CurrencyAndOil

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose with no ambiguity. The three 'calculate_barrels_for_*' tools each handle different currencies, while the four 'get_*_rate' tools each provide different exchange or oil price data. The naming and descriptions make it impossible to confuse which tool to use for which currency or rate type.
Naming Consistency5/5
The tool names follow a perfectly consistent verb_noun pattern throughout. All tools use snake_case with clear action prefixes ('calculate_' for conversion tools, 'get_' for rate retrieval tools) followed by specific currency or rate identifiers. This creates a highly predictable and readable naming convention.
Tool Count5/5
The 7 tools are well-scoped for the server's purpose of currency and oil price calculations. Each tool earns its place by covering different currency pairs (EUR, RUB, USD) and both calculation and rate retrieval functions. The count is neither too sparse nor bloated for the domain.
Completeness5/5
The tool surface provides complete coverage for the domain of calculating oil barrel purchases across major currencies. It includes all necessary rate retrieval tools (Brent prices in RUB/USD, EUR/RUB and USD/RUB exchange rates) and corresponding calculation tools for each supported currency. There are no obvious gaps or dead ends in the workflow.
Average 3.6/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

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 mentions the data source ('zenrus.ru') but doesn't describe rate limits, error conditions, freshness of 'current' data, or authentication needs. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
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, efficient sentence that states exactly what the tool does without any wasted words. It's appropriately sized for a simple tool with no parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple data retrieval tool with no parameters and no output schema, the description is minimally adequate. It specifies what data is retrieved and the source, but lacks information about return format, error handling, or data freshness that would be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the input requirements. The description doesn't need to add parameter information, and it appropriately doesn't mention any parameters. The baseline for 0 parameters is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get current Brent crude oil price in USD per barrel from zenrus.ru'. It specifies the verb ('Get'), resource ('Brent crude oil price'), and unit ('USD per barrel'), but doesn't explicitly differentiate from sibling tools like 'get_brent_rub_rate' or 'get_usd_rate' beyond the currency specification.
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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_brent_rub_rate' (for RUB) or 'get_usd_rate' (for general USD rates), leaving the agent to infer usage based on the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions the data source ('zenrus.ru') but lacks behavioral details such as rate limits, error handling, freshness of the rate, or whether it's a read-only operation. This is a significant gap for a tool with zero annotation coverage.
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, efficient sentence that front-loads the core action ('Get current USD/RUB exchange rate') and includes the source without any wasted words. Every part of the sentence earns its place by specifying what, from where, and the currency pair.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema), the description is adequate but incomplete. It lacks details on return format, error cases, or behavioral traits, which are important for a tool fetching real-time data. Without annotations or output schema, more context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The baseline for this scenario is 4, as the description appropriately focuses on the tool's purpose without redundant parameter information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('current USD/RUB exchange rate') with the specific source ('from zenrus.ru'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like get_eur_rate or get_brent_usd_rate, which appear to fetch different rates, preventing a perfect score.
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 provides no guidance on when to use this tool versus alternatives. With siblings like get_eur_rate and get_brent_usd_rate available, it doesn't specify scenarios where USD/RUB is needed over other currency or oil rates, leaving usage context unclear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the calculation purpose but doesn't disclose behavioral traits such as whether it uses real-time rates, historical data, or assumptions about oil prices. No information on error handling, rate limits, or data sources is included.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with every part contributing essential information.
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?
Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on how the calculation is performed, what data sources are used, error conditions, and the format of results, making it inadequate for full contextual understanding.
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 description coverage is 0%, so the description must compensate. It adds meaning by specifying that the 'amount' parameter is in Euros, which isn't in the schema. However, it doesn't explain units, constraints, or provide examples, leaving gaps in parameter understanding.
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 clearly states the specific action ('calculate') and resource ('barrels of Brent crude oil') with precise scope ('for a given amount in Euros'). It distinguishes from siblings like calculate_barrels_for_rub and calculate_barrels_for_usd by specifying the currency input (Euros).
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 when converting Euros to barrels, but doesn't explicitly state when to use this tool versus alternatives like get_eur_rate or calculate_barrels_for_usd. No guidance on prerequisites or exclusions is provided, leaving usage context partially ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the calculation purpose but lacks behavioral details such as whether it uses real-time or cached rates, any rate limits, error handling for invalid amounts, or output format. This is a significant gap for a financial calculation tool.
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, clear sentence with zero waste—front-loaded with the verb and resource, efficiently conveying the tool's purpose without unnecessary words.
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?
Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It doesn't explain the calculation method, return values (e.g., barrels as a number), or error cases, leaving critical gaps for agent usage in a context with multiple sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
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 mentions 'a given amount in Russian Rubles' which clarifies the 'amount' parameter's purpose, but doesn't add details like units (e.g., Rubles as a number), constraints (e.g., positive values), or examples. This partial compensation is insufficient for full clarity.
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 clearly states the specific verb 'calculate' and the resource 'barrels of Brent crude oil' that can be purchased, with explicit mention of the input currency 'Russian Rubles'. It distinguishes from siblings by specifying the currency input, unlike calculate_barrels_for_eur and calculate_barrels_for_usd.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying 'for a given amount in Russian Rubles', indicating this tool is for converting Rubles to barrels. However, it doesn't explicitly state when to use this versus alternatives like get_brent_rub_rate for just the rate, or when not to use it for other currencies.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the calculation purpose without disclosing behavioral traits. It doesn't mention whether this uses real-time rates, historical data, requires network calls, has rate limits, or what the output format might be, which are significant gaps for a financial calculation tool.
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, well-structured sentence that efficiently conveys the core functionality without any wasted words. It's appropriately front-loaded with the essential information and maintains perfect conciseness for this straightforward 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?
Given the financial calculation complexity, lack of annotations, no output schema, and minimal parameter documentation, the description is insufficiently complete. It doesn't explain how the calculation works (e.g., using current exchange rates, fixed formulas), what data sources are used, or what the return value represents, leaving too many unknowns for reliable agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for the single 'amount' parameter, and the description doesn't add any semantic context beyond implying it's in US Dollars. It doesn't specify units (e.g., whether amount is in dollars, thousands, etc.), valid ranges, or formatting requirements, failing to compensate for the schema's lack of documentation.
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 clearly states the specific verb ('calculate') and resource ('barrels of Brent crude oil') with precise scope ('for a given amount in US Dollars'). It effectively distinguishes from sibling tools like calculate_barrels_for_eur and calculate_barrels_for_rub by specifying the currency context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through 'for a given amount in US Dollars', which helps differentiate it from EUR/RUB variants. However, it doesn't explicitly state when to use this tool versus alternatives like get_brent_usd_rate or provide exclusion criteria, leaving some guidance gaps.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states what data is retrieved but doesn't disclose behavioral traits like rate limits, error conditions, authentication needs, freshness guarantees, or whether it's a read-only operation. The description is minimal beyond the basic function.
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?
Single sentence with zero waste - every word contributes essential information (action, what, source). Perfectly front-loaded with the core function. No unnecessary elaboration or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only data retrieval tool with no parameters and no output schema, the description covers the basic purpose adequately. However, without annotations or output schema, it lacks information about return format, error handling, or operational constraints that would be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose. Baseline is 4 for zero-parameter tools.
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 clearly states the specific action ('Get'), resource ('current EUR/RUB exchange rate'), and source ('from zenrus.ru'). It distinguishes from siblings like get_usd_rate and get_brent_rub_rate by specifying the exact currency pair and data source.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when you need the EUR/RUB rate from this specific source), but doesn't explicitly state when to use alternatives like get_usd_rate or calculate_barrels_for_eur. It provides clear purpose but lacks explicit comparative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 states the tool fetches current data, implying it's a read-only operation, but doesn't disclose behavioral traits like rate limits, error handling, or data freshness. The description adds basic context but lacks depth on operational constraints.
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, efficient sentence that front-loads the core purpose ('Get current Brent crude oil price') and includes essential details (currency, source) without redundancy. Every word earns its place, making it highly concise and well-structured.
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?
Given the tool's simplicity (0 parameters, no annotations, no output schema), the description is nearly complete: it specifies what data is retrieved, in what currency, and from which source. However, it lacks details on output format or potential errors, which could be helpful despite the absence of an output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't mention parameters, which is appropriate, but it could theoretically add context about implicit inputs (e.g., source dependency). Baseline is 4 for zero parameters, as the schema fully covers the absence.
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 clearly states the specific action ('Get'), resource ('current Brent crude oil price'), and key details ('in RUB per barrel from zenrus.ru'). It precisely distinguishes this tool from its siblings (e.g., get_brent_usd_rate for USD pricing, get_eur_rate for EUR rates).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly indicates when to use this tool: for retrieving Brent crude oil prices in RUB per barrel. It implicitly distinguishes it from alternatives by specifying the currency (RUB) and source (zenrus.ru), guiding users away from sibling tools like get_brent_usd_rate or other currency calculators.
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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