forecast_multi_horizon

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

No annotations are provided, so the description must disclose behavioral traits. It explains the output (probability, interval, SHAP, consistency flag) but does not mention side effects, permissions, rate limits, or data freshness. It adequately describes what the tool returns but lacks broader behavioral context.

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 concise with two sentences, no redundant information. It front-loads the core purpose and then details the output components, making it easy to scan.

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 simplicity of the tool (1 parameter, no output schema, no annotations), the description covers the key aspects: horizons, output components, and consistency flag. Minor omissions include output format and any constraints on usage, but overall it is sufficient for 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?

The schema already provides a clear description for the single parameter (country_code). The tool description does not add any additional meaning or constraints beyond the schema, so it meets the baseline for 100% schema coverage.

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 clearly states it provides multi-horizon shutdown forecasts for a country, listing specific horizons (1d, 7d, 30d) and output components (probability, interval, SHAP contributions). This distinguishes it from sibling tools like forecast_7day_shap or forecast_hourly.

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 usage for multi-horizon forecasting but does not explicitly state when to use it over alternatives. It mentions a consistency block for non-monotonic horizons, which gives a hint, but lacks clear when-to-use or when-not-to-use guidance relative to sibling tools.

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