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Scored across 19 tools
Most tools have clearly distinct purposes (search_traces vs search_spans_tool, find_errors vs investigate_error_spike, triage_trace vs correlate_trace). A few clusters are close-overlap: get_llm_usage / compare_time_windows / investigate_cost_spike and get_llm_model_stats / get_llm_usage all touch token/cost aggregation, but descriptions differentiate them. Boundaries are mostly sharp with one or two spots where an agent must read carefully.
Overwhelmingly consistent snake_case verb_noun pattern (list_services, get_trace, search_traces, investigate_cost_spike). The notable deviation is the redundant `_tool` suffix on search_spans_tool and list_llm_tools_tool, which breaks the otherwise clean convention. Minor but visible inconsistency.
19 tools is borderline heavy (16-25 range) for a trace-analysis server. Most earn their place, but the usage/cost-analysis cluster (get_llm_usage, compare_time_windows, investigate_cost_spike, get_llm_expensive_traces) could arguably be consolidated. Slightly over the ideal scope.
The surface covers listing, search, detail retrieval, triage, cross-backend correlation, error analysis, LLM usage/cost/latency, sessions, prompt versions, and span-level tools — a rich read/analysis lifecycle. As a read-only observability server, CRUD gaps aren't expected; minor gaps exist (no span-by-id fetch, no annotation/feedback writing) but agents can work around them.
