Get daily aggregate stablecoin data at different levels.
level='total': daily total market cap.
level='symbol': daily breakdown per stablecoin.
level='chain': daily breakdown per chain per symbol.
| Name | Required | Description | Default |
|---|---|---|---|
| level | No | total | |
| end_date | No | ||
| start_date | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, covering safety behavior. The description adds the concrete behavioral meaning of the 'level' parameter, which goes beyond the annotations. It does not disclose date-handling behavior or return formats, but given the strong annotation baseline, this partial addition is valuable and non-contradictory.
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 exceptionally concise, using a short lead sentence and three bullet-like lines for the level options. Every word earns its place, with no filler or repetition. The structure makes the options 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 relatively simple, and the description covers the core level parameter well. However, since there is no output schema, the description is also responsible for indicating what the returned data looks like, which it does not. Date parameters are also left undocumented, making the tool only partially complete despite its simplicity.
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 fully compensate. It explains the 'level' parameter values clearly but completely omits any semantics for 'start_date' and 'end_date', including format, defaults, or behavior. This leaves two of three parameters undocumented, which is a significant gap.
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 clear verb 'Get' and specific resource 'daily aggregate stablecoin data', enumerating the distinct level options ('total', 'symbol', 'chain'). This clearly differentiates it from sibling tools like orbuc_stablecoin_coin or orbuc_stablecoin_health, which focus on individual coins or health metrics.
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 provides clear context by defining what each level returns, implying this tool is for aggregate daily data rather than single-coin or health queries. However, it does not explicitly state when to avoid using it or name alternative tools for other use cases, so it falls short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose with no ambiguity. The BTC tools focus on holdings data with different temporal granularities (current, daily, weekly) and segment breakdowns, while the stablecoin tools cover market cap, supply data, chain distribution, and health checks. There is no functional overlap between tools, making selection straightforward.
All tool names follow a consistent snake_case pattern with a clear prefix structure: 'orbuc_btc_' for Bitcoin-related tools and 'orbuc_stablecoin_' for stablecoin-related tools. The naming convention is uniform throughout, using descriptive nouns and adjectives to differentiate functions (e.g., 'health', 'current', 'daily', 'segments').
With 12 tools, the server is well-scoped for its dual-domain purpose covering BTC holdings and stablecoin data. The count is appropriate, providing comprehensive coverage without bloat, and each tool serves a distinct, necessary function in the data retrieval and monitoring workflow.
The tool set offers complete coverage for both BTC holdings and stablecoin data domains. For BTC, it includes health checks, current holdings, daily/weekly time series, and segment breakdowns. For stablecoins, it covers health, aggregate data, chain distribution, historical and latest coin-specific data, and market cap tracking, leaving no obvious gaps for typical agent workflows.