installed_powerInstalled generation capacity by production type for a country, as an annual or monthly series. Returns {time:["2002",...], production_types:[{name, data}]}; data arrays are aligned to the time array. Capacity in GW.
| Name | Required | Description | Default |
|---|---|---|---|
| country | Yes | 2-letter lowercase country code, e.g. "de", "fr", "es". | |
| time_step | No | Granularity of the capacity series. Default "yearly". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, open-world, idempotent, and non-destructive. The description adds value by detailing the return object structure and that data arrays are aligned, providing useful 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?
Two concise sentences: first states purpose, second specifies output format. No redundant words, and key information is front-loaded.
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 the simple parameters and lack of output schema, the description provides sufficient detail about the return format and units. The tool is straightforward and the description covers all necessary context.
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 baseline is 3. The description mentions 'annual or monthly series' which corresponds to time_step, but adds little beyond the schema's own descriptions.
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 clearly states the tool retrieves installed generation capacity by production type for a country, as time series. It specifies the return format and units, distinguishing it from related tools like total_power or generation_mix.
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 usage for installed capacity queries but does not explicitly state when to use this tool over siblings like total_power or public_power. No guidance on when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.