Xynaptic Energy Price — current electricity spot price (EUR/MWh) with 24h trend and hourly profile. Europe (awattar market data). Lightweight, real-time. [price: $0.005 per call, x402/USDC]
| Name | Required | Description | Default |
|---|---|---|---|
| params | No | query parameters |
Changes observed during successful MCP inspections.
Input schema / properties / bodyRemoved value: -{
- "description": "JSON body for POST endpoints (e.g. insurance, ai-chat, production-risk)",
- "type": "object"
-}Input schema / properties / params / descriptionPrevious value: -"query parameters, e.g. {city: 'Paris', type: 'Appartement'}"New value: +"query parameters"Input schema / properties / params / propertiesAdded value: +{
+ "change_24h_pct": {
+ "description": "example: -12.5",
+ "type": "number"
+ },
+ "price_eur_mwh": {
+ "description": "example: 18.8",
+ "type": "number"
+ },
+ "region": {
+ "description": "example: \"de\"",
+ "type": "string"
+ }
+}Input schema / requiredAdded value: +[]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It usefully adds that the data is real-time, lightweight, sourced from awattar, and priced per call, but it does not describe permissions, rate limits, return format, or failure behavior.
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 compact and front-loads the resource and market. The brand prefix and bracketed cost note are slightly extra, but overall every phrase contributes useful information.
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?
For a simple, zero-required-parameter read tool with no output schema and no annotations, the description identifies the returned data, source, region, and cost. However, it leaves usage routing and parameter semantics ambiguous, which matters given the large sibling set.
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 reported at 100%, so the baseline is 3. The description adds EUR/MWh and Europe/awattar context, but it does not clarify the region values, whether price_eur_mwh and change_24h_pct are inputs or outputs, or how to use the nested params object.
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?
Names the specific resource — current electricity spot price in EUR/MWh with 24h trend and hourly profile — and scopes it to Europe/awattar. It is clear what the tool returns, but it does not explicitly distinguish itself from many energy-* siblings such as energy-brief, energy-demand, or energy-solar-forecast.
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 says nothing about when to use this tool versus alternatives. There is no when-to-use, when-not-to-use, or named sibling guidance despite a crowded energy toolset.
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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