Poland Electricity Prices API – PSE Day-Ahead RCE

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

Beyond the annotations, the description discloses that the tool is read-only, only queries the public source, never writes to the registry, and that onlyNew stores a stateKey memory in the user's Apify account. It also covers the APIFY_TOKEN requirement, paid-run billing model, actor identifier, 300-second server wait, and JSON response shape with truncation limits, which is unusually rich behavioral context.

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 front-loaded with the core purpose and then adds the operational details an agent needs: date filtering, publication timing, use case, read-only behavior, auth, billing, runtime, and output limits. Although dense, every clause carries relevant information and there is no filler.

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 a complex paid external-data tool with 9 parameters, no output schema, and annotations that only cover safety/open-world traits, the description fills the important gaps. It explains inputs, timing, auth, cost, runtime, output shape, truncation, and the absence of a sibling alternative, so an agent has enough context to invoke it correctly.

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?

Schema coverage is 100%, so the schema already documents the parameters in detail. The description still adds useful meaning by clarifying date-range versus lastDays behavior, PSE publication timing, maxItems as a combined cap across datasets, and the stateKey memory used by onlyNew, though it does not need to and does not explain every advanced parameter such as maxRequestsPerSecond.

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 uses a specific verb, 'Returns', and names the exact resource: Polish electricity market and grid data from the official PSE API, including RCE prices, day-ahead and imbalance prices, Kompas Energetyczny, load, and generation mix. It also explicitly states that no sibling tool covers electricity, so an agent can distinguish it from the other Polish-domain tools without opening schemas.

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?

It gives clear usage context: filter by business-date range or lastDays, and use it for energy prices and grid statistics. It also explains the publication timing for next-day data around 14:00 Europe/Warsaw and states that no sibling tool covers electricity, which is an explicit alternative-routing statement for this tool set.

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