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Scored across 9 tools
Each tool has a clearly distinct purpose with no overlap. The tools are organized into two main categories: ARMS application monitoring tools (arms_generate_trace_query, arms_search_apps) and SLS log service tools (the remaining seven), with each addressing specific operations like query generation, search, description, diagnosis, execution, time retrieval, listing, and translation. The descriptions clearly differentiate their functions, preventing misselection.
Tool names follow a highly consistent pattern throughout. All names use snake_case and a clear prefix-action-resource structure (e.g., arms_search_apps, sls_execute_query). The prefixes 'arms_' and 'sls_' denote the service domain, followed by a verb (e.g., generate, search, describe, diagnose) and a noun (e.g., trace_query, apps, logstore), making the set predictable and readable.
With 9 tools, the count is well-scoped for an observability server covering ARMS and SLS services. Each tool earns its place by addressing core operations like listing resources, executing queries, generating queries from natural language, and diagnosing issues. This provides comprehensive coverage without being overwhelming or too sparse for the domain.
The tool set offers complete coverage for the observability domain, including CRUD-like operations for logs and traces. It supports listing projects and logstores, describing structures, executing and diagnosing queries, translating natural language, and managing ARMS applications. There are no obvious gaps; tools like sls_get_current_time and sls_diagnose_query add utility for time handling and error analysis, ensuring agents can handle full workflows without dead ends.