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deifos

FeedbackBasket MCP Server

by deifos

search_feedback

Search for feedback across projects using text queries, filter by category, and limit results to analyze bug reports, feature requests, and reviews.

Instructions

Search for feedback across all accessible projects using text search

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query to find in feedback content
projectIdNoLimit search to specific project
categoryNoFilter search results by category
limitNoMaximum number of results (default: 10)

Implementation Reference

  • MCP server handler for the 'search_feedback' tool: validates input arguments, constructs search options, and delegates execution to the client.searchFeedback method.
    case 'search_feedback':
      if (!args || typeof args !== 'object' || !('query' in args) || typeof args.query !== 'string') {
        throw new Error('Search query is required');
      }
      const searchOptions: {
        projectId?: string;
        category?: 'BUG' | 'FEATURE' | 'REVIEW';
        limit?: number;
      } = {};
      
      if (typeof args.projectId === 'string') {
        searchOptions.projectId = args.projectId;
      }
      if (typeof args.category === 'string' && ['BUG', 'FEATURE', 'REVIEW'].includes(args.category)) {
        searchOptions.category = args.category as 'BUG' | 'FEATURE' | 'REVIEW';
      }
      if (typeof args.limit === 'number') {
        searchOptions.limit = args.limit;
      }
      
      return await client.searchFeedback(args.query, searchOptions);
  • Defines the tool name, description, and input schema for 'search_feedback' returned by the ListTools handler.
    {
      name: 'search_feedback',
      description: 'Search for feedback across all accessible projects using text search',
      inputSchema: {
        type: 'object',
        properties: {
          query: {
            type: 'string',
            description: 'Search query to find in feedback content',
          },
          projectId: {
            type: 'string',
            description: 'Limit search to specific project',
          },
          category: {
            type: 'string',
            enum: ['BUG', 'FEATURE', 'REVIEW'],
            description: 'Filter search results by category',
          },
          limit: {
            type: 'number',
            description: 'Maximum number of results (default: 10)',
            minimum: 1,
            maximum: 50,
          },
        },
        required: ['query'],
        additionalProperties: false,
      },
    },
  • FeedbackBasketClient method that implements the search_feedback tool logic by mapping parameters to a call to the shared getFeedback method with the search query.
    async searchFeedback(query: string, options: {
      projectId?: string;
      category?: 'BUG' | 'FEATURE' | 'REVIEW';
      limit?: number;
    } = {}): Promise<{ content: Array<{ type: string; text: string }> }> {
      return this.getFeedback({
        search: query,
        limit: options.limit || 10,
        ...(options.projectId && { projectId: options.projectId }),
        ...(options.category && { category: options.category }),
      });
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions searching 'across all accessible projects' which hints at scope, but doesn't address important aspects like permissions needed, whether this is a read-only operation, pagination behavior, rate limits, or what the response format looks like. The description is minimal and lacks crucial behavioral context.

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 gets straight to the point with no wasted words. It's appropriately sized for a search tool and front-loads the essential information about what the tool does.

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

Completeness2/5

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

For a search tool with 4 parameters and no output schema, the description is insufficient. It doesn't explain what results look like, how they're structured, or what 'accessible projects' means in practice. With no annotations and no output schema, the description should provide more context about the operation's behavior and results.

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 all 4 parameters thoroughly. The description doesn't add any meaningful parameter semantics beyond what's in the schema - it mentions 'text search' which aligns with the 'query' parameter but provides no additional context about parameter interactions or usage patterns.

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 verb ('Search') and resource ('feedback across all accessible projects'), specifying text-based search functionality. It distinguishes from 'get_feedback' (which likely retrieves specific feedback) and 'get_bug_reports' (which is category-specific), though it doesn't explicitly mention these siblings.

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 text-based searching of feedback, but doesn't explicitly state when to use this tool versus alternatives like 'get_feedback' or 'get_bug_reports'. No guidance is provided about when not to use it or about prerequisites.

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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