query_demand

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

Since no annotations exist, the description carries full burden. It discloses sorting behavior ('Returns hourly rows ordered by time'), the default limit meaning (168 = one week of hours), and the effect of using long ranges (prefer daily_demand). It does not mention pagination behavior, whether the limit is a hard cap or default, or what happens if range exceeds limit, but the essential behavioral traits are adequately covered given the tool's simplicity.

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 at under 70 words, front-loaded with the core purpose and unit (MWh), then uses a structured Args list for parameters, followed by behavior and usage guidance. Every sentence serves a distinct purpose, and there is no redundancy or fluff.

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 tool has 4 parameters (3 required, 0 enums, 0% schema coverage) and an output schema, the description appropriately covers input semantics, behavior (ordered hourly rows), and usage guidance with sibling reference. With no annotations, it compensates well. The output schema presumably describes return fields, so the description's lack of explicit return format is acceptable.

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 0%, so the description must compensate. It provides clear, helpful semantics for each parameter: region meaning (Balancing authority code with examples), start/end format ('YYYY-MM-DD') with 'inclusive' clarified, and limit meaning (max rows, default 168 = one week of hours). This adds substantial value beyond the schema labels (e.g., 'Region', 'Start', 'End', 'Limit').

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 explicitly states the tool returns hourly electricity demand (MWh) for one region over a date range, using a specific verb 'Return' and identifying the resource (demand data), region, and output unit (MWh). It also distinguishes itself from siblings like daily_demand and peak_demand by mentioning hourly data and the limit default of 168 rows (one week of hours), and directly points to daily_demand as an alternative for long ranges.

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 gives clear when-to-use guidance: 'For long ranges prefer daily_demand', explicitly naming the sibling alternative. It also defines the purpose (hourly data for one region) implicitly telling the agent not to use this for multiple regions or aggregated summaries (compare_regions, peak_demand). The Args docstring reinforces required parameters and their formats.

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