btmcp
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TDQS
Scored across 10 tools
Most tools have clearly distinct purposes: listing symbols, profiling series, fetching bars, running/validating backtests, and inspecting runs/trades. The only mild overlap is between describe_series and get_bars, since both return summary statistics about price data, but their different scopes (single-series profile vs. multi-symbol window aggregates) make the boundary clear enough.
All tool names follow a consistent snake_case verb_noun pattern: list_symbols, describe_series, get_bars, validate_strategy, run_backtest, explain_trades, publish_run_report. There is no mixing of camelCase, inconsistent verbs, or vague names like 'process' or 'helper'.
Ten tools is well-scoped for a backtesting/data-analysis server. Each tool covers a distinct stage of the workflow: data discovery, series inspection, bar data, news, strategy validation, backtest execution, run retrieval, comparison, trade explanation, and publishing.
The core backtesting workflow is well covered: explore data, validate a strategy, run it, inspect results, compare runs, explain trades, and publish a report. A minor gap is the lack of a list_runs or similar discovery tool, so an agent without prior run IDs cannot enumerate completed runs, though this is workable since run_backtest returns IDs and links.