fix(#2792): automated Cursor CLI fix

application/i18n/locales/en/ai.ts

@@ -58,8 +58,8 @@ export const enAiMessages: Messages = {
   'ai.providers.defaultModel.placeholder': 'e.g. gpt-4o, claude-sonnet-4-20250514',
   'ai.providers.contextWindow': 'Context window',
   'ai.providers.contextWindow.placeholder': 'e.g. 128000',
-  'ai.providers.contextWindow.help': 'Leave blank to use the model list value when available, otherwise Netcatty uses a safe default.',
-  'ai.providers.contextWindow.error': 'Enter a positive whole number, or leave it blank.',
+  'ai.providers.contextWindow.help': 'Leave blank to use the model list value when available, otherwise Netcatty uses a safe default. Minimum is 1024 tokens.',
+  'ai.providers.contextWindow.error': 'Enter a whole number of at least 1024, or leave it blank.',
   'ai.providers.refreshModels': 'Refresh models',
   'ai.providers.searchModel': 'Search or type model ID...',
   'ai.providers.filterModels': 'Filter models...',

application/i18n/locales/ru/ai.ts

@@ -39,8 +39,8 @@ export const ruAiMessages: Messages = {
   'ai.providers.defaultModel.placeholder': 'например, gpt-4o, claude-sonnet-4-20250514',
   'ai.providers.contextWindow': 'Контекстное окно',
   'ai.providers.contextWindow.placeholder': 'например, 128000',
-  'ai.providers.contextWindow.help': 'Оставьте пустым, чтобы использовать значение из списка моделей, если оно доступно; иначе Netcatty применит безопасное значение по умолчанию.',
-  'ai.providers.contextWindow.error': 'Введите положительное целое число или оставьте поле пустым.',
+  'ai.providers.contextWindow.help': 'Оставьте пустым, чтобы использовать значение из списка моделей, если оно доступно; иначе Netcatty применит безопасное значение по умолчанию. Минимум — 1024 токена.',
+  'ai.providers.contextWindow.error': 'Введите целое число не меньше 1024 или оставьте поле пустым.',
   'ai.providers.refreshModels': 'Обновить модели',
   'ai.providers.searchModel': 'Искать или ввести ID модели...',
   'ai.providers.filterModels': 'Фильтровать модели...',

application/i18n/locales/zh-CN/ai.ts

@@ -58,8 +58,8 @@ export const zhCNAiMessages: Messages = {
   'ai.providers.defaultModel.placeholder': '例如 gpt-4o, claude-sonnet-4-20250514',
   'ai.providers.contextWindow': '上下文窗口',
   'ai.providers.contextWindow.placeholder': '例如 128000',
-  'ai.providers.contextWindow.help': '留空时优先使用模型列表返回的值；如果没有，Netcatty 会使用安全默认值。',
-  'ai.providers.contextWindow.error': '请输入正整数，或留空。',
+  'ai.providers.contextWindow.help': '留空时优先使用模型列表返回的值；如果没有，Netcatty 会使用安全默认值。最小值是 1024 tokens。',
+  'ai.providers.contextWindow.error': '请输入不小于 1024 的正整数，或留空。',
   'ai.providers.refreshModels': '刷新模型列表',
   'ai.providers.searchModel': '搜索或输入模型 ID...',
   'ai.providers.filterModels': '筛选模型...',

application/i18n/locales/zh-TW/ai.ts

@@ -58,8 +58,8 @@ export const zhTWAiMessages: Messages = {
   'ai.providers.defaultModel.placeholder': '例如 gpt-4o, claude-sonnet-4-20250514',
   'ai.providers.contextWindow': '上下文視窗',
   'ai.providers.contextWindow.placeholder': '例如 128000',
-  'ai.providers.contextWindow.help': '留空時優先使用模型列表傳回的值；如果沒有，Netcatty 會使用安全預設值。',
-  'ai.providers.contextWindow.error': '請輸入正整數，或留空。',
+  'ai.providers.contextWindow.help': '留空時優先使用模型列表傳回的值；如果沒有，Netcatty 會使用安全預設值。最小值是 1024 tokens。',
+  'ai.providers.contextWindow.error': '請輸入不小於 1024 的正整數，或留空。',
   'ai.providers.refreshModels': '重新整理模型列表',
   'ai.providers.searchModel': '搜尋或輸入模型 ID...',
   'ai.providers.filterModels': '篩選模型...',

components/settings/tabs/ai/ProviderConfigForm.tsx

@@ -2,7 +2,7 @@ import React, { useCallback, useEffect, useMemo, useRef, useState } from "react"
 import { Check, ChevronDown, ChevronRight, Eye, EyeOff, Pencil, Upload, RotateCcw, X } from "lucide-react";
 import type { ProviderConfig, ProviderAdvancedParams, ProviderStyle } from "../../../../infrastructure/ai/types";
 import { PROVIDER_PRESETS, resolveProviderStyle } from "../../../../infrastructure/ai/types";
-import { sanitizeContextWindow } from "../../../../infrastructure/ai/contextCompaction";
+import { sanitizeContextWindow, MIN_CONTEXT_WINDOW_TOKENS } from "../../../../infrastructure/ai/contextCompaction";
 import { encryptField, decryptField } from "../../../../infrastructure/persistence/secureFieldAdapter";
 import { useI18n } from "../../../../application/i18n/I18nProvider";
 import { Button } from "../../../ui/button";
@@ -193,7 +193,10 @@ export const ProviderConfigForm: React.FC<{
     const defaultName = PROVIDER_PRESETS[provider.providerId]?.name ?? "";
     const rawContextWindow = form.contextWindow.trim();
     const rawContextWindowNumber = Number(rawContextWindow);
-    if (rawContextWindow && (!Number.isInteger(rawContextWindowNumber) || rawContextWindowNumber <= 0)) {
+    if (
+      rawContextWindow
+      && (!Number.isInteger(rawContextWindowNumber) || rawContextWindowNumber < MIN_CONTEXT_WINDOW_TOKENS)
+    ) {
       setContextWindowError(t("ai.providers.contextWindow.error"));
       return;
     }

infrastructure/ai/contextCompaction.test.ts

@@ -11,6 +11,7 @@ import {
   formatMessagesForCompaction,
   prepareContextCompaction,
   resolveContextWindow,
+  sanitizeContextWindow,
   shouldCompactContext,
 } from "./contextCompaction.ts";
 
@@ -314,3 +315,33 @@ test("resolveContextWindow prefers manual override, then fetched model metadata,
     128000,
   );
 });
+
+test("sanitizeContextWindow rejects values below the minimum floor", () => {
+  assert.equal(sanitizeContextWindow(1), undefined);
+  assert.equal(sanitizeContextWindow(1023), undefined);
+  assert.equal(sanitizeContextWindow(1024), 1024);
+  assert.equal(sanitizeContextWindow("128000"), 128000);
+});
+
+test("resolveContextWindow ignores tiny manual overrides and falls back", () => {
+  assert.equal(
+    resolveContextWindow({
+      provider: {
+        contextWindow: 1,
+        modelContextWindows: { "qwen/test": 131072 },
+      },
+      modelId: "qwen/test",
+      defaultContextWindow: 128000,
+    }),
+    131072,
+  );
+
+  assert.equal(
+    resolveContextWindow({
+      provider: { contextWindow: 1 },
+      modelId: "unknown",
+      defaultContextWindow: 128000,
+    }),
+    128000,
+  );
+});

infrastructure/ai/contextCompaction.ts

@@ -13,6 +13,8 @@ import { redactSecretsForModel } from "./harness/modelSecretRedaction";
 const REDACTED_PAYLOAD_PREVIEW_CHARS = 80;
 
 export const DEFAULT_CONTEXT_WINDOW_TOKENS = 128_000;
+/** Floor for manual/discovered windows — values below this are treated as unset. */
+export const MIN_CONTEXT_WINDOW_TOKENS = 1_024;
 export const DEFAULT_PROTECT_RECENT_MESSAGES = 10;
 
 export const CONTEXT_COMPACTION_SYSTEM_PROMPT = `You are summarizing a long Netcatty agent conversation so it can continue without exceeding the model context window.
@@ -85,8 +87,8 @@ export function resolveContextWindow({
 
 export function sanitizeContextWindow(value: unknown): number | undefined {
   const num = typeof value === "number" ? value : Number(value);
-  if (!Number.isFinite(num) || num <= 0) return undefined;
-  return Math.max(1, Math.round(num));
+  if (!Number.isFinite(num) || num < MIN_CONTEXT_WINDOW_TOKENS) return undefined;
+  return Math.round(num);
 }
 
 export function estimateModelMessagesTokens(

infrastructure/ai/harness/contextManager.test.ts

@@ -213,6 +213,51 @@ test('prepareStepContext emits step compaction trace when over budget', async ()
   assert.ok(events.includes('step'));
 });
 
+test('prepareStepContext never returns empty messages after tiny context-window budget prune', async () => {
+  const messages: ModelMessage[] = [
+    { role: 'user', content: 'which processes use the most resources?' },
+    {
+      role: 'assistant',
+      content: [{
+        type: 'tool-call',
+        toolCallId: 'call-1',
+        toolName: 'terminal_execute',
+        input: { command: "ps -eo pid=,pcpu=,pmem=,rss=,comm= --sort=-pcpu | head -n 11" },
+      }],
+    },
+    {
+      role: 'tool',
+      content: [{
+        type: 'tool-result',
+        toolCallId: 'call-1',
+        toolName: 'terminal_execute',
+        output: {
+          type: 'text',
+          value: 'PID CPU% MEM% RSS COMMAND\n1 0.1 0.2 1024 init\n'.repeat(40),
+        },
+      }],
+    },
+  ];
+
+  const prepared = await prepareStepContext({
+    messages,
+    stepNumber: 1,
+    sessionId: 'chat-tiny-window',
+    chatSessionId: 'chat-tiny-window',
+    contextWindow: 1,
+    maxOutputTokens: 512,
+    runtimeContext: createInitialCattyRuntimeContext({
+      chatSessionId: 'chat-tiny-window',
+      turnId: 'turn-tiny',
+      permissionMode: 'confirm',
+      scopeType: 'terminal',
+    }),
+  });
+
+  assert.ok(prepared.messages.length > 0, 'step budget prune must not empty the prompt');
+  assert.match(JSON.stringify(prepared.messages), /tool-result|processes use the most/);
+});
+
 test('prepareStepContext retains handle notice after step budget guard', async () => {
   const store = new ToolOutputStore();
   store.store({

infrastructure/ai/harness/contextManager.ts

@@ -362,17 +362,24 @@ function applyStepBudgetGuard(
     reservedTokens: input.reservedTokens,
   });
   if (afterTotal >= threshold && splitAt > 0) {
-    next = keepRecentContextMessages(next, input.protectRecentMessages);
-    didAdjust = true;
-    afterTotal = computeTotalInputTokens({
-      messages: next,
-      providerId: input.providerId,
-      reservedTokens: input.reservedTokens,
-    });
+    const recent = keepRecentContextMessages(next, input.protectRecentMessages);
+    // Never accept an empty keep-recent slice — an empty prompt is worse than over-budget.
+    if (recent.length > 0) {
+      next = recent;
+      didAdjust = true;
+      afterTotal = computeTotalInputTokens({
+        messages: next,
+        providerId: input.providerId,
+        reservedTokens: input.reservedTokens,
+      });
+    }
   }
   while (afterTotal >= threshold && next.length > 2) {
     const pruned = pruneFirstModelMessage(next);
     if (pruned.length === next.length) break;
+    // A single head prune can drop a whole user+tool-call+result unit and empty the list
+    // (e.g. contextWindow=1). Reject empty prunes so the follow-up model call still has a prompt.
+    if (pruned.length === 0) break;
     next = pruned;
     didAdjust = true;
     afterTotal = computeTotalInputTokens({
@@ -382,6 +389,10 @@ function applyStepBudgetGuard(
     });
   }
 
+  if (next.length === 0 && messages.length > 0) {
+    return { messages, didAdjust: false, didTypedCompression: false };
+  }
+
   return {
     messages: next,
     didAdjust: didAdjust || next.length !== messages.length,
@@ -515,6 +526,15 @@ export async function prepareStepContext(
     ...(didAdjust ? { lastStepAdjusted: true } : {}),
   };
 
+  // Last-resort guard: never hand an empty prompt to the model after a tool step.
+  if (working.length === 0 && input.messages.length > 0) {
+    return {
+      messages: integrity.messages.length > 0 ? integrity.messages : input.messages,
+      didAdjust: false,
+      runtimeContext,
+    };
+  }
+
   return {
     messages: working,
     didAdjust,