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

With no annotations, the description carries the behavioral disclosure burden. It explains that annual_kwh triggers backend-side computation and explicitly warns against client-side re-derivation, and it clarifies the difference between summary and detailed outputs. It does not discuss pagination behavior or authentication, but the 'Fetch' verb implies a read operation and core behavior is disclosed.

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 well-structured: the main purpose is front-loaded, and the second paragraph adds only high-value operational details. Every sentence earns its place, including the warning not to re-derive fees client-side.

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 an 11-parameter tool with no annotations and zero schema descriptions, the description covers the central workflow but omits pagination semantics, the role of 'since', and how this tool relates to its siblings. The presence of an output schema and clear core behavior makes it usable, but the definition is not fully complete for a complex tool.

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 description coverage is 0%, so the description must compensate. It adds real meaning for annual_kwh and detail_level, and lightly maps sprzedawca to 'retailer' while mentioning date, market, region, and annual consumption as scoping options. However, it does not explain page, size, since, or the exact meaning of osd and taryfa beyond the phrase 'OSD + tariff', leaving several parameters only inferable from names.

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 opens with a specific verb ('Fetch') and a precise resource ('composite electricity prices and rate breakdown'), scoped to OSD and tariff. It naturally differentiates this tool from siblings like search_tariffs and get_tariff_components by focusing on composite price retrieval rather than tariff lookup or component extraction.

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 clearly establishes the main use case: fetch prices for a given OSD and tariff, with optional filters. It gives practical guidance for annual_kwh and detail_level, but does not explicitly mention when not to use this tool or when a sibling would be preferable. Context is clear, but exclusions are absent.

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

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.

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.

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.

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.

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.

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.

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

No annotations are provided, so the description carries the full burden. It explicitly discloses the fuzzy-matching typo behavior and the exact-string output expectation. It does not cover edge cases like no-match behavior, but the key behavioral traits are present.

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 sentences plus an example line. Every sentence earns its place: purpose, example inputs, and fuzzy behavior are all stated without filler. The most important 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?

For a simple resolver with an output schema, the description covers purpose, fuzzy behavior, and expected output. The missing region semantics is a real gap, but the overall definition is largely complete and actionable for the common query-only case.

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 description coverage is 0%, so the description must compensate. It explains the query parameter through examples and semantics, but the region parameter is never mentioned at all, leaving one of the two parameters completely undocumented.

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 opens with a specific verb 'Resolve' and names both the input (natural-language city/company name) and the output (exact OSD/default retailer strings for the SENS API). This clearly differentiates it from the sibling search/get tariff tools.

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 clearly indicates when to use this tool: when you have a fuzzy or natural-language operator name and need the canonical API strings. It gives concrete examples. It does not explicitly list exclusions or alternative tools, but the intended scenario is clear.

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

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

No annotations are provided, so the description carries the behavioral burden. 'Discover' implies a read-only search and 'optionally narrowed' describes filtering behavior, but it does not disclose prerequisites such as whether the operator should be resolved first, what happens when no results match, or whether the output is limited to codes rather than prices.

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 a single front-loaded sentence with no filler. It states the core action first and then the optional modifiers, with every phrase contributing to the agent's understanding of what to pass and why.

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 low-complexity search tool with an output schema, the description covers the main operation and filter semantics. But there are no annotations, no guidance on sibling-tool workflows, and no statement about whether customer_type is required or what the default behavior is when optional filters are omitted.

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 description coverage is 0%, so the description must compensate. It maps customer_type to a 'customer profile' and clarifies that zone_preference and operator are optional narrowing filters. However, it does not explain what 'operator' means or the semantics behind the zone enum values, so the compensation is only partial.

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 uses a specific verb ('Discover') and a specific resource ('valid tariff codes'), and clearly scopes the results to a customer profile with optional zone/operator filters. This semantically distinguishes it from sibling tools like get_prices and get_tariff_components, which target different outputs.

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 when to use the tool: when tariff codes are needed for a customer type, optionally narrowed by zone or operator. However, it provides no explicit when-not-to-use guidance, no mention of alternatives, and does not explain how this tool relates to resolve_operator or get_prices.

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