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Energy Charts

by io.github.pipeworx-io

Total Power

total_power
Read-onlyIdempotent

Total electricity generation / load for a country over a date range. Returns {unix_seconds, production_types:[{name, data}]}; data arrays are 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", 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 already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds output structure details (timestamp alignment, MW units) and clarifies the return format, which provides useful behavioral context beyond annotations.

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 cover purpose, scope, output structure, and units with zero waste. All information is front-loaded and essential.

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?

For a simple 3-parameter tool with no output schema, the description covers the key aspects: what it returns, units, and the 'all' country option. It lacks error conditions or limits, but given the simplicity, it is fairly complete.

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 coverage is 100%, so the schema already documents all parameters. The description does not add new parameter details (e.g., date format, defaults) beyond what's in the schema. Baseline 3 is appropriate.

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?

The description uses specific verbs ('returns') and resource ('total electricity generation/load for a country') and clearly distinguishes from siblings like 'generation_mix' or 'electricity_price' by specifying aggregate power data.

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?

The description implies usage for aggregate power queries but does not explicitly state when to use this tool over alternatives (e.g., 'generation_mix' for breakdown). No when-not-to-use guidance is provided.

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

All Energy Charts toolsInspect
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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.

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