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by rad-security

list_http_requests

Analyze HTTP request insights in Kubernetes environments with filtering by method, path, workloads, and PII detection to identify security patterns and potential risks.

Instructions

List HTTP requests insights with optional filtering by method, path, source and destination workloads, and PII detection

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersNoFilter string for filtering results. Filter options: method, path, cluster_id, scheme, source_workload_name, source_workload_namespace, destination_workload_name, destination_workload_namespace,has_pii. Example: 'method:GET,path:/api/v1/users,scheme:https,source_workload_name:my-workload,source_workload_namespace:my-namespace,destination_workload_name:my-workload,destination_workload_namespace:my-namespace,has_pii:true'
offsetNoOffset to start the list from
limitNoLimit the number of items in the list
qNoQuery to filter the list of HTTP requests

Implementation Reference

  • Handler function that executes the list_http_requests tool. Validates input params using the schema and makes an API request to fetch HTTP requests insights.
    export async function listHttpRequests(
      client: RadSecurityClient,
      params: z.infer<typeof listHttpRequestsSchema>
    ): Promise<any> {
      const validatedParams = listHttpRequestsSchema.parse(params);
      const response = await client.makeRequest(
        `/accounts/${client.getAccountId()}/container_runtime_insights/http_requests`,
        validatedParams
      );
      return response;
    }
  • Zod input schema defining parameters for the list_http_requests tool: filters, offset, limit, q.
    export const listHttpRequestsSchema = z.object({
      filters: z.string().optional().describe("Filter string for filtering results. Filter options: method, path, cluster_id, " +
        "scheme, source_workload_name, source_workload_namespace, destination_workload_name, destination_workload_namespace," +
        "has_pii. Example: 'method:GET,path:/api/v1/users,scheme:https,source_workload_name:my-workload,source_workload_namespace:my-namespace,destination_workload_name:my-workload,destination_workload_namespace:my-namespace,has_pii:true'"),
      offset: z.number().optional().describe("Offset to start the list from"),
      limit: z.number().optional().default(20).describe("Limit the number of items in the list"),
      q: z.string().optional().describe("Query to filter the list of HTTP requests"),
    });
  • src/index.ts:388-394 (registration)
    Tool registration in the listTools handler, defining the tool name, description, and input schema.
      name: "list_http_requests",
      description:
        "List HTTP requests insights with optional filtering by method, path, source and destination workloads, and PII detection",
      inputSchema: zodToJsonSchema(
        runtimeNetwork.listHttpRequestsSchema
      ),
    },
  • src/index.ts:1179-1191 (registration)
    Tool execution handler in the callTool request handler switch statement, parses args and calls the handler function.
    case "list_http_requests": {
      const args = runtimeNetwork.listHttpRequestsSchema.parse(
        request.params.arguments
      );
      const response = await runtimeNetwork.listHttpRequests(
        client,
        args
      );
      return {
        content: [
          { type: "text", text: JSON.stringify(response, null, 2) },
        ],
      };
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'List' implies a read-only operation, the description doesn't address important behavioral aspects like pagination behavior (implied by offset/limit parameters but not explained), rate limits, authentication requirements, error conditions, or what format the insights are returned in. It mentions filtering but doesn't explain how filtering logic works.

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

Conciseness4/5

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

The description is a single, efficient sentence that communicates the core functionality and filtering options. It's appropriately sized for a listing tool, though it could potentially be more front-loaded by starting with the primary purpose before listing filter options. No wasted words or redundant information.

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 tool with 4 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'HTTP requests insights' actually means, what data is returned, how results are structured, or provide any context about the data source or system. The description assumes too much domain knowledge and doesn't compensate for the lack of structured metadata.

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 parameters thoroughly. The description mentions filtering by method, path, source/destination workloads, and PII detection - which aligns with the 'filters' parameter documentation but doesn't add meaningful semantic context beyond what's already in the schema. The baseline of 3 is appropriate when 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 tool's purpose: 'List HTTP requests insights' with optional filtering capabilities. It specifies the resource (HTTP requests insights) and verb (list), but doesn't explicitly differentiate from sibling tools like 'list_network_connections' or 'list_security_findings' which might handle related but different data types.

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?

The description provides no guidance on when to use this tool versus alternatives. It mentions filtering capabilities but doesn't specify use cases, prerequisites, or comparisons with sibling tools like 'list_network_connections' or 'radql_query' that might offer similar functionality. There's no 'when' or 'when not' context provided.

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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