get_analysis_performance

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

With no annotations, the description carries the behavioral burden and does well: it declares read-only status, explains how missing/non-binary/cost data are handled (excluded with counts, not zero-filled), and clarifies the population boundary. It omits details like rate limits or response format, but the key behavioral traits are disclosed.

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

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

Three focused sentences with the core purpose front-loaded and exclusions stated efficiently. Every sentence adds meaningful information and there is no redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only aggregation tool with six optional filters and no output schema, the description gives a solid picture of scope, exclusions, and data handling. Some gaps remain around return shape and how grouping affects output, but overall it is substantially complete for selection and basic invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 17%, and the description does not compensate by explaining the meaning or usage of most parameters. It only indirectly relates to cost_assumptions; bias, symbol, group_by, timeframe, and strategy_version remain dependent on schema enums/names for understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Aggregate'), a clear resource ('live analysis-journal outcomes'), and the exact metrics produced (win rate, gross/net R, MFE/MAE, timing). It also differentiates itself from backtest-related tools by explicitly stating it never mixes Strategy Tester backtests.

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

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

The description provides clear context: use this for live analysis-journal performance aggregation, and it explicitly excludes backtest data. However, it does not name specific sibling alternatives or state direct when-to-use versus other performance and journal tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.