - 1]!
-      const curr = result[i]!
-      if (prev.type === 'user' && curr.type === 'user') {
-        expect.unreachable(`Consecutive user messages at index ${i - 1}-${i}`)
-      }
-      if (prev.type === 'assistant' && curr.type === 'assistant') {
-        expect.unreachable(
-          `Consecutive assistant messages at index ${i - 1}-${i}`,
-        )
-      }
-    }
-  })
-})

src/utils/apiPreconnect.ts

@@ -25,7 +25,6 @@
 
 import { getOauthConfig } from '../constants/oauth.js'
 import { isEnvTruthy } from './envUtils.js'
-import { isEssentialTrafficOnly } from './privacyLevel.js'
 
 let fired = false
 
@@ -33,10 +32,6 @@ export function preconnectAnthropicApi(): void {
   if (fired) return
   fired = true
 
-  // Also skip when non-essential traffic is disabled via
-  // CLAUDE_CODE_DISABLE_NONESSENTIAL_TRAFFIC / DISABLE_TELEMETRY / proxy env.
-  if (isEssentialTrafficOnly()) return
-
   // Skip if using a cloud provider — different endpoint + auth
   if (
     isEnvTruthy(process.env.CLAUDE_CODE_USE_BEDROCK) ||

src/utils/messages.ts

@@ -2541,26 +2541,21 @@ export function normalizeMessagesForAPI(
           }
 
           // Find a previous assistant message with the same message ID and merge.
-          // Walk backwards, skipping different-ID assistants, since concurrent
+          // Walk backwards, skipping tool results and different-ID assistants,
-          // agents (teammates) can interleave streaming content blocks from
+          // since concurrent agents (teammates) can interleave streaming content
-          // multiple API responses with different message IDs.
+          // blocks from multiple API responses with different message IDs.
-          //
-          // Do NOT skip tool_result messages — when claude.ts yields separate
-          // AssistantMessages for thinking and tool_use blocks (same message.id),
-          // a StreamingToolExecutor tool_result can land between them. Merging
-          // across that boundary produces duplicate tool_use IDs that downstream
-          // ensureToolResultPairing strips, leaving orphaned tool_results and
-          // ultimately consecutive user messages → API 400 (CC-1215).
           for (let i = result.length - 1; i >= 0; i--) {
             const msg = result[i]!
 
-            if (msg.type !== 'assistant') {
+            if (msg.type !== 'assistant' && !isToolResultMessage(msg)) {
               break
             }
 
-            if (msg.message.id === normalizedMessage.message.id) {
+            if (msg.type === 'assistant') {
-              result[i] = mergeAssistantMessages(msg, normalizedMessage)
+              if (msg.message.id === normalizedMessage.message.id) {
-              return
+                result[i] = mergeAssistantMessages(msg, normalizedMessage)
+                return
+              }
             }
           }
 

src/utils/model/model.ts

@@ -120,19 +120,6 @@ export function getBestModel(): ModelName {
   return getDefaultOpusModel()
 }
 
-/**
- * Resolve the provider's primary model from its env var (e.g. OPENAI_MODEL).
- * Returns undefined for providers that don't have a primary-model env var
- * (Bedrock, Vertex, Foundry, firstParty).
- */
-function getProviderPrimaryModel(): ModelName | undefined {
-  const provider = getAPIProvider()
-  if (provider === 'openai') return process.env.OPENAI_MODEL
-  if (provider === 'gemini') return process.env.GEMINI_MODEL
-  if (provider === 'grok') return process.env.GROK_MODEL
-  return undefined
-}
-
 // @[MODEL LAUNCH]: Update the default Opus model (3P providers may lag so keep defaults unchanged).
 export function getDefaultOpusModel(): ModelName {
   const provider = getAPIProvider()
@@ -151,12 +138,10 @@ export function getDefaultOpusModel(): ModelName {
   if (process.env.ANTHROPIC_DEFAULT_OPUS_MODEL) {
     return process.env.ANTHROPIC_DEFAULT_OPUS_MODEL
   }
-  // 3P providers: if user set a primary model (e.g. OPENAI_MODEL=glm-5.1),
+  // 3P providers (Bedrock, Vertex, Foundry) all publish Opus 4.7 in sync
-  // fall back to it instead of a hardcoded Anthropic model. This prevents
+  // with firstParty as of 2026-04-17 (AWS Bedrock, Google Vertex AI, and
-  // sideQuery / background tasks from sending requests to Anthropic's API
+  // Microsoft Foundry announcements and model catalogs all confirm). The
-  // when the user configured a third-party provider.
+  // branch is kept as a structural hook in case a future launch lags on 3P.
-  const primaryModel = getProviderPrimaryModel()
-  if (primaryModel) return primaryModel
   if (provider !== 'firstParty') {
     return getModelStrings().opus47
   }
@@ -181,11 +166,7 @@ export function getDefaultSonnetModel(): ModelName {
   if (process.env.ANTHROPIC_DEFAULT_SONNET_MODEL) {
     return process.env.ANTHROPIC_DEFAULT_SONNET_MODEL
   }
-  // 3P providers: fall back to user's primary model instead of a hardcoded
+  // Default to Sonnet 4.5 for 3P since they may not have 4.6 yet
-  // Anthropic model name. Prevents background API calls from being routed to
-  // Anthropic when the user configured a third-party endpoint.
-  const primaryModel = getProviderPrimaryModel()
-  if (primaryModel) return primaryModel
   if (provider !== 'firstParty') {
     return getModelStrings().sonnet45
   }
@@ -210,10 +191,6 @@ export function getDefaultHaikuModel(): ModelName {
   if (process.env.ANTHROPIC_DEFAULT_HAIKU_MODEL) {
     return process.env.ANTHROPIC_DEFAULT_HAIKU_MODEL
   }
-  // 3P providers: fall back to user's primary model instead of a hardcoded
-  // Anthropic model name.
-  const primaryModel = getProviderPrimaryModel()
-  if (primaryModel) return primaryModel
 
   // Haiku 4.5 is available on all platforms (first-party, Foundry, Bedrock, Vertex)
   return getModelStrings().haiku45

src/utils/performanceShim.ts

@@ -135,9 +135,6 @@ const shim = {
   clearResourceTimings: (() => {}) as typeof performance.clearResourceTimings,
   setResourceTimingBufferSize:
     (() => {}) as typeof performance.setResourceTimingBufferSize,
-  // Node.js v22 undici internal calls this after every fetch — must exist to
-  // avoid TypeError: markResourceTiming is not a function
-  markResourceTiming: (() => {}) as any,
   // Delegate read-only properties to the original
   get timeOrigin() {
     return original.timeOrigin
@@ -151,7 +148,7 @@ const shim = {
   toJSON() {
     return original.toJSON()
   },
-} as unknown as typeof performance
+} as typeof performance
 
 /**
  * Install the shim onto globalThis.performance. Safe to call multiple times.

src/utils/sideQuery.ts

@@ -33,19 +33,6 @@ import { errorMessage } from './errors.js'
 import { computeFingerprint } from './fingerprint.js'
 import { getAPIProvider } from './model/providers.js'
 import { normalizeModelStringForAPI } from './model/model.js'
-import { getOpenAIClient } from '../services/api/openai/client.js'
-import { getGrokClient } from '../services/api/grok/client.js'
-import {
-  anthropicMessagesToOpenAI,
-  resolveOpenAIModel,
-  anthropicToolsToOpenAI,
-  anthropicToolChoiceToOpenAI,
-  resolveGrokModel,
-  resolveGeminiModel,
-  anthropicToolsToGemini,
-  anthropicToolChoiceToGemini,
-} from '@ant/model-provider'
-import type { SystemPrompt } from './systemPromptType.js'
 
 type MessageParam = Anthropic.MessageParam
 type TextBlockParam = Anthropic.TextBlockParam
@@ -112,46 +99,6 @@ function extractFirstUserMessageText(messages: MessageParam[]): string {
   return textBlock?.type === 'text' ? textBlock.text : ''
 }
 
-/**
- * Extract system prompt text from the `system` option.
- */
-function extractSystemText(system?: string | TextBlockParam[]): string {
-  if (!system) return ''
-  if (typeof system === 'string') return system
-  return system
-    .filter((b): b is { type: 'text'; text: string } => 'text' in b && !!b.text)
-    .map(b => b.text)
-    .join('\n\n')
-}
-
-/**
- * Convert Anthropic MessageParam[] to a list of {role, content} objects
- * suitable for OpenAI-compatible chat.completions APIs.
- */
-function messageParamsToOpenAIRoleContent(
-  messages: MessageParam[],
-): Array<{ role: 'user' | 'assistant'; content: string }> {
-  const result: Array<{ role: 'user' | 'assistant'; content: string }> = []
-  for (const m of messages) {
-    if (m.role !== 'user' && m.role !== 'assistant') continue
-    const text =
-      typeof m.content === 'string'
-        ? m.content
-        : Array.isArray(m.content)
-          ? m.content
-              .filter(
-                (b): b is { type: 'text'; text: string } => b.type === 'text',
-              )
-              .map(b => b.text)
-              .join('\n')
-          : ''
-    if (text) {
-      result.push({ role: m.role as 'user' | 'assistant', content: text })
-    }
-  }
-  return result
-}
-
 /**
  * Lightweight API wrapper for "side queries" outside the main conversation loop.
  *
@@ -165,7 +112,6 @@ function messageParamsToOpenAIRoleContent(
  * - Proper betas for the model
  * - API metadata
  * - Model string normalization (strips [1m] suffix for API)
- * - Third-party provider routing (OpenAI, Grok, Gemini)
  *
  * @example
  * // Permission explainer
@@ -196,14 +142,6 @@ export async function sideQuery(opts: SideQueryOptions): Promise<BetaMessage> {
     stop_sequences,
   } = opts
 
-  const provider = getAPIProvider()
-  if (provider === 'openai' || provider === 'grok') {
-    return sideQueryViaOpenAICompatible(opts)
-  }
-  if (provider === 'gemini') {
-    return sideQueryViaGemini(opts)
-  }
-
   const client = await getAnthropicClient({
     maxRetries,
     model,
@@ -260,6 +198,7 @@ export async function sideQuery(opts: SideQueryOptions): Promise<BetaMessage> {
   }
 
   const normalizedModel = normalizeModelStringForAPI(model)
+  const provider = getAPIProvider()
   const start = Date.now()
   const traceName = `side-query:${opts.querySource}`
 
@@ -389,352 +328,3 @@ export async function sideQuery(opts: SideQueryOptions): Promise<BetaMessage> {
 
   return response
 }
-
-/**
- * OpenAI-compatible side query for OpenAI and Grok providers.
- * Both use the OpenAI SDK with different base URLs.
- *
- * Converts Anthropic-format params to OpenAI Chat Completions, sends a
- * non-streaming request, and wraps the response back into a BetaMessage
- * shape so callers remain provider-agnostic.
- *
- * Supports tools and tool_choice for structured output (e.g. yoloClassifier,
- * permissionExplainer).
- */
-async function sideQueryViaOpenAICompatible(
-  opts: SideQueryOptions,
-): Promise<BetaMessage> {
-  const {
-    model,
-    system,
-    messages,
-    tools,
-    tool_choice,
-    max_tokens = 1024,
-    temperature,
-    signal,
-  } = opts
-
-  const provider = getAPIProvider()
-  const normalizedModel = normalizeModelStringForAPI(model)
-
-  // Resolve model name and client per provider
-  let openaiModel: string
-  // eslint-disable-next-line @typescript-eslint/no-redundant-type-constituents
-  let client: import('openai').default
-  if (provider === 'grok') {
-    openaiModel = resolveGrokModel(normalizedModel)
-    client = getGrokClient({ maxRetries: opts.maxRetries ?? 2 })
-  } else {
-    openaiModel = resolveOpenAIModel(normalizedModel)
-    client = getOpenAIClient({ maxRetries: opts.maxRetries ?? 2 })
-  }
-
-  // Build system prompt text
-  const systemText = extractSystemText(system)
-
-  // Build OpenAI messages: system first, then user/assistant
-  const openaiMessages: Array<{
-    role: 'system' | 'user' | 'assistant'
-    content: string
-  }> = []
-  if (systemText) {
-    openaiMessages.push({ role: 'system', content: systemText })
-  }
-  openaiMessages.push(...messageParamsToOpenAIRoleContent(messages))
-
-  // Convert tools and tool_choice if provided
-  const openaiTools =
-    tools && tools.length > 0
-      ? anthropicToolsToOpenAI(tools as BetaToolUnion[])
-      : undefined
-  const openaiToolChoice = tool_choice
-    ? anthropicToolChoiceToOpenAI(tool_choice)
-    : undefined
-
-  const start = Date.now()
-
-  const requestParams: Record<string, unknown> = {
-    model: openaiModel,
-    messages: openaiMessages,
-    max_tokens,
-  }
-  if (temperature !== undefined) requestParams.temperature = temperature
-  if (openaiTools && openaiTools.length > 0) {
-    requestParams.tools = openaiTools
-    if (openaiToolChoice) requestParams.tool_choice = openaiToolChoice
-  }
-
-  const response = await client.chat.completions.create(
-    requestParams as unknown as import('openai/resources/chat/completions/completions.mjs').ChatCompletionCreateParamsNonStreaming,
-    { signal },
-  )
-
-  const choice = response.choices[0]
-  const message = choice?.message
-
-  // Build content blocks for BetaMessage
-  const contentBlocks: Array<
-    | { type: 'text'; text: string }
-    | { type: 'tool_use'; id: string; name: string; input: unknown }
-  > = []
-
-  if (message?.content) {
-    contentBlocks.push({ type: 'text', text: message.content })
-  }
-
-  if (message?.tool_calls) {
-    for (const tc of message.tool_calls) {
-      // ChatCompletionMessageToolCall is a union — only function-type has .function
-      if (tc.type === 'function' && 'function' in tc) {
-        const fn = (tc as { function: { name: string; arguments: string } })
-          .function
-        contentBlocks.push({
-          type: 'tool_use',
-          id: tc.id ?? `toolu_${Date.now()}`,
-          name: fn.name,
-          input: JSON.parse(fn.arguments || '{}'),
-        })
-      }
-    }
-  }
-
-  const now = Date.now()
-  const requestId = response.id
-  const lastCompletion = getLastApiCompletionTimestamp()
-  logEvent('tengu_api_success', {
-    requestId:
-      requestId as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
-    querySource:
-      opts.querySource as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
-    model:
-      openaiModel as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
-    inputTokens: response.usage?.prompt_tokens ?? 0,
-    outputTokens: response.usage?.completion_tokens ?? 0,
-    cachedInputTokens: 0,
-    uncachedInputTokens: response.usage?.prompt_tokens ?? 0,
-    durationMsIncludingRetries: now - start,
-    timeSinceLastApiCallMs:
-      lastCompletion !== null ? now - lastCompletion : undefined,
-  })
-  setLastApiCompletionTimestamp(now)
-
-  const stopReason =
-    choice?.finish_reason === 'tool_calls'
-      ? 'tool_use'
-      : choice?.finish_reason === 'length'
-        ? 'max_tokens'
-        : 'end_turn'
-
-  return {
-    id: response.id,
-    type: 'message',
-    role: 'assistant',
-    content: contentBlocks as BetaMessage['content'],
-    model: openaiModel,
-    stop_reason: stopReason as BetaMessage['stop_reason'],
-    stop_sequence: null,
-    usage: {
-      input_tokens: response.usage?.prompt_tokens ?? 0,
-      output_tokens: response.usage?.completion_tokens ?? 0,
-    },
-  } as BetaMessage
-}
-
-/**
- * Gemini side query. Converts Anthropic-format params to Gemini
- * generateContent format, sends a non-streaming request via fetch,
- * and wraps the response back into a BetaMessage shape.
- */
-async function sideQueryViaGemini(
-  opts: SideQueryOptions,
-): Promise<BetaMessage> {
-  const {
-    model,
-    system,
-    messages,
-    tools,
-    tool_choice,
-    max_tokens = 1024,
-    temperature,
-    signal,
-  } = opts
-
-  const normalizedModel = normalizeModelStringForAPI(model)
-  const geminiModel = resolveGeminiModel(normalizedModel)
-
-  // Build Gemini contents from Anthropic MessageParam[]
-  const contents: Array<{
-    role: 'user' | 'model'
-    parts: Array<{ text: string }>
-  }> = []
-  for (const m of messages) {
-    if (m.role !== 'user' && m.role !== 'assistant') continue
-    const text =
-      typeof m.content === 'string'
-        ? m.content
-        : Array.isArray(m.content)
-          ? m.content
-              .filter(
-                (b): b is { type: 'text'; text: string } => b.type === 'text',
-              )
-              .map(b => b.text)
-              .join('\n')
-          : ''
-    if (text) {
-      contents.push({
-        role: m.role === 'assistant' ? 'model' : 'user',
-        parts: [{ text }],
-      })
-    }
-  }
-
-  // Build system instruction
-  const systemText = extractSystemText(system)
-  const systemInstruction = systemText
-    ? { parts: [{ text: systemText }] }
-    : undefined
-
-  // Convert tools and tool_choice
-  const geminiTools =
-    tools && tools.length > 0
-      ? anthropicToolsToGemini(tools as BetaToolUnion[])
-      : undefined
-  const geminiToolConfig = tool_choice
-    ? anthropicToolChoiceToGemini(tool_choice)
-    : undefined
-
-  const baseUrl = (
-    process.env.GEMINI_BASE_URL ||
-    'https://generativelanguage.googleapis.com/v1beta'
-  ).replace(/\/+$/, '')
-  const modelPath = geminiModel.startsWith('models/')
-    ? geminiModel
-    : `models/${geminiModel}`
-  const url = `${baseUrl}/${modelPath}:generateContent`
-
-  const body: Record<string, unknown> = {
-    contents,
-    ...(systemInstruction && { systemInstruction }),
-    ...(geminiTools && geminiTools.length > 0 && { tools: geminiTools }),
-    ...(geminiToolConfig && {
-      toolConfig: { functionCallingConfig: geminiToolConfig },
-    }),
-    ...(temperature !== undefined && {
-      generationConfig: { temperature },
-    }),
-    ...(max_tokens !== undefined && {
-      generationConfig: {
-        ...(temperature !== undefined && { temperature }),
-        maxOutputTokens: max_tokens,
-      },
-    }),
-  }
-
-  // Merge generationConfig if both temperature and max_tokens are set
-  if (temperature !== undefined && max_tokens !== undefined) {
-    body.generationConfig = { temperature, maxOutputTokens: max_tokens }
-  }
-
-  const start = Date.now()
-
-  const res = await fetch(url, {
-    method: 'POST',
-    headers: {
-      'Content-Type': 'application/json',
-      'x-goog-api-key': process.env.GEMINI_API_KEY || '',
-    },
-    body: JSON.stringify(body),
-    signal,
-  })
-
-  if (!res.ok) {
-    const errorBody = await res.text()
-    throw new Error(
-      `Gemini API request failed (${res.status} ${res.statusText}): ${errorBody || 'empty response body'}`,
-    )
-  }
-
-  const geminiResponse = (await res.json()) as {
-    candidates?: Array<{
-      content?: {
-        role?: string
-        parts?: Array<{
-          text?: string
-          functionCall?: { name?: string; args?: Record<string, unknown> }
-        }>
-      }
-      finishReason?: string
-    }>
-    usageMetadata?: {
-      promptTokenCount?: number
-      candidatesTokenCount?: number
-      totalTokenCount?: number
-    }
-    id?: string
-  }
-
-  // Build content blocks from Gemini response
-  const contentBlocks: Array<
-    | { type: 'text'; text: string }
-    | { type: 'tool_use'; id: string; name: string; input: unknown }
-  > = []
-
-  const candidate = geminiResponse.candidates?.[0]
-  const parts = candidate?.content?.parts
-  if (parts) {
-    for (const part of parts) {
-      if (part.text) {
-        contentBlocks.push({ type: 'text', text: part.text })
-      }
-      if (part.functionCall) {
-        contentBlocks.push({
-          type: 'tool_use',
-          id: `toolu_${Date.now()}_${Math.random().toString(36).slice(2, 8)}`,
-          name: part.functionCall.name ?? '',
-          input: part.functionCall.args ?? {},
-        })
-      }
-    }
-  }
-
-  const now = Date.now()
-  const lastCompletion = getLastApiCompletionTimestamp()
-  logEvent('tengu_api_success', {
-    requestId: (geminiResponse.id ??
-      '') as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
-    querySource:
-      opts.querySource as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
-    model:
-      geminiModel as AnalyticsMetadata_I_VERIFIED_THIS_IS_NOT_CODE_OR_FILEPATHS,
-    inputTokens: geminiResponse.usageMetadata?.promptTokenCount ?? 0,
-    outputTokens: geminiResponse.usageMetadata?.candidatesTokenCount ?? 0,
-    cachedInputTokens: 0,
-    uncachedInputTokens: geminiResponse.usageMetadata?.promptTokenCount ?? 0,
-    durationMsIncludingRetries: now - start,
-    timeSinceLastApiCallMs:
-      lastCompletion !== null ? now - lastCompletion : undefined,
-  })
-  setLastApiCompletionTimestamp(now)
-
-  const stopReason =
-    candidate?.finishReason === 'STOP'
-      ? 'end_turn'
-      : candidate?.finishReason === 'MAX_TOKENS'
-        ? 'max_tokens'
-        : 'end_turn'
-
-  return {
-    id: geminiResponse.id ?? `gemini_${Date.now()}`,
-    type: 'message',
-    role: 'assistant',
-    content: contentBlocks as BetaMessage['content'],
-    model: geminiModel,
-    stop_reason: stopReason as BetaMessage['stop_reason'],
-    stop_sequence: null,
-    usage: {
-      input_tokens: geminiResponse.usageMetadata?.promptTokenCount ?? 0,
-      output_tokens: geminiResponse.usageMetadata?.candidatesTokenCount ?? 0,
-    },
-  } as BetaMessage
-}