diff --git a/src/__tests__/main/parsers/usage-aggregator.test.ts b/src/__tests__/main/parsers/usage-aggregator.test.ts
index 5161080a..f3fde93a 100644
--- a/src/__tests__/main/parsers/usage-aggregator.test.ts
+++ b/src/__tests__/main/parsers/usage-aggregator.test.ts
@@ -2,6 +2,7 @@
  * Tests for usage aggregator utilities
  */
 
+import { describe, expect, it } from 'vitest';
 import {
 	aggregateModelUsage,
 	estimateContextUsage,
@@ -96,15 +97,32 @@ describe('estimateContextUsage', () => {
 			expect(result).toBe(10);
 		});
 
-		it('should cap at 100%', () => {
+		it('should correctly calculate for Claude with all token types', () => {
+			// Simulates a real Claude response: input + cacheRead + cacheCreation = total
 			const stats = createStats({
-				inputTokens: 150000,
-				outputTokens: 100000,
+				inputTokens: 2,
+				cacheReadInputTokens: 33541,
+				cacheCreationInputTokens: 11657,
+				outputTokens: 12,
 				contextWindow: 200000,
 			});
 			const result = estimateContextUsage(stats, 'claude-code');
-			// Output tokens excluded; 150k / 200k = 75%
-			expect(result).toBe(75);
+			// (2 + 33541 + 11657) / 200000 = 45200 / 200000 = 22.6% -> 23%
+			expect(result).toBe(23);
+		});
+
+		it('should return null when tokens exceed context window (accumulated values)', () => {
+			// When Claude Code does complex multi-tool turns, token values accumulate
+			// across internal API calls and can exceed the context window
+			const stats = createStats({
+				inputTokens: 21627,
+				cacheReadInputTokens: 1079415,
+				cacheCreationInputTokens: 39734,
+				contextWindow: 200000,
+			});
+			const result = estimateContextUsage(stats, 'claude-code');
+			// Total = 1,140,776 > 200,000 -> null (accumulated, skip update)
+			expect(result).toBeNull();
 		});
 	});
 
@@ -112,6 +130,7 @@ describe('estimateContextUsage', () => {
 		it('should use claude-code default context window (200k)', () => {
 			const stats = createStats({ contextWindow: 0 });
 			const result = estimateContextUsage(stats, 'claude-code');
+			// 10000 + 0 + 0 = 10000 / 200000 = 5%
 			expect(result).toBe(5);
 		});
 
@@ -149,6 +168,18 @@ describe('estimateContextUsage', () => {
 			const result = estimateContextUsage(stats, 'claude-code');
 			expect(result).toBe(0);
 		});
+
+		it('should return null when accumulated tokens exceed default window', () => {
+			const stats = createStats({
+				inputTokens: 50000,
+				cacheReadInputTokens: 500000,
+				cacheCreationInputTokens: 10000,
+				contextWindow: 0,
+			});
+			const result = estimateContextUsage(stats, 'claude-code');
+			// 560000 > 200000 default -> null
+			expect(result).toBeNull();
+		});
 	});
 });
 
@@ -166,38 +197,52 @@ describe('calculateContextTokens', () => {
 		...overrides,
 	});
 
-	it('should exclude output tokens and cacheReadInputTokens for Claude agents', () => {
+	it('should include input + cacheRead + cacheCreation for Claude agents', () => {
 		const stats = createStats();
 		const result = calculateContextTokens(stats, 'claude-code');
-		// 10000 + 1000 = 11000 (no output tokens, no cacheRead - cumulative)
-		expect(result).toBe(11000);
+		// 10000 + 2000 + 1000 = 13000 (all input token types, excludes output)
+		expect(result).toBe(13000);
 	});
 
-	it('should include output tokens but exclude cacheReadInputTokens for Codex agents', () => {
+	it('should include input + cacheCreation + output for Codex agents', () => {
 		const stats = createStats();
 		const result = calculateContextTokens(stats, 'codex');
-		// 10000 + 5000 + 1000 = 16000 (includes output, excludes cacheRead)
+		// 10000 + 1000 + 5000 = 16000 (combined input+output window)
 		expect(result).toBe(16000);
 	});
 
 	it('should default to Claude behavior when agent is undefined', () => {
 		const stats = createStats();
 		const result = calculateContextTokens(stats);
-		// 10000 + 1000 = 11000 (excludes cacheRead)
-		expect(result).toBe(11000);
+		// 10000 + 2000 + 1000 = 13000 (Claude default: all input token types)
+		expect(result).toBe(13000);
 	});
 
-	it('should exclude cacheReadInputTokens because they are cumulative session totals', () => {
-		// cacheReadInputTokens accumulate across all turns in a session and can
-		// exceed the context window. Including them would cause context % > 100%.
+	it('should calculate correctly for typical first Claude turn', () => {
+		// Real-world scenario: first message with system prompt cache
+		const stats = createStats({
+			inputTokens: 2,
+			cacheReadInputTokens: 33541,
+			cacheCreationInputTokens: 11657,
+			outputTokens: 12,
+		});
+		const result = calculateContextTokens(stats, 'claude-code');
+		// 2 + 33541 + 11657 = 45200 (total context for the API call)
+		expect(result).toBe(45200);
+	});
+
+	it('should handle accumulated values from multi-tool turns', () => {
+		// When values are accumulated across internal API calls,
+		// the total can exceed the context window. calculateContextTokens
+		// returns the raw total; callers must check against contextWindow.
 		const stats = createStats({
 			inputTokens: 5000,
 			cacheCreationInputTokens: 1000,
-			cacheReadInputTokens: 500000, // Very high cumulative value
+			cacheReadInputTokens: 500000, // Accumulated from many internal calls
 		});
 		const result = calculateContextTokens(stats, 'claude-code');
-		// Should only be 5000 + 1000 = 6000, NOT 506000
-		expect(result).toBe(6000);
+		// 5000 + 500000 + 1000 = 506000 (raw total, may exceed window)
+		expect(result).toBe(506000);
 	});
 });
 
diff --git a/src/__tests__/main/process-listeners/usage-listener.test.ts b/src/__tests__/main/process-listeners/usage-listener.test.ts
index 6a2df6a6..6d5385ce 100644
--- a/src/__tests__/main/process-listeners/usage-listener.test.ts
+++ b/src/__tests__/main/process-listeners/usage-listener.test.ts
@@ -162,19 +162,21 @@ describe('Usage Listener', () => {
 			});
 		});
 
-		it('should handle zero context window gracefully', async () => {
+		it('should handle zero context window gracefully (falls back to 200k default)', async () => {
 			setupListener();
 			const handler = eventHandlers.get('usage');
 			const usageStats = createMockUsageStats({ contextWindow: 0 });
 
 			handler?.('group-chat-test-chat-123-participant-TestAgent-abc123', usageStats);
 
+			// With contextWindow 0, falls back to 200k default
+			// 1800 / 200000 = 0.9% -> rounds to 1%
 			await vi.waitFor(() => {
 				expect(mockDeps.groupChatStorage.updateParticipant).toHaveBeenCalledWith(
 					'test-chat-123',
 					'TestAgent',
 					expect.objectContaining({
-						contextUsage: 0,
+						contextUsage: 1,
 					})
 				);
 			});
diff --git a/src/__tests__/renderer/components/HistoryDetailModal.test.tsx b/src/__tests__/renderer/components/HistoryDetailModal.test.tsx
index 234236b9..1db065af 100644
--- a/src/__tests__/renderer/components/HistoryDetailModal.test.tsx
+++ b/src/__tests__/renderer/components/HistoryDetailModal.test.tsx
@@ -470,9 +470,9 @@ describe('HistoryDetailModal', () => {
 				/>
 			);
 
-			// Context = (inputTokens + cacheCreationInputTokens) / contextWindow (cacheRead excluded)
-			// (5000 + 5000) / 100000 = 10%
-			expect(screen.getByText('10%')).toBeInTheDocument();
+			// Context = (inputTokens + cacheReadInputTokens + cacheCreationInputTokens) / contextWindow
+			// (5000 + 2000 + 5000) / 100000 = 12%
+			expect(screen.getByText('12%')).toBeInTheDocument();
 		});
 
 		it('should display token counts', () => {
diff --git a/src/__tests__/renderer/components/MainPanel.test.tsx b/src/__tests__/renderer/components/MainPanel.test.tsx
index c4c024e6..3808e781 100644
--- a/src/__tests__/renderer/components/MainPanel.test.tsx
+++ b/src/__tests__/renderer/components/MainPanel.test.tsx
@@ -1955,8 +1955,8 @@ describe('MainPanel', () => {
 				<MainPanel {...defaultProps} activeSession={session} getContextColor={getContextColor} />
 			);
 
-			// Context usage should be 50000 / 200000 * 100 = 25% (cacheRead excluded - cumulative)
-			expect(getContextColor).toHaveBeenCalledWith(25, theme);
+			// Context usage: (50000 + 25000 + 0) / 200000 * 100 = 38% (input + cacheRead + cacheCreation)
+			expect(getContextColor).toHaveBeenCalledWith(38, theme);
 		});
 	});
 
@@ -2373,9 +2373,10 @@ describe('MainPanel', () => {
 			expect(screen.queryByText('Context Window')).not.toBeInTheDocument();
 		});
 
-		it('should cap context usage at 100%', () => {
-			const getContextColor = vi.fn().mockReturnValue('#ef4444');
+		it('should use preserved session.contextUsage when accumulated values exceed window', () => {
+			const getContextColor = vi.fn().mockReturnValue('#22c55e');
 			const session = createSession({
+				contextUsage: 45, // Preserved valid percentage from last non-accumulated update
 				aiTabs: [
 					{
 						id: 'tab-1',
@@ -2386,8 +2387,8 @@ describe('MainPanel', () => {
 						usageStats: {
 							inputTokens: 150000,
 							outputTokens: 100000,
-							cacheReadInputTokens: 100000, // Excluded from calculation (cumulative)
-							cacheCreationInputTokens: 100000, // Included in calculation
+							cacheReadInputTokens: 100000, // Accumulated from multi-tool turn
+							cacheCreationInputTokens: 100000, // Accumulated from multi-tool turn
 							totalCostUsd: 0.05,
 							contextWindow: 200000,
 						},
@@ -2400,8 +2401,9 @@ describe('MainPanel', () => {
 				<MainPanel {...defaultProps} activeSession={session} getContextColor={getContextColor} />
 			);
 
-			// Context usage: (150000 + 100000) / 200000 = 125% -> capped at 100%
-			expect(getContextColor).toHaveBeenCalledWith(100, theme);
+			// raw = 150000 + 100000 + 100000 = 350000 > 200000 (accumulated)
+			// Falls back to session.contextUsage = 45%
+			expect(getContextColor).toHaveBeenCalledWith(45, theme);
 		});
 	});
 
diff --git a/src/__tests__/renderer/utils/contextExtractor.test.ts b/src/__tests__/renderer/utils/contextExtractor.test.ts
index 88feeec4..149cd1aa 100644
--- a/src/__tests__/renderer/utils/contextExtractor.test.ts
+++ b/src/__tests__/renderer/utils/contextExtractor.test.ts
@@ -650,8 +650,8 @@ describe('calculateTotalTokens', () => {
 
 		const total = calculateTotalTokens(contexts);
 
-		// input + cacheCreation for each context (cacheRead excluded - cumulative)
-		expect(total).toBe(450); // (100+25) + (300+25)
+		// input + cacheRead + cacheCreation for each context
+		expect(total).toBe(575); // (100+50+25) + (300+75+25)
 	});
 });
 
@@ -694,8 +694,8 @@ describe('getContextSummary', () => {
 
 		expect(summary.totalSources).toBe(2);
 		expect(summary.totalLogs).toBe(5);
-		// (100+25) + (200+25) = 350 (cacheRead excluded - cumulative)
-		expect(summary.estimatedTokens).toBe(350);
+		// (100+50+25) + (200+75+25) = 475 (input + cacheRead + cacheCreation)
+		expect(summary.estimatedTokens).toBe(475);
 		expect(summary.byAgent['claude-code']).toBe(1);
 		expect(summary.byAgent['opencode']).toBe(1);
 	});
diff --git a/src/__tests__/renderer/utils/contextUsage.test.ts b/src/__tests__/renderer/utils/contextUsage.test.ts
index 3ac808c8..b3865c22 100644
--- a/src/__tests__/renderer/utils/contextUsage.test.ts
+++ b/src/__tests__/renderer/utils/contextUsage.test.ts
@@ -28,30 +28,30 @@ describe('estimateContextUsage', () => {
 			expect(result).toBe(10);
 		});
 
-		it('should exclude cacheReadInputTokens from calculation (cumulative, not per-request)', () => {
+		it('should include cacheReadInputTokens in calculation (part of total input context)', () => {
 			const stats = createStats({
 				inputTokens: 1000,
 				outputTokens: 500,
-				cacheReadInputTokens: 50000, // Should be ignored
+				cacheReadInputTokens: 50000,
 				cacheCreationInputTokens: 5000,
 				contextWindow: 100000,
 			});
 			const result = estimateContextUsage(stats, 'claude-code');
-			// (1000 + 5000) / 100000 = 6% (cacheRead excluded)
-			expect(result).toBe(6);
+			// (1000 + 50000 + 5000) / 100000 = 56%
+			expect(result).toBe(56);
 		});
 
-		it('should cap at 100%', () => {
+		it('should return null when accumulated tokens exceed context window', () => {
 			const stats = createStats({
 				inputTokens: 50000,
 				outputTokens: 50000,
-				cacheReadInputTokens: 150000, // Ignored
+				cacheReadInputTokens: 150000,
 				cacheCreationInputTokens: 200000,
 				contextWindow: 200000,
 			});
 			const result = estimateContextUsage(stats, 'claude-code');
-			// (50000 + 200000) / 200000 = 125% -> capped at 100%
-			expect(result).toBe(100);
+			// (50000 + 150000 + 200000) = 400000 > 200000 -> null (accumulated values)
+			expect(result).toBeNull();
 		});
 
 		it('should round to nearest integer', () => {
@@ -139,19 +139,20 @@ describe('estimateContextUsage', () => {
 			expect(result).toBe(10);
 		});
 
-		it('should ignore large cache read tokens (they are cumulative, not per-request)', () => {
-			// Claude Code reports cacheReadInputTokens as cumulative session totals.
-			// They can exceed the context window, so we exclude them from calculation.
+		it('should return null when accumulated cacheRead tokens cause total to exceed context window', () => {
+			// During multi-tool turns, Claude Code accumulates token values across
+			// internal API calls. When accumulated total exceeds context window,
+			// return null to signal callers should preserve previous valid percentage.
 			const stats = createStats({
-				inputTokens: 500, // small new turn input
-				outputTokens: 1000, // small response
-				cacheReadInputTokens: 758000, // cumulative across session - should be IGNORED
-				cacheCreationInputTokens: 50000, // new cache this turn
+				inputTokens: 500,
+				outputTokens: 1000,
+				cacheReadInputTokens: 758000, // accumulated across multi-tool turn
+				cacheCreationInputTokens: 50000,
 				contextWindow: 200000,
 			});
 			const result = estimateContextUsage(stats, 'claude-code');
-			// (500 + 50000) / 200000 = 25% (cacheRead excluded)
-			expect(result).toBe(25);
+			// (500 + 758000 + 50000) = 808500 > 200000 -> null (accumulated values)
+			expect(result).toBeNull();
 		});
 	});
 
@@ -172,17 +173,17 @@ describe('estimateContextUsage', () => {
 			expect(result).toBe(5);
 		});
 
-		it('should handle very large token counts', () => {
+		it('should return null for very large accumulated token counts', () => {
 			const stats = createStats({
 				inputTokens: 250000,
 				outputTokens: 500000,
-				cacheReadInputTokens: 500000, // Ignored
+				cacheReadInputTokens: 500000,
 				cacheCreationInputTokens: 250000,
 				contextWindow: 0,
 			});
 			const result = estimateContextUsage(stats, 'claude-code');
-			// (250000 + 250000) / 200000 = 250% -> capped at 100%
-			expect(result).toBe(100);
+			// (250000 + 500000 + 250000) = 1000000 > 200000 -> null (accumulated values)
+			expect(result).toBeNull();
 		});
 
 		it('should handle very small percentages', () => {
@@ -213,34 +214,33 @@ describe('calculateContextTokens', () => {
 		...overrides,
 	});
 
-	describe('Claude agents (excludes output and cacheRead tokens)', () => {
-		it('should exclude output and cacheRead tokens for claude-code', () => {
+	describe('Claude agents (input + cacheRead + cacheCreation)', () => {
+		it('should include input, cacheRead, and cacheCreation tokens for claude-code', () => {
 			const stats = createStats();
 			const result = calculateContextTokens(stats, 'claude-code');
-			// 10000 + 1000 = 11000 (no output, no cacheRead)
-			// cacheRead is excluded because Claude Code reports it as cumulative
-			expect(result).toBe(11000);
+			// 10000 + 2000 + 1000 = 13000 (excludes output only)
+			expect(result).toBe(13000);
 		});
 
-		it('should exclude output and cacheRead tokens for claude', () => {
+		it('should include input, cacheRead, and cacheCreation tokens for claude', () => {
 			const stats = createStats();
 			const result = calculateContextTokens(stats, 'claude');
-			expect(result).toBe(11000);
+			expect(result).toBe(13000);
 		});
 
-		it('should exclude output and cacheRead tokens when agent is undefined', () => {
+		it('should include input, cacheRead, and cacheCreation tokens when agent is undefined', () => {
 			const stats = createStats();
 			const result = calculateContextTokens(stats);
 			// Defaults to Claude behavior
-			expect(result).toBe(11000);
+			expect(result).toBe(13000);
 		});
 	});
 
 	describe('OpenAI agents (includes output tokens)', () => {
-		it('should include output tokens for codex', () => {
+		it('should include input, output, and cacheCreation tokens for codex', () => {
 			const stats = createStats();
 			const result = calculateContextTokens(stats, 'codex');
-			// 10000 + 5000 + 1000 = 16000 (includes output, excludes cacheRead)
+			// 10000 + 5000 + 1000 = 16000 (input + output + cacheCreation, excludes cacheRead)
 			expect(result).toBe(16000);
 		});
 	});
@@ -268,18 +268,19 @@ describe('calculateContextTokens', () => {
 			expect(result).toBe(10000);
 		});
 
-		it('should ignore large cacheRead values (cumulative session data)', () => {
-			// This tests the real bug scenario: Claude Code reports cumulative cacheRead
-			// that exceeds context window, which would cause 100%+ display
+		it('should include cacheRead in raw calculation (callers detect accumulated values)', () => {
+			// calculateContextTokens returns the raw total including cacheRead.
+			// Callers (estimateContextUsage) detect when total > contextWindow
+			// and return null to signal accumulated values from multi-tool turns.
 			const stats = createStats({
 				inputTokens: 50000,
 				outputTokens: 9000,
-				cacheReadInputTokens: 758000, // Cumulative - should be IGNORED
+				cacheReadInputTokens: 758000,
 				cacheCreationInputTokens: 75000,
 			});
 			const result = calculateContextTokens(stats, 'claude-code');
-			// 50000 + 75000 = 125000 (cacheRead excluded)
-			expect(result).toBe(125000);
+			// 50000 + 758000 + 75000 = 883000 (raw total, callers check against window)
+			expect(result).toBe(883000);
 		});
 	});
 });
diff --git a/src/main/parsers/usage-aggregator.ts b/src/main/parsers/usage-aggregator.ts
index 150937b2..10f4b323 100644
--- a/src/main/parsers/usage-aggregator.ts
+++ b/src/main/parsers/usage-aggregator.ts
@@ -60,12 +60,16 @@ const COMBINED_CONTEXT_AGENTS: Set<ToolType> = new Set(['codex']);
 /**
  * Calculate total context tokens based on agent-specific semantics.
  *
- * IMPORTANT: Claude Code reports CUMULATIVE session tokens, not per-request tokens.
- * The cacheReadInputTokens can exceed the context window because they accumulate
- * across all turns in the conversation. For context pressure display, we should
- * only count tokens that represent NEW context being added:
+ * For a single Anthropic API call, the total input context is the sum of:
+ *   inputTokens + cacheReadInputTokens + cacheCreationInputTokens
+ * These three fields partition the input into uncached, cache-hit, and newly-cached segments.
  *
- * Claude models: Context = input + cacheCreation (excludes cacheRead - already cached)
+ * CAVEAT: When Claude Code performs multi-tool turns (many internal API calls),
+ * the reported values may be accumulated across all internal calls within the turn.
+ * In that case the total can exceed the context window. Callers should check for
+ * this and skip the update (see estimateContextUsage).
+ *
+ * Claude models: Context = input + cacheRead + cacheCreation
  * OpenAI models: Context = input + output (combined limit)
  *
  * @param stats - The usage statistics containing token counts
@@ -79,34 +83,31 @@ export function calculateContextTokens(
 	>,
 	agentId?: ToolType
 ): number {
-	// For Claude: inputTokens = uncached new tokens, cacheCreationInputTokens = newly cached tokens
-	// cacheReadInputTokens are EXCLUDED because they represent already-cached context
-	// that Claude Code reports cumulatively across the session, not per-request.
-	// Including them would cause context % to exceed 100% impossibly.
-	const baseTokens = stats.inputTokens + (stats.cacheCreationInputTokens || 0);
-
 	// OpenAI models have combined input+output context limits
 	if (agentId && COMBINED_CONTEXT_AGENTS.has(agentId)) {
-		return baseTokens + stats.outputTokens;
+		return stats.inputTokens + (stats.cacheCreationInputTokens || 0) + stats.outputTokens;
 	}
 
-	// Claude models: output tokens don't consume context window
-	return baseTokens;
+	// Claude models: total input = uncached + cache-hit + newly-cached
+	// Output tokens don't consume the input context window
+	return (
+		stats.inputTokens + (stats.cacheReadInputTokens || 0) + (stats.cacheCreationInputTokens || 0)
+	);
 }
 
 /**
  * Estimate context usage percentage when the agent doesn't provide it directly.
  * Uses agent-specific default context window sizes for accurate estimation.
  *
- * IMPORTANT: Context calculation varies by agent:
- * - Claude models: inputTokens + cacheCreationInputTokens
- *   (cacheRead excluded - cumulative, output excluded - separate limit)
- * - OpenAI models (Codex): inputTokens + outputTokens
- *   (combined context window includes both input and output)
+ * Context calculation varies by agent:
+ * - Claude models: inputTokens + cacheReadInputTokens + cacheCreationInputTokens
+ * - OpenAI models (Codex): inputTokens + outputTokens (combined limit)
  *
- * Note: cacheReadInputTokens are NOT included because Claude Code reports them
- * as cumulative session totals, not per-request values. Including them would
- * cause context percentage to exceed 100% impossibly.
+ * Returns null when the calculated total exceeds the context window, which indicates
+ * accumulated values from multi-tool turns (many internal API calls within one turn).
+ * A single API call's total input can never exceed the context window, so values
+ * above it are definitely accumulated. Callers should preserve the previous valid
+ * percentage when this returns null.
  *
  * @param stats - The usage statistics containing token counts
  * @param agentId - The agent identifier for agent-specific context window size
@@ -126,19 +127,23 @@ export function estimateContextUsage(
 	// Calculate total context using agent-specific semantics
 	const totalContextTokens = calculateContextTokens(stats, agentId);
 
-	// If context window is provided and valid, use it
-	if (stats.contextWindow && stats.contextWindow > 0) {
-		return Math.min(100, Math.round((totalContextTokens / stats.contextWindow) * 100));
-	}
+	// Determine effective context window
+	const effectiveContextWindow =
+		stats.contextWindow && stats.contextWindow > 0
+			? stats.contextWindow
+			: agentId && agentId !== 'terminal'
+				? DEFAULT_CONTEXT_WINDOWS[agentId] || 0
+				: 0;
 
-	// If no agent specified or terminal, cannot estimate
-	if (!agentId || agentId === 'terminal') {
+	if (!effectiveContextWindow || effectiveContextWindow <= 0) {
 		return null;
 	}
 
-	// Use agent-specific default context window
-	const defaultContextWindow = DEFAULT_CONTEXT_WINDOWS[agentId];
-	if (!defaultContextWindow || defaultContextWindow <= 0) {
+	// If total exceeds context window, the values are accumulated across multiple
+	// internal API calls within a complex turn (tool use chains). A single API call's
+	// total input cannot exceed the context window. Return null to signal callers
+	// should keep the previous valid percentage.
+	if (totalContextTokens > effectiveContextWindow) {
 		return null;
 	}
 
@@ -146,7 +151,7 @@ export function estimateContextUsage(
 		return 0;
 	}
 
-	return Math.min(100, Math.round((totalContextTokens / defaultContextWindow) * 100));
+	return Math.round((totalContextTokens / effectiveContextWindow) * 100);
 }
 
 /**
diff --git a/src/main/process-listeners/usage-listener.ts b/src/main/process-listeners/usage-listener.ts
index 757bd0c9..26c2a042 100644
--- a/src/main/process-listeners/usage-listener.ts
+++ b/src/main/process-listeners/usage-listener.ts
@@ -52,18 +52,29 @@ export function setupUsageListener(
 			// Calculate context usage percentage using agent-specific logic
 			// Note: For group chat, we don't have agent type here, defaults to Claude behavior
 			const totalContextTokens = usageAggregator.calculateContextTokens(usageStats);
-			const contextUsage =
-				usageStats.contextWindow > 0
-					? Math.round((totalContextTokens / usageStats.contextWindow) * 100)
-					: 0;
+			const effectiveWindow = usageStats.contextWindow > 0 ? usageStats.contextWindow : 200000;
+
+			// Skip update if values are accumulated (total > window) from multi-tool turns
+			const contextUsage =
+				totalContextTokens <= effectiveWindow
+					? Math.round((totalContextTokens / effectiveWindow) * 100)
+					: -1; // -1 signals "skip update"
+
+			// Update participant with usage stats (skip context update if accumulated)
+			const updateData: {
+				contextUsage?: number;
+				tokenCount?: number;
+				totalCost: number;
+			} = {
+				totalCost: usageStats.totalCostUsd,
+			};
+			if (contextUsage >= 0) {
+				updateData.contextUsage = contextUsage;
+				updateData.tokenCount = totalContextTokens;
+			}
 
-			// Update participant with usage stats
 			groupChatStorage
-				.updateParticipant(groupChatId, participantName, {
-					contextUsage,
-					tokenCount: totalContextTokens,
-					totalCost: usageStats.totalCostUsd,
-				})
+				.updateParticipant(groupChatId, participantName, updateData)
 				.then((updatedChat) => {
 					// Emit participants changed so UI updates
 					// Note: updateParticipant returns the updated chat, avoiding extra DB read
@@ -87,17 +98,25 @@ export function setupUsageListener(
 			// Calculate context usage percentage using agent-specific logic
 			// Note: Moderator is typically Claude, defaults to Claude behavior
 			const totalContextTokens = usageAggregator.calculateContextTokens(usageStats);
-			const contextUsage =
-				usageStats.contextWindow > 0
-					? Math.round((totalContextTokens / usageStats.contextWindow) * 100)
-					: 0;
+			const effectiveWindow = usageStats.contextWindow > 0 ? usageStats.contextWindow : 200000;
 
-			// Emit moderator usage for the moderator card
-			groupChatEmitters.emitModeratorUsage?.(groupChatId, {
-				contextUsage,
-				totalCost: usageStats.totalCostUsd,
-				tokenCount: totalContextTokens,
-			});
+			// Skip context update if values are accumulated (total > window) from multi-tool turns.
+			// When accumulated, emit with contextUsage/tokenCount as -1 so the handler
+			// knows to preserve the previous values. Cost is always updated.
+			if (totalContextTokens <= effectiveWindow) {
+				const contextUsage = Math.round((totalContextTokens / effectiveWindow) * 100);
+				groupChatEmitters.emitModeratorUsage?.(groupChatId, {
+					contextUsage,
+					totalCost: usageStats.totalCostUsd,
+					tokenCount: totalContextTokens,
+				});
+			} else {
+				groupChatEmitters.emitModeratorUsage?.(groupChatId, {
+					contextUsage: -1,
+					totalCost: usageStats.totalCostUsd,
+					tokenCount: -1,
+				});
+			}
 		}
 
 		safeSend('process:usage', sessionId, usageStats);
diff --git a/src/renderer/App.tsx b/src/renderer/App.tsx
index 8733308c..b010a767 100644
--- a/src/renderer/App.tsx
+++ b/src/renderer/App.tsx
@@ -2714,36 +2714,30 @@ function MaestroConsoleInner() {
 				actualSessionId = sessionId;
 			}
 
-			// Calculate context window usage percentage from CURRENT reported tokens.
-			// IMPORTANT: Claude Code reports cacheReadInputTokens as CUMULATIVE session totals,
-			// not per-request values. Including them causes context % to exceed 100% impossibly.
-			// For Claude: context = inputTokens + cacheCreationInputTokens (new content only)
+			// Calculate context window usage percentage.
+			// For Claude: context = inputTokens + cacheReadInputTokens + cacheCreationInputTokens
+			//   (these three fields partition the total input into uncached, cache-hit, newly-cached)
 			// For Codex: context = inputTokens + outputTokens (combined limit)
+			//
+			// When Claude Code performs complex multi-tool turns, the reported values are
+			// accumulated across internal API calls and can exceed the context window.
+			// estimateContextUsage returns null in that case - we skip the update and
+			// keep the last valid measurement. This means the gauge may stay static
+			// during tool-heavy turns, but it's always accurate when it does update,
+			// keeping the compact warning reliable.
 			const sessionForUsage = sessionsRef.current.find((s) => s.id === actualSessionId);
 			const agentToolType = sessionForUsage?.toolType;
-			const isClaudeUsage = agentToolType === 'claude-code' || agentToolType === 'claude';
-			const currentContextTokens = isClaudeUsage
-				? usageStats.inputTokens + usageStats.cacheCreationInputTokens
-				: usageStats.inputTokens + usageStats.outputTokens;
-
-			// Calculate context percentage, falling back to agent-specific defaults if contextWindow not provided
-			let contextPercentage: number;
-			if (usageStats.contextWindow > 0) {
-				contextPercentage = Math.min(
-					Math.round((currentContextTokens / usageStats.contextWindow) * 100),
-					100
-				);
-			} else {
-				// Use fallback estimation with agent-specific default context window
-				const estimated = estimateContextUsage(usageStats, agentToolType);
-				contextPercentage = estimated ?? 0;
-			}
+			const contextPercentage = estimateContextUsage(usageStats, agentToolType);
 
 			// Batch the usage stats update, context percentage, and cycle tokens
 			// The batched updater handles the accumulation logic internally
 			batchedUpdater.updateUsage(actualSessionId, tabId, usageStats);
 			batchedUpdater.updateUsage(actualSessionId, null, usageStats); // Session-level accumulation
-			batchedUpdater.updateContextUsage(actualSessionId, contextPercentage);
+			if (contextPercentage !== null) {
+				// Valid measurement from a non-accumulated turn - use it directly
+				batchedUpdater.updateContextUsage(actualSessionId, contextPercentage);
+			}
+			// When null (accumulated values), keep the last valid percentage unchanged
 			batchedUpdater.updateCycleTokens(actualSessionId, usageStats.outputTokens);
 
 			// Update persistent global stats (not batched - this is a separate concern)
@@ -3272,7 +3266,17 @@ function MaestroConsoleInner() {
 
 		const unsubModeratorUsage = window.maestro.groupChat.onModeratorUsage?.((id, usage) => {
 			if (id === activeGroupChatId) {
-				setModeratorUsage(usage);
+				// When contextUsage is -1, values are accumulated from multi-tool turns.
+				// Preserve previous context/token values, only update cost.
+				if (usage.contextUsage === -1) {
+					setModeratorUsage((prev) =>
+						prev
+							? { ...prev, totalCost: usage.totalCost }
+							: { contextUsage: 0, totalCost: usage.totalCost, tokenCount: 0 }
+					);
+				} else {
+					setModeratorUsage(usage);
+				}
 			}
 		});
 
diff --git a/src/renderer/components/MainPanel.tsx b/src/renderer/components/MainPanel.tsx
index c23bdcc1..c9314f5e 100644
--- a/src/renderer/components/MainPanel.tsx
+++ b/src/renderer/components/MainPanel.tsx
@@ -544,11 +544,13 @@ export const MainPanel = React.memo(
 		}, [configuredContextWindow, activeTab?.usageStats?.contextWindow]);
 
 		// Compute context tokens using agent-specific calculation
-		// Claude: input + cacheCreation (excludes cacheRead which is cumulative)
+		// Claude: input + cacheRead + cacheCreation (total input for the request)
 		// Codex: input + output (combined limit)
+		// When values are accumulated from multi-tool turns, total may exceed contextWindow.
+		// In that case, derive tokens from session.contextUsage (preserved last valid percentage).
 		const activeTabContextTokens = useMemo(() => {
 			if (!activeTab?.usageStats) return 0;
-			return calculateContextTokens(
+			const raw = calculateContextTokens(
 				{
 					inputTokens: activeTab.usageStats.inputTokens,
 					outputTokens: activeTab.usageStats.outputTokens,
@@ -557,7 +559,20 @@ export const MainPanel = React.memo(
 				},
 				activeSession?.toolType
 			);
-		}, [activeTab?.usageStats, activeSession?.toolType]);
+			// Accumulated from multi-tool turns: derive from session's preserved percentage.
+			// App.tsx skips updating session.contextUsage when accumulated, so it holds
+			// the last valid percentage from estimateContextUsage.
+			if (activeTabContextWindow > 0 && raw > activeTabContextWindow) {
+				const preservedPercentage = activeSession?.contextUsage ?? 0;
+				return Math.round((preservedPercentage / 100) * activeTabContextWindow);
+			}
+			return raw;
+		}, [
+			activeTab?.usageStats,
+			activeSession?.toolType,
+			activeTabContextWindow,
+			activeSession?.contextUsage,
+		]);
 
 		// Compute context usage percentage from context tokens and window size
 		const activeTabContextUsage = useMemo(() => {
diff --git a/src/renderer/utils/contextUsage.ts b/src/renderer/utils/contextUsage.ts
index 1b150ddb..cb7e376b 100644
--- a/src/renderer/utils/contextUsage.ts
+++ b/src/renderer/utils/contextUsage.ts
@@ -31,12 +31,16 @@ const COMBINED_CONTEXT_AGENTS: Set<ToolType> = new Set(['codex']);
 /**
  * Calculate total context tokens based on agent-specific semantics.
  *
- * IMPORTANT: Claude Code reports CUMULATIVE session tokens, not per-request tokens.
- * The cacheReadInputTokens can exceed the context window because they accumulate
- * across all turns in the conversation. For context pressure display, we should
- * only count tokens that represent NEW context being added:
+ * For a single Anthropic API call, the total input context is the sum of:
+ *   inputTokens + cacheReadInputTokens + cacheCreationInputTokens
+ * These three fields partition the input into uncached, cache-hit, and newly-cached segments.
  *
- * Claude models: Context = input + cacheCreation (excludes cacheRead - already cached)
+ * CAVEAT: When Claude Code performs multi-tool turns (many internal API calls),
+ * the reported values may be accumulated across all internal calls within the turn.
+ * In that case the total can exceed the context window. Callers should check for
+ * this and skip the update (see estimateContextUsage).
+ *
+ * Claude models: Context = input + cacheRead + cacheCreation
  * OpenAI models: Context = input + output (combined limit)
  *
  * @param stats - The usage statistics containing token counts
@@ -50,34 +54,31 @@ export function calculateContextTokens(
 	>,
 	agentId?: ToolType
 ): number {
-	// For Claude: inputTokens = uncached new tokens, cacheCreationInputTokens = newly cached tokens
-	// cacheReadInputTokens are EXCLUDED because they represent already-cached context
-	// that Claude Code reports cumulatively across the session, not per-request.
-	// Including them would cause context % to exceed 100% impossibly.
-	const baseTokens = stats.inputTokens + (stats.cacheCreationInputTokens || 0);
-
 	// OpenAI models have combined input+output context limits
 	if (agentId && COMBINED_CONTEXT_AGENTS.has(agentId)) {
-		return baseTokens + stats.outputTokens;
+		return stats.inputTokens + (stats.cacheCreationInputTokens || 0) + stats.outputTokens;
 	}
 
-	// Claude models: output tokens don't consume context window
-	return baseTokens;
+	// Claude models: total input = uncached + cache-hit + newly-cached
+	// Output tokens don't consume the input context window
+	return (
+		stats.inputTokens + (stats.cacheReadInputTokens || 0) + (stats.cacheCreationInputTokens || 0)
+	);
 }
 
 /**
  * Estimate context usage percentage when the agent doesn't provide it directly.
  * Uses agent-specific default context window sizes for accurate estimation.
  *
- * IMPORTANT: Context calculation varies by agent:
- * - Claude models: inputTokens + cacheCreationInputTokens
- *   (cacheRead excluded - cumulative, output excluded - separate limit)
- * - OpenAI models (Codex): inputTokens + outputTokens
- *   (combined context window includes both input and output)
+ * Context calculation varies by agent:
+ * - Claude models: inputTokens + cacheReadInputTokens + cacheCreationInputTokens
+ * - OpenAI models (Codex): inputTokens + outputTokens (combined limit)
  *
- * Note: cacheReadInputTokens are NOT included because Claude Code reports them
- * as cumulative session totals, not per-request values. Including them would
- * cause context percentage to exceed 100% impossibly.
+ * Returns null when the calculated total exceeds the context window, which indicates
+ * accumulated values from multi-tool turns (many internal API calls within one turn).
+ * A single API call's total input can never exceed the context window, so values
+ * above it are definitely accumulated. Callers should preserve the previous valid
+ * percentage when this returns null.
  *
  * @param stats - The usage statistics containing token counts
  * @param agentId - The agent identifier for agent-specific context window size
@@ -97,19 +98,23 @@ export function estimateContextUsage(
 	// Calculate total context using agent-specific semantics
 	const totalContextTokens = calculateContextTokens(stats, agentId);
 
-	// If context window is provided and valid, use it
-	if (stats.contextWindow && stats.contextWindow > 0) {
-		return Math.min(100, Math.round((totalContextTokens / stats.contextWindow) * 100));
-	}
+	// Determine effective context window
+	const effectiveContextWindow =
+		stats.contextWindow && stats.contextWindow > 0
+			? stats.contextWindow
+			: agentId && agentId !== 'terminal'
+				? DEFAULT_CONTEXT_WINDOWS[agentId] || 0
+				: 0;
 
-	// If no agent specified or terminal, cannot estimate
-	if (!agentId || agentId === 'terminal') {
+	if (!effectiveContextWindow || effectiveContextWindow <= 0) {
 		return null;
 	}
 
-	// Use agent-specific default context window
-	const defaultContextWindow = DEFAULT_CONTEXT_WINDOWS[agentId];
-	if (!defaultContextWindow || defaultContextWindow <= 0) {
+	// If total exceeds context window, the values are accumulated across multiple
+	// internal API calls within a complex turn (tool use chains). A single API call's
+	// total input cannot exceed the context window. Return null to signal callers
+	// should keep the previous valid percentage.
+	if (totalContextTokens > effectiveContextWindow) {
 		return null;
 	}
 
@@ -117,5 +122,5 @@ export function estimateContextUsage(
 		return 0;
 	}
 
-	return Math.min(100, Math.round((totalContextTokens / defaultContextWindow) * 100));
+	return Math.round((totalContextTokens / effectiveContextWindow) * 100);
 }