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get_project_findings

Retrieve historical analysis findings for .NET and Java projects to detect stateful code patterns and get remediation guidance for stateless architecture migration.

Instructions

Retrieve historical analysis findings for a project

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNameYesName of the project

Implementation Reference

  • The execute function implementing the core logic of the 'get_project_findings' tool: parses input, fetches findings via API client, formats or returns error response.
    async execute(args) {
      try {
        const { projectName } = args;
    
        // Call Statelessor API
        const findings = await apiClient.getProjectFindings(projectName);
    
        if (!findings || findings.length === 0) {
          return {
            content: [
              {
                type: 'text',
                text: `No historical findings found for project: ${projectName}`,
              },
            ],
          };
        }
    
        // Format findings
        return {
          content: [
            {
              type: 'text',
              text: resultFormatter.formatHistoricalFindings(findings, projectName),
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: 'text',
              text: `Error retrieving findings: ${error.message}`,
            },
          ],
          isError: true,
        };
      }
    },
  • Tool definition object containing name, description, and input schema for validation.
    definition: {
      name: 'get_project_findings',
      description: 'Retrieve historical analysis findings for a project',
      inputSchema: {
        type: 'object',
        properties: {
          projectName: {
            type: 'string',
            description: 'Name of the project',
          },
        },
        required: ['projectName'],
      },
    },
  • mcp-server.js:61-62 (registration)
    MCP server switch case that registers and dispatches calls to the getFindingsTool handler.
    case 'get_project_findings':
      return await getFindingsTool.execute(args);
  • Supporting API client method that performs HTTP GET to retrieve project findings from the backend service.
    async getProjectFindings(projectName) {
      const requestId = this.generateRequestId();
      
      try {
        const response = await this.client.get(`/findings/${projectName}`, {
          headers: {
            'X-Request-ID': requestId,
          },
        });
    
        return response.data;
      } catch (error) {
        throw this.handleError(error, 'getProjectFindings');
      }
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action is to 'retrieve' findings, implying a read-only operation, but doesn't specify details like whether it returns all findings or a subset, if there are rate limits, authentication requirements, or error conditions. This leaves gaps in understanding the tool's behavior.

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, clear sentence with no wasted words. It's appropriately sized for a simple tool and front-loaded with the core purpose, making it efficient and easy to parse.

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?

Given no annotations and no output schema, the description is incomplete. It doesn't explain what 'historical analysis findings' entail, the return format, or potential limitations. For a tool with one parameter but lacking structured behavioral data, more context is needed to fully understand its use.

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?

The input schema has 100% description coverage, with the parameter 'projectName' documented as 'Name of the project'. The description doesn't add any extra meaning beyond this, such as format examples or constraints, so it meets the baseline score of 3 where the schema does the heavy lifting.

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 ('retrieve') and resource ('historical analysis findings for a project'), making the purpose understandable. However, it doesn't distinguish this tool from its siblings like 'analyze_git_repository' or 'analyze_local_project', which might also retrieve findings but through different methods or scopes.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites, such as whether the project must have been previously analyzed, or differentiate it from sibling tools like 'explain_remediation' or 'generate_analysis_script', which could be related to findings.

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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