backtest_signal

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

With no annotations, the description fully carries the burden of behavioral disclosure. It clearly explains the bar-by-bar walkthrough using the live evaluation engine, ensuring production matching, and lists key output metrics. Minor omission: no mention of data prerequisites or performance implications.

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?

Two sentences that front-load the purpose and efficiently cover the evaluation method and output. No redundancy, every sentence adds value.

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?

Given the presence of an output schema (returns trade list and summary metrics), the description appropriately lists specific metrics (total return, win rate, Sharpe, max drawdown). Lacks mention of error states or required data availability, but overall covers the essential context for correct tool 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 coverage is 100%, and parameter descriptions in the schema are adequate. The tool description adds overarching context (bar-by-bar engine) but does not enhance individual parameter meanings beyond what the schema already provides.

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 uses a specific verb ('backtest') and resource ('saved signal definition'), explicitly contrasting with sibling tools like 'backtest_portfolio' or 'run_backtest' by emphasizing bar-by-bar live engine simulation for signal fidelity.

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?

Implies usage context (requires a saved signal ID and date range) but does not explicitly state when to prefer this tool over alternatives like 'backtest_portfolio' or 'walk_forward_analysis'. No 'when not to use' guidance is provided.

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