get_energy_breakdown

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

Annotations are absent, so the description carries full burden. It explicitly states the tool returns data (crude oil prices, etc.), implying a read-only operation with no side effects. While it does not explicitly confirm read-only behavior or mention caching/rate limits, the list of outputs is sufficiently transparent for a data retrieval tool.

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, well-structured paragraph with three sentences. It front-loads the main purpose, provides a detailed list of outputs, and ends with usage context. Every sentence adds value, though a slightly more concise enumeration might improve it marginally.

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 no parameters, no output schema, and moderate complexity, the description provides a thorough account of the data included and the business context (GDI Energy pillar). It covers all necessary information for an agent to understand what the tool returns and its relevance.

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?

There are zero parameters in the input schema, which is fully covered by the schema description (trivially 100%). The description adds no parameter meaning, but the baseline for no parameters is 4. It does not need to compensate for missing schema documentation.

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 provides a comprehensive US energy market status for supply chain cost analysis. It specifies the exact data returned (crude oil, natural gas, etc.) and distinguishes itself from the sibling 'get_energy_forecast' by noting it is the disaggregated view behind the GDI Energy pillar, offering a full picture rather than a single risk number.

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 identifies target users (supply chain cost analysts, transportation managers, energy procurement teams), which implies usage context. However, it does not explicitly state when to use this tool versus alternatives like 'commodity_price_monitor' or 'get_energy_forecast', nor does it provide exclusions or conditions for use.

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