Fix linting errors for MCP workspace

Author: chrisreddington

mcp-server/src/ai/rock-paper-scissors-ai.test.ts

@@ -1,4 +1,4 @@
-import { RockPaperScissorsAI, type Strategy, type Difficulty } from './rock-paper-scissors-ai.js';
+import { RockPaperScissorsAI } from './rock-paper-scissors-ai.js';
 import type { RPSGameState, RPSChoice, Player } from '@turn-based-mcp/shared';
 import { RockPaperScissorsGame } from '@turn-based-mcp/shared';
 
@@ -59,8 +59,8 @@ describe('RockPaperScissorsAI', () => {
       });
 
       it('should counter the most frequent opponent choice', async () => {
-        // Create a state where opponent played rock 2 times, paper 1 time
-        let state = initialState;
+  // Create a state where opponent played rock 2 times, paper 1 time
+  let state = initialState;
         state = game.applyMove(state, { choice: 'rock' }, 'player1');
         state = game.applyMove(state, { choice: 'paper' }, 'ai');
         state = game.applyMove(state, { choice: 'rock' }, 'player1');
@@ -74,8 +74,8 @@ describe('RockPaperScissorsAI', () => {
       });
 
       it('should handle tied frequencies', async () => {
-        // Create equal frequency scenario
-        let state = initialState;
+  // Create equal frequency scenario
+  let state = initialState;
         state = game.applyMove(state, { choice: 'rock' }, 'player1');
         state = game.applyMove(state, { choice: 'paper' }, 'ai');
         state = game.applyMove(state, { choice: 'paper' }, 'player1');
@@ -126,7 +126,7 @@ describe('RockPaperScissorsAI', () => {
     });
 
     it('should default to random for invalid difficulty', async () => {
-      const choice = await ai.makeChoice(initialState, 'invalid' as Difficulty);
+  const choice = await ai.makeChoice(initialState, 'invalid' as any);
       expect(['rock', 'paper', 'scissors']).toContain(choice);
     });
   });
@@ -156,7 +156,7 @@ describe('RockPaperScissorsAI', () => {
   });
 
   describe('analyzeGameState', () => {
-    it('should provide basic game analysis for initial state', () => {
+  it('should provide basic game analysis for initial state', () => {
       const analysis = ai.analyzeGameState(initialState);
 
       expect(analysis).toContain('Game Status: playing');
@@ -165,7 +165,7 @@ describe('RockPaperScissorsAI', () => {
     });
 
     it('should show round history after moves', async () => {
-      let state = initialState;
+  let state = initialState;
       state = game.applyMove(state, { choice: 'rock' }, 'player1');
       state = game.applyMove(state, { choice: 'paper' }, 'ai');
 
@@ -175,7 +175,7 @@ describe('RockPaperScissorsAI', () => {
     });
 
     it('should analyze opponent patterns', async () => {
-      let state = initialState;
+  let state = initialState;
       // Create pattern: rock, paper, rock
       state = game.applyMove(state, { choice: 'rock' }, 'player1');
       state = game.applyMove(state, { choice: 'scissors' }, 'ai');
@@ -196,7 +196,7 @@ describe('RockPaperScissorsAI', () => {
     });
 
     it('should show current score correctly', async () => {
-      let state = initialState;
+      let state = initialState; // reassigned in subsequent applyMove calls
       // Player 1 wins first round
       state = game.applyMove(state, { choice: 'rock' }, 'player1');
       state = game.applyMove(state, { choice: 'scissors' }, 'ai');
@@ -208,7 +208,7 @@ describe('RockPaperScissorsAI', () => {
     });
 
     it('should handle finished games', () => {
-      let state = initialState;
+      const state = { ...initialState }; // mutate copy, no reassignment afterward
       state.status = 'finished';
       state.winner = 'player1';
       state.currentRound = 3;
@@ -218,7 +218,7 @@ describe('RockPaperScissorsAI', () => {
     });
 
     it('should handle draw rounds', async () => {
-      let state = initialState;
+      let state = initialState; // reassigned in applyMove calls
       state = game.applyMove(state, { choice: 'rock' }, 'player1');
       state = game.applyMove(state, { choice: 'rock' }, 'player2');
 
@@ -278,7 +278,7 @@ describe('RockPaperScissorsAI', () => {
     });
 
     it('should maintain consistent difficulty behavior', async () => {
-      const difficulties: Difficulty[] = ['easy', 'medium', 'hard'];
+  const difficulties: any[] = ['easy', 'medium', 'hard'];
 
       for (const difficulty of difficulties) {
         const choice = await ai.makeChoice(initialState, difficulty);
@@ -287,7 +287,7 @@ describe('RockPaperScissorsAI', () => {
     });
 
     it('should handle incomplete rounds', () => {
-      let state = initialState;
+  const state = initialState;
       // Only player1 has made a choice in current round
       state.rounds[0] = { player1Choice: 'rock' };
 
@@ -307,7 +307,7 @@ describe('RockPaperScissorsAI', () => {
 
     it('should be consistent with same game state', async () => {
       // Create a deterministic scenario
-      let state = initialState;
+  let state = initialState;
       state = game.applyMove(state, { choice: 'rock' }, 'player1');
       state = game.applyMove(state, { choice: 'paper' }, 'player2');
       state = game.applyMove(state, { choice: 'rock' }, 'player1');

mcp-server/src/ai/rock-paper-scissors-ai.ts

@@ -1,4 +1,4 @@
-import type { RPSGameState, RPSMove, RPSChoice, Difficulty } from '@turn-based-mcp/shared'
+import type { RPSGameState, RPSChoice, Difficulty } from '@turn-based-mcp/shared'
 import { RockPaperScissorsGame } from '@turn-based-mcp/shared'
 
 export type Strategy = 'random' | 'adaptive' | 'pattern'
@@ -195,7 +195,7 @@ export class RockPaperScissorsAI {
    * Rebuilds the opponent history array from the game state's completed rounds.
    * Assumes player1 is the human opponent whose patterns we want to learn.
    */
-  private updateOpponentHistory(gameState: RPSGameState) {
+  private updateOpponentHistory(gameState: RPSGameState): void {
     // Extract opponent moves from completed rounds
     this.opponentHistory = []
 

mcp-server/src/ai/rock-paper-scissors-security.test.ts

@@ -1,10 +1,8 @@
 import { RockPaperScissorsAI } from './rock-paper-scissors-ai'
-import { RockPaperScissorsGame } from '@turn-based-mcp/shared'
 import type { RPSGameState, RPSChoice } from '@turn-based-mcp/shared'
 
 describe('RockPaperScissorsAI - Current Move Security', () => {
   let ai: RockPaperScissorsAI
-  let game: RockPaperScissorsGame
 
   const createMockGameState = (
     rounds: Array<{
@@ -31,7 +29,7 @@ describe('RockPaperScissorsAI - Current Move Security', () => {
 
   beforeEach(() => {
     ai = new RockPaperScissorsAI()
-    game = new RockPaperScissorsGame()
+  // separate game instance not required for these security-focused tests
   })
 
   describe('Current Round Security Tests', () => {

mcp-server/src/ai/tic-tac-toe-ai.test.ts

@@ -1,4 +1,4 @@
-import { TicTacToeAI, type Difficulty } from './tic-tac-toe-ai.js';
+import { TicTacToeAI } from './tic-tac-toe-ai.js';
 import type { TicTacToeGameState, Player } from '@turn-based-mcp/shared';
 import { TicTacToeGame } from '@turn-based-mcp/shared';
 
@@ -35,7 +35,7 @@ describe('TicTacToeAI', () => {
 
       it('should choose from available moves only', async () => {
         // Fill most of the board
-        let state = initialState;
+          const state = initialState;
         state.board = [
           ['X', 'O', 'X'],
           ['O', 'X', 'O'],
@@ -61,7 +61,7 @@ describe('TicTacToeAI', () => {
 
     describe('medium difficulty', () => {
       it('should win when possible', async () => {
-        let state = initialState;
+          const state = initialState;
         // Set up a winning scenario for AI
         state.board = [
           ['O', 'O', null],
@@ -74,7 +74,7 @@ describe('TicTacToeAI', () => {
       });
 
       it('should block opponent from winning', async () => {
-        let state = initialState;
+          const state = initialState;
         // Set up scenario where player can win
         state.board = [
           ['X', 'X', null],
@@ -101,7 +101,7 @@ describe('TicTacToeAI', () => {
       });
 
       it('should prefer center when available', async () => {
-        let state = initialState;
+          const state = initialState;
         state.board = [
           ['X', null, null],
           [null, null, null],
@@ -113,7 +113,7 @@ describe('TicTacToeAI', () => {
       });
 
       it('should choose corners when center is taken', async () => {
-        let state = initialState;
+          const state = initialState;
         state.board = [
           [null, null, null],
           [null, 'X', null],
@@ -130,7 +130,7 @@ describe('TicTacToeAI', () => {
       });
 
       it('should prioritize winning over blocking', async () => {
-        let state = initialState;
+          const state = initialState;
         // Both AI and player can win
         state.board = [
           ['O', 'O', null], // AI can win here
@@ -145,7 +145,7 @@ describe('TicTacToeAI', () => {
 
     describe('hard difficulty', () => {
       it('should play optimally using minimax', async () => {
-        let state = initialState;
+          const state = initialState;
         // Classic opening: AI should respond optimally to corner play
         state.board = [
           ['X', null, null],
@@ -158,7 +158,7 @@ describe('TicTacToeAI', () => {
       });
 
       it('should never lose from a winning position', async () => {
-        let state = initialState;
+          const state = initialState;
         // AI is in a winning position
         state.board = [
           ['O', 'X', null],
@@ -171,7 +171,7 @@ describe('TicTacToeAI', () => {
       });
 
       it('should force a draw from losing position', async () => {
-        let state = initialState;
+          const state = initialState;
         // Player has advantage but AI should force draw
         state.board = [
           ['X', null, null],
@@ -206,7 +206,7 @@ describe('TicTacToeAI', () => {
     });
 
     it('should default to easy difficulty for invalid difficulty', async () => {
-      const move = await ai.makeMove(initialState, 'invalid' as Difficulty);
+  const move = await ai.makeMove(initialState, 'invalid' as any);
       expect(game.validateMove(initialState, move, 'ai')).toBe(true);
     });
   });
@@ -223,7 +223,7 @@ describe('TicTacToeAI', () => {
     });
 
     it('should detect winning opportunities', () => {
-      let state = initialState;
+        const state = initialState;
       state.board = [
         ['O', 'O', null],
         ['X', null, null],
@@ -235,7 +235,7 @@ describe('TicTacToeAI', () => {
     });
 
     it('should detect player threats', () => {
-      let state = initialState;
+        const state = initialState;
       state.board = [
         ['X', 'X', null],
         ['O', null, null],
@@ -250,7 +250,7 @@ describe('TicTacToeAI', () => {
     });
 
     it('should analyze board state correctly', () => {
-      let state = initialState;
+        const state = initialState;
       state.board = [
         ['X', null, 'O'],
         [null, 'X', null],  // Center has X
@@ -264,7 +264,7 @@ describe('TicTacToeAI', () => {
     });
 
     it('should handle game-ending scenarios', () => {
-      let state = initialState;
+        const state = initialState;
       state.board = [
         ['X', 'X', 'X'],
         ['O', 'O', null],
@@ -280,7 +280,7 @@ describe('TicTacToeAI', () => {
 
   describe('edge cases and robustness', () => {
     it('should handle full board gracefully', async () => {
-      let state = initialState;
+        const state = initialState;
       state.board = [
         ['X', 'O', 'X'],
         ['O', 'X', 'O'],
@@ -304,7 +304,7 @@ describe('TicTacToeAI', () => {
     });
 
     it('should maintain consistent behavior across difficulties', async () => {
-      const difficulties: Difficulty[] = ['easy', 'medium', 'hard'];
+  const difficulties: any[] = ['easy', 'medium', 'hard'];
 
       for (const difficulty of difficulties) {
         const move = await ai.makeMove(initialState, difficulty);
@@ -313,7 +313,7 @@ describe('TicTacToeAI', () => {
     });
 
     it('should handle near-end game scenarios', async () => {
-      let state = initialState;
+        const state = initialState;
       // Only one move left
       state.board = [
         ['X', 'O', 'X'],

mcp-server/src/ai/tic-tac-toe-ai.ts

@@ -1,4 +1,4 @@
-import type { TicTacToeGameState, TicTacToeMove, Difficulty } from '@turn-based-mcp/shared'
+import type { TicTacToeGameState, TicTacToeMove, Difficulty, PlayerId } from '@turn-based-mcp/shared'
 import { TicTacToeGame } from '@turn-based-mcp/shared'
 
 /**
@@ -193,11 +193,11 @@ export class TicTacToeAI {
    * Tests each valid move to see if it results in an immediate win.
    * Used for both finding AI wins and blocking opponent wins.
    */
-  private findWinningMove(gameState: TicTacToeGameState, playerId: string): TicTacToeMove | null {
-    const validMoves = this.game.getValidMoves(gameState, playerId as any)
+  private findWinningMove(gameState: TicTacToeGameState, playerId: PlayerId): TicTacToeMove | null {
+    const validMoves = this.game.getValidMoves(gameState, playerId)
 
     for (const move of validMoves) {
-      const tempGameState = this.game.applyMove(gameState, move, playerId as any)
+  const tempGameState = this.game.applyMove(gameState, move, playerId)
       const result = this.game.checkGameEnd(tempGameState)
 
       if (result && result.winner === playerId) {