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Public Power

public_power
Read-onlyIdempotent

Electricity generation broken down by production type (solar, wind, nuclear, gas, etc.) for a country over a date range. Returns {unix_seconds, production_types:[{name, data}]}; each series' data array is timestamp-aligned to unix_seconds. Power in MW.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoOptional end date, YYYY-MM-DD. Defaults to today.
startNoOptional start date, YYYY-MM-DD. Defaults to 7 days ago.
countryYes2-letter lowercase country code, e.g. "de", "fr", "es", "pl", or "all" for the EU aggregate.

TDQS

A4/5.0
Behavior4/5

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

Annotations declare readOnlyHint and idempotentHint, indicating safety. Description adds details on return structure (unix_seconds, production_types), timestamp alignment, and units (MW), going beyond annotations. No contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences plus return format note. Purpose is front-loaded, details are concise, and every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given annotations and no output schema, the description covers input, output structure, and units. Missing error handling or data availability details, but sufficient for a read-only query tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all parameters with descriptions; description adds examples and context (e.g., country codes). However, the description does not significantly enhance understanding beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it returns electricity generation by production type for a country over a date range. It specifies the return format and units, distinguishing it from siblings like total_power, electricity_price, etc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Describes the tool's functionality and parameters but does not explicitly guide when to use it over siblings (e.g., total_power, generation_mix). The context is implied but not explicit.

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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TDQS

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_grounded, and deep_research, which all perform similar data retrieval. The multiple Polymarket tools also overlap in focus, making it unclear which to use for a given task.

Naming Consistency2/5

Tool names are inconsistent: some use 'ask_', 'polymarket_', 'pipeworx_', while others like 'electricity_price', 'installed_power', and 'remember' follow no coherent pattern. Conventions are mixed and unpredictable.

Tool Count2/5

With 35 tools, the server is over-scoped for an 'Energy Charts' purpose. Only 5-6 tools are directly energy-related; the rest are a miscellany of data services, prediction markets, and memory functions, which is excessive and unfocused.

Completeness2/5

The server lacks essential energy analysis tools like forecast, emission factors, or capacity utilization, yet includes many unrelated tools (e.g., betting, memory). This creates significant gaps for the stated domain.