Save prompt flow

src/extension/extension/vscode-node/contributions.ts

@@ -35,6 +35,7 @@ import { OnboardTerminalTestsContribution } from '../../onboardDebug/vscode-node
 import { DebugCommandsContribution } from '../../prompt/vscode-node/debugCommands';
 import { RenameSuggestionsContrib } from '../../prompt/vscode-node/renameSuggestions';
 import { PromptFileContextContribution } from '../../promptFileContext/vscode-node/promptFileContextService';
+import { PromptSaveCommands } from '../../promptSave/vscode-node/commands';
 import { RelatedFilesProviderContribution } from '../../relatedFiles/vscode-node/relatedFiles.contribution';
 import { ChatReplayContribution } from '../../replay/vscode-node/chatReplayContrib';
 import { SearchPanelCommands } from '../../search/vscode-node/commands';
@@ -108,5 +109,6 @@ export const vscodeNodeChatContributions: IExtensionContributionFactory[] = [
 	asContributionFactory(RelatedFilesProviderContribution),
 	asContributionFactory(BYOKContrib),
 	asContributionFactory(McpSetupCommands),
+	asContributionFactory(PromptSaveCommands),
 	newWorkspaceContribution,
 ];

src/extension/promptSave/common/types.ts

@@ -0,0 +1,49 @@
+/*---------------------------------------------------------------------------------------------
+ *  Copyright (c) Microsoft Corporation. All rights reserved.
+ *  Licensed under the MIT License. See License.txt in the project root for license information.
+ *--------------------------------------------------------------------------------------------*/
+
+/**
+ * Command names for prompt save cross-repository communication
+ */
+export const PROMPT_SAVE_CHECK_COMMAND = 'github.copilot.chat.prompt.save.check';
+export const PROMPT_SAVE_ANALYZE_COMMAND = 'github.copilot.chat.prompt.save.analyze';
+
+/**
+ * Input arguments for conversation analysis
+ */
+export interface IAnalyzeConversationArgs {
+	/**
+	 * Array of conversation turns (user/assistant message pairs)
+	 */
+	readonly turns: Array<{
+		readonly role: 'user' | 'assistant';
+		readonly content: string;
+	}>;
+
+	/**
+	 * Optional: The current user query that triggered the save
+	 */
+	readonly currentQuery?: string;
+}
+
+/**
+ * Output from prompt save analysis
+ */
+export interface IPromptTaskSave {
+	/**
+	 * Suggested filename in kebab-case (without .prompt.md extension)
+	 * Example: "generate-unit-tests"
+	 */
+	readonly title: string;
+
+	/**
+	 * Brief description of the prompt's purpose (1-2 sentences)
+	 */
+	readonly description: string;
+
+	/**
+	 * Generalized prompt text that can be reused for similar tasks
+	 */
+	readonly prompt: string;
+}

src/extension/promptSave/vscode-node/commands.ts

@@ -0,0 +1,151 @@
+/*---------------------------------------------------------------------------------------------
+ *  Copyright (c) Microsoft Corporation. All rights reserved.
+ *  Licensed under the MIT License. See License.txt in the project root for license information.
+ *--------------------------------------------------------------------------------------------*/
+
+import * as vscode from 'vscode';
+import { ChatFetchResponseType, ChatLocation } from '../../../platform/chat/common/commonTypes';
+import { IEndpointProvider } from '../../../platform/endpoint/common/endpointProvider';
+import { ILogService } from '../../../platform/log/common/logService';
+import { ITelemetryService } from '../../../platform/telemetry/common/telemetry';
+import { CancellationTokenSource } from '../../../util/vs/base/common/cancellation';
+import { Disposable } from '../../../util/vs/base/common/lifecycle';
+import { IInstantiationService } from '../../../util/vs/platform/instantiation/common/instantiation';
+import { Turn } from '../../prompt/common/conversation';
+import { PromptRenderer } from '../../prompts/node/base/promptRenderer';
+import { IAnalyzeConversationArgs, IPromptTaskSave, PROMPT_SAVE_ANALYZE_COMMAND, PROMPT_SAVE_CHECK_COMMAND } from '../common/types';
+import { PromptSavePrompt } from './promptSavePrompt';
+
+export { PROMPT_SAVE_ANALYZE_COMMAND, PROMPT_SAVE_CHECK_COMMAND } from '../common/types';
+
+export class PromptSaveCommands extends Disposable {
+	constructor(
+		@ITelemetryService private readonly telemetryService: ITelemetryService,
+		@IInstantiationService private readonly instantiationService: IInstantiationService,
+		@IEndpointProvider private readonly endpointProvider: IEndpointProvider,
+		@ILogService private readonly logService: ILogService,
+	) {
+		super();
+
+		this._register(vscode.commands.registerCommand(
+			PROMPT_SAVE_CHECK_COMMAND,
+			() => this.checkAvailability()
+		));
+
+		this._register(vscode.commands.registerCommand(
+			PROMPT_SAVE_ANALYZE_COMMAND,
+			(args: IAnalyzeConversationArgs) => this.analyzeConversation(args)
+		));
+	}
+
+	private async checkAvailability(): Promise<boolean> {
+		// Check if LLM analysis is available
+		try {
+			const models = await vscode.lm.selectChatModels({ family: 'gpt-4o' });
+			return models.length > 0;
+		} catch {
+			return false;
+		}
+	}
+
+	private async analyzeConversation(args: IAnalyzeConversationArgs): Promise<IPromptTaskSave | undefined> {
+		const startTime = Date.now();
+
+		try {
+			// Convert input turns to conversation Turn objects
+			const history: Turn[] = args.turns.map(turn => {
+				return new Turn(
+					undefined,
+					{
+						type: turn.role === 'user' ? 'user' : 'model',
+						message: turn.content
+					}
+				);
+			});
+
+			// Get endpoint for free mini model
+			const endpoint = await this.endpointProvider.getChatEndpoint('gpt-4.1');
+
+			// Render the prompt using PromptRenderer to preserve DI and endpoint wiring
+			const renderer = PromptRenderer.create(
+				this.instantiationService,
+				endpoint,
+				PromptSavePrompt,
+				{ history, currentQuery: args.currentQuery }
+			);
+			const { messages } = await renderer.render();
+
+			// Create cancellation token
+			const cts = new CancellationTokenSource();
+
+			// Send request to LLM
+			const response = await endpoint.makeChatRequest(
+				'prompt-save',
+				messages,
+				undefined,
+				cts.token,
+				ChatLocation.Panel,
+				undefined,
+				undefined,
+				false
+			);
+
+			if (cts.token.isCancellationRequested) {
+				return undefined;
+			}
+
+			if (response.type !== ChatFetchResponseType.Success) {
+				throw new Error(`Chat request failed: ${response.reason}`);
+			}
+
+			// Extract JSON from markdown code block
+			const analysis = this.parseAnalysisResponse(response.value);
+
+			this.telemetryService.sendMSFTTelemetryEvent('chat.promptSave.success', {
+				durationMs: String(Date.now() - startTime),
+				turnCount: String(args.turns.length),
+			});
+
+			return analysis;
+
+		} catch (error) {
+			this.logService.error(`Prompt save analysis failed: ${error instanceof Error ? error.message : String(error)}`);
+
+			this.telemetryService.sendMSFTTelemetryEvent('chat.promptSave.error', {
+				durationMs: String(Date.now() - startTime),
+				error: error instanceof Error ? error.message : String(error),
+			});
+
+			// Return undefined on error - VS Code will fall back to simple save
+			return undefined;
+		}
+	}
+
+	private parseAnalysisResponse(response: string): IPromptTaskSave {
+		// Extract JSON from markdown code block
+		const jsonMatch = response.match(/```json\s*\n([\s\S]*?)\n```/);
+		if (!jsonMatch) {
+			throw new Error('No JSON code block found in response');
+		}
+
+		const parsed = JSON.parse(jsonMatch[1]);
+
+		// Validate required fields
+		if (!parsed.title || !parsed.description || !parsed.prompt) {
+			throw new Error('Invalid analysis response: missing required fields');
+		}
+
+		// Sanitize title to ensure it's valid kebab-case
+		const sanitizedTitle = parsed.title
+			.toLowerCase()
+			.replace(/[^a-z0-9-]/g, '-')
+			.replace(/-+/g, '-')
+			.replace(/^-|-$/g, '');
+
+		return {
+			title: sanitizedTitle,
+			description: parsed.description,
+			prompt: parsed.prompt
+		};
+	}
+}

src/extension/promptSave/vscode-node/promptSavePrompt.tsx

@@ -0,0 +1,95 @@
+/*---------------------------------------------------------------------------------------------
+ *  Copyright (c) Microsoft Corporation. All rights reserved.
+ *  Licensed under the MIT License. See License.txt in the project root for license information.
+ *--------------------------------------------------------------------------------------------*/
+
+import { BasePromptElementProps, PromptElement, SystemMessage, TextChunk, UserMessage } from '@vscode/prompt-tsx';
+import { Turn } from '../../prompt/common/conversation';
+import { InstructionMessage } from '../../prompts/node/base/instructionMessage';
+import { ResponseTranslationRules } from '../../prompts/node/base/responseTranslationRules';
+import { SafetyRules } from '../../prompts/node/base/safetyRules';
+import { Tag } from '../../prompts/node/base/tag';
+import { HistoryWithInstructions } from '../../prompts/node/panel/conversationHistory';
+
+export interface PromptSavePromptProps extends BasePromptElementProps {
+	/**
+	 * The conversation history to analyze
+	 */
+	readonly history: readonly Turn[];
+
+	/**
+	 * Optional: The user's final query that triggered the save
+	 */
+	readonly currentQuery?: string;
+}
+
+/**
+ * Prompt for analyzing chat conversations and extracting reusable prompt tasks.
+ * Used by the /save command to generate prompt file metadata.
+ */
+export class PromptSavePrompt extends PromptElement<PromptSavePromptProps> {
+	override render() {
+		return (
+			<>
+				<SystemMessage priority={1000}>
+					You are an expert at analyzing chat conversations and extracting reusable prompt patterns. Your task is to analyze a conversation between a user and an AI assistant, then create a generalized, reusable prompt task definition.<br />
+					<SafetyRules />
+				</SystemMessage>
+				<HistoryWithInstructions historyPriority={800} passPriority history={this.props.history}>
+					<InstructionMessage priority={1000}>
+						<PromptSaveRules />
+						<ResponseTranslationRules />
+					</InstructionMessage>
+				</HistoryWithInstructions>
+				<UserMessage priority={900}>
+					{this.props.currentQuery && <>Current request: {this.props.currentQuery}<br /><br /></>}
+					Analyze the conversation above and extract a reusable prompt task. Return your analysis as a JSON object wrapped in a markdown code block with triple backticks (```json).<br />
+					<br />
+					The JSON object must match this structure:<br />
+					<Tag name='schema'>
+						<TextChunk breakOnWhitespace>
+							{`{
+  "title": "kebab-case-filename",
+  "description": "Brief description of the prompt's purpose (1-2 sentences)",
+  "prompt": "Generalized prompt text that can be reused for similar tasks"
+}`}
+						</TextChunk>
+					</Tag>
+				</UserMessage>
+			</>
+		);
+	}
+}
+
+class PromptSaveRules extends PromptElement {
+	render() {
+		return (
+			<>
+				Think step by step:<br />
+				1. Review the conversation to identify the user's primary goal or task pattern<br />
+				2. Extract the core intent, removing conversation-specific details (e.g., specific file names, variable names, or project-specific context)<br />
+				3. Identify any recurring instructions, constraints, or requirements that define how the task should be approached<br />
+				4. Generalize the task into a reusable prompt that could apply to similar scenarios<br />
+				5. Create a very concise action-oriented title in kebab-case format that will be used for the slash command (1-3 words, e.g., "generate-unit-tests", "refactor-for-performance", "explain-api-design", etc)<br />
+				6. Write a brief description (1 sentence, max 15 words) explaining the goal of the prompt<br />
+				7. Craft the generalized multi-line markdown text prompt, using placeholders where appropriate (e.g., "the selected code", "the current file", "the specified functionality")<br />
+				<br />
+				Guidelines for creating the prompt:<br />
+				- Focus on the pattern of interaction, not specific implementation details<br />
+				- Preserve important constraints or requirements (e.g., "follow test-driven development", "maintain backward compatibility")<br />
+				- Use general terms rather than specific names (e.g., "the function" instead of "calculateTotal")<br />
+				- Keep the prompt concise but complete (reflecting the complexity of the task) - it should provide clear direction without unnecessary verbosity<br />
+				- The prompt should work as a standalone instruction that captures the essence of the conversation's goal<br />
+				<br />
+				Example good titles:<br />
+				- "review-pr-changes"<br />
+				- "add-error-handling"<br />
+				- "write-api-docs"<br />
+				- "optimize-database-query"<br />
+				- "migrate-to-typescript"<br />
+				<br />
+				Return ONLY the JSON object in a markdown code block. Do not include explanations or additional prose.
+			</>
+		);
+	}
+}