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SofiaFlux

sens-mcp

by SofiaFlux

get_tariff_components

Retrieve the fixed and variable rate components of a Polish energy tariff as approved by URE.

Instructions

Inspect the detailed fixed/variable rate components of a tariff, as approved by URE (the Polish energy regulator).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNo
tariff_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'inspect' which weakly implies a read-only operation, but it does not mention whether the tool returns historical/current data, how 'since' affects behavior, what happens for invalid tariff IDs, or any authorization requirements. The 'as approved by URE' detail adds domain context but no behavioral transparency.

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?

The description is a single, focused sentence with no fluff. It front-loads the core purpose and includes a relevant regulatory qualifier. Nothing extraneous is present, and it is appropriately brief for a straightforward lookup tool.

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

Completeness2/5

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

Despite having an output schema (which covers return values), the description omits key operational context: the optional 'since' parameter is absent, no usage example or prerequisite is given, and the relationship between this tool and get_prices is unclear. For a tool with two params and zero schema descriptions, this is insufficient.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not mention either parameter. The 'since' parameter is completely unexplained, and even 'tariff_id' gets no elaboration beyond its name. The description provides zero added meaning beyond the input schema's property titles.

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 a specific verb ('Inspect') and resource ('detailed fixed/variable rate components of a tariff'), instantly distinguishing it from siblings like search_tariffs or get_prices. The clarification about URE approval adds regulatory context. This is unambiguous and free of tautology.

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

Usage Guidelines2/5

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

The description implies the tool is for inspecting tariff components, but it gives no explicit guidance on when to choose it over get_prices, resolve_operator, or search_tariffs. There are no stated conditions, exclusions, or alternative pointers. The context is limited to a generic 'this is what it does'.

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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