Compare one endpoint across multiple zones.
start/end default to UTC; start inclusive, end EXCLUSIVE.
tz="local" is rejected (zones may differ); pass an explicit IANA
tz like "Europe/Berlin" if you need wall-clock alignment.
| Name | Required | Description | Default |
|---|---|---|---|
| tz | No | ||
| end | Yes | ||
| start | Yes | ||
| zones | Yes | ||
| endpoint | Yes | ||
| aggregation | No | daily |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description shoulders the behavioral disclosure. It clearly explains the start/end boundary behavior and the `tz="local"` rejection with an acceptable alternative, but it does not disclose whether the operation is read-only, how zone validity is handled, or what happens on missing data. This is useful but partial.
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 three short sentences with no filler. The core purpose comes first, and the time semantics are formatted as scannable rule lines. Every sentence earns its place.
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?
The description nails the non-obvious time behavior, and an output schema exists so return-value structure does not need to be explained. On the other hand, the `aggregation` parameter has no explanation beyond its default, and there is no guidance on how missing zones or invalid endpoints will be reported. For a six-parameter tool with no annotations, this is decent but not 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 has 0% coverage, and the description adds real meaning for `start`, `end`, and `tz`, clarifying UTC defaults, inclusivity, and the IANA requirement. However, `endpoint`, `zones`, and especially `aggregation` (only shown with `default: "daily"` in the schema) remain undocumented, so the compensation is incomplete.
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 opens with 'Compare one endpoint across multiple zones,' which clearly identifies the verb, resource, and scope. It is distinguishable from siblings like get_series and list_zones, though it does not explicitly name an alternative.
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 gives explicit time-window semantics (UTC default, inclusive start, exclusive end) and concrete guidance for the tz parameter, including a rejection case and workaround. It does not explicitly state when to choose this tool over siblings such as get_series or get_generation, so usage context is mostly implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Several dedicated getters (get_day_ahead_prices, get_generation, get_load, get_crossborder_flow) overlap with the generic get_series, which explicitly covers the same endpoint families, creating some choice ambiguity. However, the tool names and cross-references like get_derivation vs get_tb_spread and compare_zones vs get_series help an agent distinguish the specific purpose of each tool. Overall there is real overlap, but the descriptions mostly steer an agent correctly.
Tool names are lowercase snake_case and consistently follow verb-first patterns: get_ for data retrieval, list_ for reference/discovery, and compare_/data_ for cross-cutting utilities. No mixed casing or erratic verb styles appear. data_coverage is a minor pattern deviation but still reads naturally alongside the other names.
Fourteen tools is well within the appropriate range for an ENTSO-E data platform: several list_ discovery tools, specialized getters, a generic get_series to prevent endpoint-specific tool explosion, plus data_coverage and compare_zones. The count feels comprehensive without being bloated, and the generic query tool keeps the surface scalable.
The tool surface covers the core read-only ENTSO-E workflows: endpoint discovery, zone/psr_type reference data, raw time-series via get_series, outages, cross-border flows, load, generation, prices, and server-side derivations. It also adds operational safeguards like data_coverage and analytical shortcuts like compare_zones and get_derivation. There are no obvious dead ends or missing lifecycle stages for the stated domain.