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quick_scan

Scan log content to detect errors and identify issues for real-time monitoring and debugging.

Instructions

⚡ Ultra-fast log scan for real-time monitoring (< 1 second)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
logTextYesLog content for quick error detection

Implementation Reference

  • MCP tool handler for 'quick_scan' that validates input, calls rapidDebugger.quickScan, and formats the MCPToolResult response.
    private async handleQuickScan(args: any): Promise<MCPToolResult> {
      const { logText } = args;
    
      if (!logText || typeof logText !== 'string') {
        throw new Error('logText is required and must be a string');
      }
    
      const scanResult = await this.rapidDebugger.quickScan(logText);
    
      return {
        success: true,
        data: {
          ...scanResult,
          message: `⚡ Quick scan completed in ${scanResult.time}ms`
        },
        metadata: {
          processedAt: new Date(),
          scanMode: 'quick'
        }
      };
    }
  • Input schema definition for the 'quick_scan' tool, specifying logText as required string.
    inputSchema: {
      type: 'object',
      properties: {
        logText: {
          type: 'string',
          description: 'Log content for quick error detection'
        }
      },
      required: ['logText']
    }
  • src/server.ts:64-77 (registration)
    Registration of the 'quick_scan' tool in the ListToolsRequestHandler response.
    {
      name: 'quick_scan',
      description: '⚡ Ultra-fast log scan for real-time monitoring (< 1 second)',
      inputSchema: {
        type: 'object',
        properties: {
          logText: {
            type: 'string',
            description: 'Log content for quick error detection'
          }
        },
        required: ['logText']
      }
    },
  • Core implementation of quickScan logic: counts errors, detects critical issues, measures execution time.
    async quickScan(logContent: string): Promise<{errors: number, critical: boolean, time: number}> {
      const start = Date.now();
      const errors = LogUtils.extractErrorPatterns(logContent);
      const critical = logContent.toLowerCase().includes('fatal') || 
                      logContent.toLowerCase().includes('critical') ||
                      errors.length > 5;
      
      return {
        errors: errors.length,
        critical,
        time: Date.now() - start
      };
    }
  • src/server.ts:177-179 (registration)
    Dispatch registration in the CallToolRequestHandler switch statement.
    case 'quick_scan':
      result = await this.handleQuickScan(args);
      break;
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden. It mentions performance (< 1 second) which is useful behavioral context, but lacks critical details: whether it's read-only or mutative, error handling, rate limits, or what 'scan' entails (e.g., pattern matching, simple keyword search). The speed claim is helpful but insufficient for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads key information: speed, purpose, and performance metric. Every word earns its place with no redundancy or fluff, making it optimally concise for its purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 1 parameter with full schema coverage and no output schema, the description provides adequate context for a simple scanning tool. However, with no annotations and behavioral gaps (e.g., unspecified return format, error handling), it's minimally complete but leaves the agent guessing about operational details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the single parameter 'logText' as 'Log content for quick error detection'. The description adds no additional parameter semantics beyond what's in the schema, maintaining the baseline score of 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function as 'Ultra-fast log scan for real-time monitoring' with a specific performance metric (< 1 second). It distinguishes from siblings like 'analyze_log' by emphasizing speed rather than depth, but doesn't explicitly contrast with all alternatives like 'get_recent_errors' or 'rapid_debug'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for 'real-time monitoring' and 'quick error detection' (via parameter description), suggesting when speed is critical. However, it doesn't provide explicit guidance on when to choose this over siblings like 'analyze_log' (depth vs speed) or 'get_recent_errors' (historical vs current).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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