Arzbin MCP Server

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

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds valuable context by calling the result 'estimated' and 'indicative', alerting the agent to potential inaccuracy. The 'Not financial advice' disclaimer also adds transparency. No contradiction with annotations.

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 that covers the core function, data source, and an important caveat. Every clause earns its place, with no wasted words.

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 tool's simplicity, the complete input schema, and the presence of an output schema, the description is nearly sufficient. It covers the purpose, the estimation nature, and the data source. A minor gap is that it doesn't hint at how the conversion handles unknown asset codes or rounding, but this is not critical for a conversion 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?

The input schema provides 100% coverage of parameter descriptions, including examples for code and constraints for amount. The description does not add additional parameter-specific meaning beyond restating the asset types, so it stays at the baseline.

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's function: converting fiat, crypto, or gold amounts to Toman value using Arzbin data. The verb 'Converts' and the explicit target (Toman value) distinguish it from the sibling rate-retrieval 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 implies usage context (conversion rather than raw rate lookup) and is supported by the sibling tool names. However, it does not explicitly state when not to use this tool or name alternatives, leaving a slight gap in guidance.

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?

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds the 'where available' condition, implying data may be missing for some currencies, but does not elaborate on error handling, empty results, or rate limits. This is minimal added value beyond annotations.

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 sentence that is concise and front-loaded. It wastes no words and directly communicates the core action and resource, making it easy to scan.

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?

The tool is simple with one parameter and has a comprehensive set of annotations plus an output schema. The description covers the purpose and the availability caveat, which is sufficient for this complexity. Slightly more detail about what 'source comparison data' means could improve it, but it is not necessary given the output schema.

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 100% with the 'code' parameter already described as 'Fiat currency code such as USD, EUR, AED, GBP.' The tool description only repeats 'fiat currency code' without adding new meaning, so it does not compensate beyond the schema baseline.

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 returns 'Arzbin source comparison data for a fiat currency code', specifying both the verb and resource. It distinguishes from sibling tools like get_latest_fiat_rates by focusing on source comparison rather than just rates, and adds a condition 'where available'.

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?

No explicit guidance on when to use this tool versus alternatives. It does not mention that this is for comparing sources or when to prefer it over get_latest_fiat_rates. The 'where available' is a condition, not a usage guideline.

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?

Annotations already cover safety (readOnlyHint, destructiveHint, idempotentHint, openWorldHint). The description adds the caveat that data is 'indicative market data, not financial advice' and calls the data 'curated', providing useful context about data trustworthiness. However, it does not describe response structure or pagination (though an output schema exists), so it does not go beyond a moderate level of added 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 two sentences: the first clearly states the tool's purpose, and the second adds a necessary disclaimer. It is concise, front-loaded, and contains no fluff.

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 tool's simplicity (1 optional parameter, output schema present, strong annotations), the description covers the core purpose, currency scope, and data caveat. It lacks explicit sibling differentiation, but the tool name and description sufficiently convey the crypto-specific use case. This is nearly complete for a read-only list 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?

The input schema fully describes the single 'symbols' parameter (100% coverage), so the description does not need to add parameter context. It neither repeats nor enhances the schema, thus the baseline score of 3 is appropriate.

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's function: 'Returns latest curated Arzbin crypto prices in Toman and USD.' It uses a specific verb ('returns'), specifies the resource ('crypto prices'), and includes currency details, distinguishing it from sibling tools like get_latest_fiat_rates or get_latest_gold_rates.

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 indirectly implies usage by stating 'crypto prices', which differentiates it from fiat and gold rate tools, but it does not explicitly mention alternatives or provide when/when-not guidance. The intended use is clear from context, but no exclusions or alternative tool references are given.

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?

The description adds a data quality caveat ('indicative market data, not financial advice') beyond the annotations, providing useful context about data reliability. It does not disclose rate limits or error behavior, but annotations already cover the read-only and idempotent safety profile.

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, no fluff, front-loads the key function and then a caveat. Every word earns its place.

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?

The tool is simple with one optional parameter and an output schema. The description adequately covers purpose and data quality; the schema handles filtering details. It only lacks explicit usage alternatives, already accounted for in the usage dimension.

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% for the single parameter (codes), including examples and default behavior. The description does not add parameter semantics, but the baseline of 3 is appropriate when the schema fully documents the parameters.

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 returns the latest fiat currency rates in Toman, with a specific resource (Arzbin fiat rates) and scope (latest, in Toman). It distinguishes from siblings like crypto/gold rates and market history by explicitly focusing on fiat currency.

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 does not explicitly mention alternatives or exclusions, such as when to use convert_to_toman or get_market_history. Usage is implied from the tool name and mention of 'fiat rates,' but lacks clear guidance on when not to use this tool.

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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description carries a lower burden. It adds context by noting the data is indicative market data and not financial advice, which helps the agent set appropriate expectations. No contradictions with annotations.

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 two sentences, with the main purpose in the first sentence and a disclaimer in the second. No wasted words, and 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?

The tool is simple with one optional parameter and an output schema, and annotations cover safety. The description plus schema provides sufficient context for correct selection and invocation. No critical information is missing.

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?

The input schema fully describes the 'types' parameter with examples and default behavior (omit for all), achieving 100% schema coverage. The description adds no additional parameter details, so the baseline of 3 applies.

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 returns latest Arzbin gold and coin rates in Toman, using a specific verb and resource. It also distinguishes from sibling tools like get_latest_crypto_rates and get_latest_fiat_rates by focusing on gold and coin rates.

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?

There is no explicit guidance on when to use this tool vs alternatives, but the name and description imply it is for gold/coin rates. It does not mention exclusions or when to prefer sibling tools, so usage guidance is implied rather than explicit.

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?

Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds value by disclosing the clamping behavior ('Days are clamped to 1-365') and specifying OHLC return format, which are not covered by annotations.

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 two sentences, front-loaded with the core purpose, and contains no redundant or vague language. Every word earns its place.

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 tool's low complexity, the presence of an output schema, and rich annotations, the description is sufficient. It covers the essential purpose and the key clamping constraint, making it complete for an agent to select and invoke correctly.

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 covers all parameters with descriptions (100% coverage), so baseline is 3. The description adds meaning by clarifying that days are clamped to 1-365, which is a behavioral detail beyond the schema's simple range description.

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 ('Returns') and resource ('OHLC history') with scope ('fiat, gold, or crypto market'). It clearly distinguishes from sibling tools that focus on latest rates and conversion.

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 implies use for historical data by stating 'history', which contextually separates it from sibling tools like get_latest_fiat_rates. However, it does not explicitly mention when not to use or name alternatives, so it falls short of a 5.

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