evaluate_forecast

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

With no annotations, the description carries the full burden. It clearly explains the process (hold out days, forecast from history, score with MASE) and notes that MASE is scale-free and comparable. It does not explicitly state no side effects or required permissions, but the analytical nature is clear.

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 a single, front-loaded sentence that efficiently communicates the purpose, process, and key metric property. No superfluous words.

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?

Despite the tool's relative complexity (backtesting, forecasting, scoring), the description covers the essential aspects. An output schema exists, so return values need not be described. The mention of MASE's scale-free nature addresses comparability. The description is complete for an agent to understand when and how to use the tool.

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 100%, so baseline is 3. The description adds minimal meaning beyond the schema: it restates that test_size is the number of recent days to hold out and that unique_id is a SKU identifier, but the schema already provides these details with defaults and types.

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 ('SKU's forecast'), clearly defining the action. It distinguishes from sibling tools like forecast_series (which generates forecasts) and explain_forecast (which explains), as evaluate_forecast is about validation and scoring.

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 implies when to use (when you need to validate forecast accuracy for a SKU) but does not explicitly state when not to use it or suggest alternatives. No mention of prerequisites or comparison with siblings like classify_demand_pattern or recommend_replenishment.

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