Server Quality Checklist

Tool Scores

• market_data_metadataB
  3.2/5.0
  Behavior3/5

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

  The description discloses credit behavior (indicative credits, actual in response headers) and mentions optional pagination/type filtering. However, without annotations, it does not cover response format, rate limits, or other behavioral traits, leaving a moderate gap.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is concise and well-structured, with a clear action list and credit note. It avoids irrelevant detail, though the action bullet is slightly redundant with the main description.

  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?

  The tool is simple and the schema is fully covered, but the absence of an output schema and lack of description about the returned data leaves ambiguity about what the list will contain. The cost information and action list help, but the response format is not disclosed, so the completeness is moderate.

  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?

  The input schema provides 100% descriptive coverage for all parameters. The description merely summarizes 'optional pagination and type filter' without adding any information beyond what the schema already documents, so it meets the baseline but adds no extra value.

  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 lists supported crypto and fiat assets, with a specific action name. However, it does not explicitly differentiate from sibling tools like 'market_data_assets' or 'market_data_exchange_rates', so it is specific but not fully disambiguated.

  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?

  There is no guidance on when to use this tool versus alternatives. The description only provides the action and credit information without any context for selection or exclusion.

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

• market_data_assetsB
  3.4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden. It does disclose the credit cost per action and notes that actual credits are returned in headers, which is useful. However, it does not clarify if the operation is read-only, potential errors, or any side effects, leaving a gap.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is well-structured with bullets and front-loads the main purpose. The credit information adds detail but is relevant. It is not overly verbose.

  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?

  With no output schema, the description should provide more context on the return payload. It mentions asset details but doesn't describe the structure or fields. The two actions are clear, but the lack of response details leaves the tool under-specified.

  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?

  Input schema has 100% description coverage, with each parameter already described (e.g., assetId and assetSymbol with examples). The description only repeats the action-to-parameter mapping without adding new semantics, so baseline score of 3 applies.

  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 handles 'Market Data assets (asset details)' and enumerates two specific actions for retrieving asset details by ID or symbol. This gives a clear verb+resource. It doesn't explicitly contrast with sibling tools, but the actions are distinct.

  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: use get-asset-details-by-asset-id when you have an ID, and get-asset-details-by-asset-symbol when you have a symbol. However, it does not provide explicit guidance on when to choose this tool over siblings or any exclusions.

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

• market_data_exchange_ratesA
  3.8/5.0
  Behavior3/5

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

  The description discloses credit costs per action and notes that credits are indicative, with actual credits returned in response headers. Since no annotations are provided, the description carries the burden, but it does not mention whether the tool is read-only, likely response format, or error behavior.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is well-structured with bullet points for actions and credits, and front-loaded with 'Market Data exchange rates.' The credit list is slightly redundant since both actions cost the same, but overall it remains concise and scannable.

  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?

  With no annotations and no output schema, the description should provide more context. It lists actions and credits but lacks guidance on parameter grouping, response structure, error handling, or examples. The tool is simple enough that this is acceptable but leaves gaps.

  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?

  The schema already covers all parameters with descriptions, so baseline is 3. The description adds examples like BTC and USD, but does not clarify which parameters are required together or how the action field dictates parameter usage.

  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 tool provides exchange rates, with two specific actions 'get-exchange-rate-by-asset-symbols' and 'get-exchange-rate-by-asset-ids' that list the verb and resource. This differentiates it from sibling tools like market_data_metadata, which focus on metadata.

  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 makes it clear that exchange rates are the domain, and the two actions are defined with their parameters. However, it does not explicitly state when to use one action over the other or mention alternative tools for non-exchange-rate needs.

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

• system_infoA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description must disclose behavior. It states the tool is a reference doc, makes no API call, consumes no credits, and lists the content of each action. This is transparent and honest. It does not describe the response format, but for a documentation lookup the key facts are covered.

  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 well-organized with a clear lead statement and bullet points for each action. Every line earns its place, with no redundancy or filler. It is appropriately sized for the complexity.

  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, the description covers essentials: what it is, no API call, and the specific content of each action. The schema handles parameters. It could mention the response format or the 'context' echo, but these are minor given the reference nature.

  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?

  Schema coverage is 100% and both parameters are described. The description adds value by explaining what each action value returns (e.g., 'Complete error code table', 'Credit charging structure'), going beyond bare enum labels. This helps the agent select the correct action.

  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 tool is 'CryptoAPIs reference documentation' and lists specific topics it covers (blockchains, errors, credits, callbacks, limits). This distinguishes it from the sibling market data tools, which are about live data. The resource and scope are unmistakable.

  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?

  It explicitly says 'no API call, no credits consumed', which immediately signals when to use this for reference lookups. It also details what each action returns, implying the appropriate contexts for choosing this tool over live-data siblings. No explicit exclusions or alternatives are given, but the context is clear.

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