Backtest a simple buying rule on past prices

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

Beyond the read-only/idempotent annotations, the description discloses the cost model assumptions (unleveraged, bid prices, no spread, fees, overnight costs, or dividends) and confirms nothing is placed or prepared. It also previews the return payload (invested, units, average cost, end value, result, worst fall, dca comparison). This is rich behavioral context that annotations alone cannot convey.

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?

The description is front-loaded with the core behavior and the strategy definitions, and every clause carries information. It loses a point for redundancy: 'It places nothing and prepares nothing' is restated at the end as 'Nothing was sent to eToro and nothing was prepared,' and the simulation disclaimer is somewhat padded.

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 complex 8-parameter tool with no output schema, the description fully compensates by enumerating the returned metrics and the dca comparison, and by stating the data source and cost assumptions. Nothing an agent needs to call or interpret this correctly is missing.

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?

With 75% schema coverage the baseline is 3, but the description adds meaning the schema lacks: it explains the strategy enum values (one purchase at start vs. amountUsd every everyDays days) even though the schema's strategy field has no description. It restates amountUsd and everyDays semantics that are already documented, adding marginal value.

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 (backtest/simulate a buying rule) and resource (past prices for a symbol/window), and enumerates the two concrete strategies ('buy_and_hold' and 'dca') with their mechanics. It also implicitly separates itself from real-trade siblings by stressing it 'places nothing and prepares nothing.' An agent can tell exactly what this does without opening the schema.

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?

Usage is implied rather than stated: the reader can infer this is for historical 'what-if' simulation, and the disclaimers ('not a prediction, a recommendation or financial advice') clarify intent. However, no explicit when-to-use or when-not guidance is given, and no sibling alternatives (e.g. etoro_simulate_position) are named or contrasted.

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