get_price_analysis

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It mentions the tool analyzes SPOT prices and returns JSON, but does not reveal potential behavioral traits such as error handling, rate limits, or what 'statistics' entails. More detail is needed.

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 well-structured with docs-style sections (Args, Returns, Examples). However, the note about SPOT is somewhat redundant with the first sentence, and the description could be tightened without losing clarity.

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 3 parameters, no annotations, and an output schema, the description covers the basics (parameter formats, example usage) but lacks completeness on edge cases, error conditions, or more precise definition of 'statistics'. It is adequate but not comprehensive.

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 input schema has 0% description coverage, but the description adds meaning: start_date and end_date are ISO format, geo_filter is optional with examples like "Península" and "Portugal". This compensates for the schema's lack of descriptions.

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 tool's purpose: 'Get electricity price analysis over time' for SPOT market prices with multi-country comparison. It distinguishes from siblings like 'get_spain_hourly_prices' by stating it handles multiple countries.

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 provides usage context: use for SPOT prices, with optional geo_filter to focus on a specific market. Examples clarify typical use cases. However, it does not explicitly mention when to avoid this tool (e.g., for Spain-only data) or name alternatives.

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