get_energy_charts

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

With no annotations provided, the description carries the burden of behavioral disclosure. It adds useful behavioral context: no API key required, faster performance than ENTSO-E, and geographic coverage (EU excluding GB). It stops short of disclosing response format or potential rate limits, but the provided traits are relevant and beyond what the schema offers.

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 compact sentence that front-loads the provider and key data types, then covers scope and performance advantages. Every word adds value, and it avoids repetition of schema content. It is an efficient and well-structured summary.

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?

For a tool with a well-documented schema and no output schema, the description covers the core context: data source, data types, geographical scope, and access requirements. It does not mention the return format (e.g., JSON data vs chart images) nor the additional dataset types not listed in the description (demand, signal, installed_capacity), but those are available in the schema. Overall, it gives enough context for an informed choice, though a little more clarity on return type would make it complete.

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 schema already covers 100% of parameter descriptions, so the baseline is 3. The description mentions 'prices (15-min)' which mirrors the schema's dataset description for 'prices', thus adding no new parameter-specific meaning. It does not clarify zone code conventions or date handling beyond what the schema lists, so it neither improves nor harms the parameter understanding.

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 specifically identifies the provider (Fraunhofer ISE) and the data types provided (prices, generation by fuel, cross-border flows) with a resolution detail (15-min). This clearly communicates what the tool does and distinguishes it from sibling tools like get_nordpool_prices or get_smard_data by naming a unique data source and scope.

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 when to use this tool via 'Faster than ENTSO-E' and notes the exclusion of GB ('All EU except GB'), which gives some context. However, it does not explicitly name alternative tools for GB data or for other scenarios, nor does it state when not to use this tool beyond the GB exclusion.

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