fiscal_list_dimensions

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

Annotations already cover read-only and idempotent behavior, so the description adds value by disclosing the performance characteristic ('may take a moment on a cold cache') and the scope of data loaded ('all three dumps'). It also clarifies the tool's role in converting free-text to exact filter values, which is non-obvious behavior.

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: the first states the exact purpose, the second provides a use case and a performance caveat. Every word earns its place; no fluff or repetition.

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's simplicity (no params, output schema exists), the description fully covers what it does, when to use it, and what to expect. The performance note addresses a key operational concern. No gaps remain.

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 tool has zero parameters and an empty input schema, so the description need not explain individual params. The baseline for 0 params is 4, and the description doesn't contradict or omit anything; it implicitly indicates no input is required.

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 the tool lists valid dimension values across datasets, naming specific categories (variables, households, models, budget topics, departments). This is a specific verb+resource and clearly distinguishes it from sibling tools that focus on headline figures, breakdowns, status, etc.

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?

Explicitly says 'call this first to build correct parameters for the other tools' and explains it turns free-text guesses into exact filter values. This gives precise when-to-use guidance and implies it should precede other tools, effectively differentiating from alternatives.

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