macro_usa_rig_count

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, establishing a safe read operation. The description adds useful context: the exact data range, the return type (pandas.DataFrame), and the source URL. This goes beyond what annotations provide without contradicting them.

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 compact, consisting of three short lines: the report title and date range, the source URL, and the return type. Every line adds value, and there is no redundant or extraneous wording. It is efficiently structured for quick consumption.

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?

With no output schema, the description covers the return type and data range, which is essential. It does not list specific DataFrame columns or clarify whether all historical data is returned or just the latest week, but given the zero-parameter, simple fetch nature of the tool, the provided information is largely sufficient.

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 no parameters, so the empty schema is 100% covered by definition. The description adds relevant non-parameter information (return type and source), which is appropriate for a zero-parameter tool. The baseline of 4 applies here, and the description does not detract from it.

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 identifies the resource as the Baker Hughes drilling report (rig count) with a specific data range (20080317 to present) and source URL. It effectively distinguishes this from sibling macro_* tools by naming the unique data source and metric (rig count).

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 context via the title and data range, but it does not explicitly state when to use this tool versus alternatives. There are no explicit exclusions or references to other tools, so the guidance is implicit rather than prescriptive.

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