Hi-AI

Instructions

Implementation Reference

• src/tools/prompt/enhancePromptGemini.ts:43-119 (handler)

  Main handler function implementing the tool logic: parses args, applies Gemini-specific prompting strategies (few-shot examples, output format spec, context placement, decomposition, parameters), generates enhancements, combines into enhanced prompt, and formats structured output.

  export async function enhancePromptGemini(args: {
    prompt: string;
    agent_role?: string;
    strategies?: string[];
  }): Promise<ToolResult> {
    const { prompt, agent_role, strategies } = args;
  
    const allStrategies = ['few-shot', 'output-format', 'context-placement', 'decomposition', 'parameters'];
    const strategiesToApply = strategies && strategies.length > 0 ? strategies : allStrategies;
  
    const enhancements: PromptEnhancement[] = [];
  
    // 1. Few-Shot Examples
    if (strategiesToApply.includes('few-shot')) {
      enhancements.push({
        strategy: 'Add Few-Shot Examples',
        description: 'Add 2-3 high-quality examples to guide the model to learn patterns',
        applied: addFewShotExamples(prompt, agent_role),
        improvement: 'Improve consistency by clarifying format, expression, and scope'
      });
    }
  
    // 2. Output Format Specification
    if (strategiesToApply.includes('output-format')) {
      enhancements.push({
        strategy: 'Output Format Specification',
        description: 'Specify structured format with XML tags or markdown headers',
        applied: specifyOutputFormat(prompt, agent_role),
        improvement: 'Clarify desired response structure for easier parsing'
      });
    }
  
    // 3. Context Placement
    if (strategiesToApply.includes('context-placement')) {
      enhancements.push({
        strategy: 'Context Placement Optimization',
        description: 'Place long context before specific requests (Gemini 3 optimization)',
        applied: optimizeContextPlacement(prompt),
        improvement: 'Help model utilize context more effectively'
      });
    }
  
    // 4. Prompt Decomposition
    if (strategiesToApply.includes('decomposition')) {
      enhancements.push({
        strategy: 'Prompt Decomposition',
        description: 'Decompose complex tasks into multiple steps and chain them',
        applied: decomposePrompt(prompt, agent_role),
        improvement: 'Improve output quality at each step, easier debugging'
      });
    }
  
    // 5. Parameter Tuning Suggestions
    if (strategiesToApply.includes('parameters')) {
      enhancements.push({
        strategy: 'Parameter Tuning Suggestions',
        description: 'Suggest optimal values for Temperature, Top-K, Top-P, Max Tokens',
        applied: suggestParameters(prompt, agent_role),
        improvement: 'Optimize model behavior for task type'
      });
    }
  
    const result = {
      original_prompt: prompt,
      agent_role: agent_role || 'Generic Agent',
      strategies_applied: strategiesToApply,
      enhancements,
      enhanced_prompt: combineEnhancements(prompt, enhancements),
      summary: generateSummary(enhancements)
    };
  
    const output = formatOutput(result);
  
    return {
      content: [{ type: 'text', text: output }]
    };
  }

• src/tools/prompt/enhancePromptGemini.ts:5-34 (schema)

  ToolDefinition schema defining name 'enhance_prompt_gemini', description, input schema with prompt (required), optional agent_role and strategies, and annotations.

  export const enhancePromptGeminiDefinition: ToolDefinition = {
    name: 'enhance_prompt_gemini',
    description: 'prompt improvement|gemini strategies|quality improvement|prompt enhancement|gemini strategies|quality improvement - Enhance prompts using Gemini API prompting strategies (Few-Shot, Output Format, Context)',
    inputSchema: {
      type: 'object',
      properties: {
        prompt: {
          type: 'string',
          description: 'The original prompt to enhance'
        },
        agent_role: {
          type: 'string',
          description: 'The role of the agent that will receive this prompt (e.g., "Specification Agent", "Planning Agent")'
        },
        strategies: {
          type: 'array',
          items: {
            type: 'string',
            enum: ['few-shot', 'output-format', 'context-placement', 'decomposition', 'parameters']
          },
          description: 'Specific Gemini strategies to apply. If not provided, all strategies will be applied.'
        }
      },
      required: ['prompt']
    },
    annotations: {
      title: 'Enhance Prompt (Gemini Strategies)',
      audience: ['user', 'assistant']
    }
  };

• src/index.ts:104-160 (registration)

  Registration of the tool definition in the main tools array used for listing tools via MCP protocol.

  const tools: ToolDefinition[] = [
    // Time Utility Tools
    getCurrentTimeDefinition,
  
    // Semantic Code Analysis Tools (Serena-inspired)
    findSymbolDefinition,
    findReferencesDefinition,
  
    // Sequential Thinking Tools
    createThinkingChainDefinition,
    analyzeProblemDefinition,
    stepByStepAnalysisDefinition,
    breakDownProblemDefinition,
    thinkAloudProcessDefinition,
    formatAsPlanDefinition,
  
    // Browser Development Tools
    monitorConsoleLogsDefinition,
    inspectNetworkRequestsDefinition,
  
    // Memory Management Tools
    saveMemoryDefinition,
    recallMemoryDefinition,
    listMemoriesDefinition,
    deleteMemoryDefinition,
    searchMemoriesDefinition,
    updateMemoryDefinition,
    autoSaveContextDefinition,
    restoreSessionContextDefinition,
    prioritizeMemoryDefinition,
    startSessionDefinition,
  
    // Convention Tools
    getCodingGuideDefinition,
    applyQualityRulesDefinition,
    validateCodeQualityDefinition,
    analyzeComplexityDefinition,
    checkCouplingCohesionDefinition,
    suggestImprovementsDefinition,
  
    // Planning Tools
    generatePrdDefinition,
    createUserStoriesDefinition,
    analyzeRequirementsDefinition,
    featureRoadmapDefinition,
  
    // Prompt Enhancement Tools
    enhancePromptDefinition,
    analyzePromptDefinition,
    enhancePromptGeminiDefinition,
  
    // Reasoning Tools
    applyReasoningFrameworkDefinition,
  
    // UI Preview Tools
    previewUiAsciiDefinition
  ];

• src/index.ts:686-687 (registration)

  Dispatch registration in the executeToolCall switch statement, mapping tool name to handler invocation.

  case 'enhance_prompt_gemini':
    return await enhancePromptGemini(args as any) as CallToolResult;

• src/tools/prompt/enhancePromptGemini.ts:122-374 (helper)

  Supporting helper functions for each strategy and output formatting.

  function addFewShotExamples(prompt: string, agent_role?: string): string {
    const examples = {
      'Specification Agent': `
  **Example 1: Push Notification Settings**
  Input: "Let me turn on/off notifications for comments, likes, and follows"
  Output:
  - Notification types: 6 (comments, likes, follows, announcements, events, marketing)
  - Setting method: ON/OFF toggle
  - Design reference: iOS Settings > Notifications
  - Tech stack: FCM (currently in use)
  
  **Example 2: User Profile Editing**
  Input: "Let me change my profile picture and bio"
  Output:
  - Editable fields: Profile picture, bio, display name
  - Validation: Image size < 5MB, bio < 500 chars
  - UI pattern: Inline editing (not modal)
  - Save method: Auto-save (debounce 500ms)`,
  
      'Planning Agent': `
  **Example 1: API Endpoint Addition**
  Input: "User follow/unfollow feature"
  Output:
  - Phase 1: Backend (8 hours)
    - DB schema (follows table)
    - API endpoints (POST /follows, DELETE /follows/:id)
    - Business logic (duplicate prevention, self-follow prevention)
  - Phase 2: Frontend (6 hours)
    - Follow button component
    - Followers/following list
  - Cost impact: +$0 (using existing infrastructure)
  
  **Example 2: Real-time Notifications**
  Input: "Real-time notification when someone comments"
  Output:
  - Phase 1: WebSocket server setup (12 hours)
  - Phase 2: Client subscription logic (8 hours)
  - Phase 3: Notification UI (6 hours)
  - Cost impact: +$20/month (Redis Pub/Sub)`
    };
  
    return examples[agent_role as keyof typeof examples] || `
  **Add Few-Shot examples matching the task type**:
  - Example 1: [Specific input] → [Clear output]
  - Example 2: [Different input format] → [Consistent output format]
  - Example 3: [Edge case] → [How to handle]
  
  **Guidelines**:
  - 2-3 examples (avoid overfitting)
  - Include diverse scenarios
  - Maintain consistent output format`;
  }
  
  function specifyOutputFormat(prompt: string, agent_role?: string): string {
    const formats = {
      'Specification Agent': `
  **Output Format (Markdown + YAML frontmatter)**:
  
  \`\`\`markdown
  ---
  title: [Feature Name]
  priority: [HIGH/MEDIUM/LOW]
  created: [Date]
  ---
  
  # SPEC: [Feature Name]
  
  ## REQ-001: [Requirement Title]
  **WHEN** [Condition]
  **THEN** [Result]
  
  ### Acceptance Criteria
  - [ ] [Criterion 1]
  - [ ] [Criterion 2]
  \`\`\`
  
  **Response prefix**: Start with "# SPEC: " to guide model to complete in correct format`,
  
      'Planning Agent': `
  **Output Format (Structured Markdown)**:
  
  \`\`\`markdown
  # PLAN: [Feature Name]
  
  ## Architecture
  - Backend: [Tech Stack]
  - Frontend: [Tech Stack]
  - Database: [Schema Changes]
  
  ## Timeline
  | Phase | Tasks | Duration |
  |-------|-------|----------|
  | 1     | ...   | 8h       |
  
  ## Cost Analysis
  - Infrastructure: +$X/month
  - Third-party: +$Y/month
  - Total: +$Z/month
  \`\`\`
  
  **Response prefix**: Start with "# PLAN: "`
    };
  
    return formats[agent_role as keyof typeof formats] || `
  **Output Format Specification**:
  - Separate sections with markdown headers (##, ###)
  - Use tables, bullet points, checkboxes
  - Optionally label semantic components with XML tags
    e.g.: <analysis>...</analysis>, <recommendation>...</recommendation>
  - Use response prefix to guide completion
    e.g.: Starting with "Analysis result: " makes model complete with analysis content`;
  }
  
  function optimizeContextPlacement(prompt: string): string {
    return `
  **Context Placement Optimization (Gemini 3 Recommended)**:
  
  1. **Place long context first**:
  \`\`\`
  [Tech stack info (CLAUDE.md content)]
  [Existing codebase structure]
  [Related SPEC/PLAN documents]
  
  --- Specific request below ---
  
  [User's specific question or task]
  \`\`\`
  
  2. **Structure context**:
  - Group by category (tech stack, architecture, business logic)
  - Emphasize important constraints repeatedly
  - Label clearly for reference
  
  3. **Place explicit instructions**:
  - Specific task instructions after context
  - Step-by-step guidelines (1, 2, 3...)
  - Output format examples`;
  }
  
  function decomposePrompt(prompt: string, agent_role?: string): string {
    const isComplex = prompt.length > 200 || prompt.includes('and') || prompt.includes('also') || prompt.includes('and');
  
    if (!isComplex) {
      return '**Prompt decomposition not needed**: Simple task, single prompt is sufficient.';
    }
  
    return `
  **Prompt Decomposition (Sequential Chain)**:
  
  **Step 1: Information Gathering**
  \`\`\`
  Prompt: Identify required information for "${prompt.slice(0, 100)}..."
  Output: List of required tech stack, constraints, prerequisite tasks
  \`\`\`
  
  **Step 2: Analysis and Planning**
  \`\`\`
  Prompt: Create implementation plan based on Step 1 information.
  Input: [Step 1 output]
  Output: Phase-by-phase tasks, timeline, risks
  \`\`\`
  
  **Step 3: Detailed Task Generation**
  \`\`\`
  Prompt: Decompose Step 2 plan into actionable tasks.
  Input: [Step 2 output]
  Output: Task list (with dependencies)
  \`\`\`
  
  **Benefits**:
  - Improved output quality at each step
  - Intermediate validation possible
  - Re-run only specific step on error`;
  }
  
  function suggestParameters(prompt: string, agent_role?: string): string {
    const isCreative = prompt.includes('design') || prompt.includes('idea') || prompt.includes('suggest');
    const isDeterministic = prompt.includes('analyze') || prompt.includes('calculate') || prompt.includes('verify');
  
    let temperature = 1.0; // Gemini 3 default
    let topP = 0.95;
    let topK = 40;
  
    if (isCreative) {
      temperature = 1.0;
      topP = 0.95;
    } else if (isDeterministic) {
      temperature = 0.2;
      topP = 0.8;
      topK = 20;
    }
  
    return `
  **Recommended Parameters** (Based on task characteristics):
  
  - **Temperature**: ${temperature}
    ${temperature > 0.7 ? 'Suitable for creative tasks (explore diverse options)' : 'Suitable for deterministic tasks (consistent output)'}
  
  - **Top-P**: ${topP}
    Select tokens up to ${topP * 100}% cumulative probability
  
  - **Top-K**: ${topK}
    Consider only top ${topK} tokens
  
  - **Max Output Tokens**: ${agent_role === 'Specification Agent' ? '4000 (detailed document)' : '2000 (general)'}
  
  - **Stop Sequences**: ["---END---", "\`\`\`"] (optional)
  
  **Note**:
  - Gemini 3 recommends keeping temperature at default 1.0
  - Avoid deviating significantly from defaults to prevent unexpected behavior`;
  }
  
  function combineEnhancements(prompt: string, enhancements: PromptEnhancement[]): string {
    let enhanced = `# Enhanced Prompt\n\n`;
    enhanced += `## Original Request\n${prompt}\n\n`;
    enhanced += `---\n\n`;
  
    enhancements.forEach((e, i) => {
      enhanced += `## Enhancement ${i + 1}: ${e.strategy}\n\n`;
      enhanced += `${e.applied}\n\n`;
    });
  
    return enhanced;
  }
  
  function generateSummary(enhancements: PromptEnhancement[]): string {
    return `Applied ${enhancements.length} Gemini prompting strategies to improve prompt quality:
  ${enhancements.map(e => `- ${e.strategy}: ${e.improvement}`).join('\n')}`;
  }
  
  function formatOutput(result: any): string {
    let output = `# Gemini Prompt Enhancement\n\n`;
    output += `**Original Prompt**: ${result.original_prompt}\n`;
    output += `**Target Agent**: ${result.agent_role}\n`;
    output += `**Applied Strategies**: ${result.strategies_applied.join(', ')}\n\n`;
    output += `---\n\n`;
  
    result.enhancements.forEach((e: PromptEnhancement, i: number) => {
      output += `## ${i + 1}. ${e.strategy}\n\n`;
      output += `**Description**: ${e.description}\n\n`;
      output += `**Applied Content**:\n${e.applied}\n\n`;
      output += `**Improvement Effect**: ${e.improvement}\n\n`;
      output += `---\n\n`;
    });
  
    output += `## Enhanced Prompt\n\n`;
    output += '```markdown\n' + result.enhanced_prompt + '\n```\n\n';
    output += `## Summary\n\n${result.summary}`;
  
    return output;
  }