Get daily BTC holdings time series, optionally filtered by segment.
Args:
segment: public_companies, etf_funds, governments, private_companies,
defi_other, exchanges_custodians. Omit for aggregate totals.
start: Start date YYYY-MM-DD
end: End date YYYY-MM-DD
| Name | Required | Description | Default |
|---|---|---|---|
| end | No | ||
| start | No | ||
| segment | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds the behavioral nuance that omitting the segment parameter yields aggregate totals, but it does not disclose other traits such as response format, pagination, default date ranges, or potential errors. This is comparable to the get_calls example where annotations cover safety and the description adds a scoping constraint, justifying a 3.
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 succinct: a one-line summary followed by a clear Args block. Every line provides necessary information without fluff. It is well-structured and front-loaded with the action, making it easy to parse quickly.
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 and good annotations, the description covers the essential usage: the data type, filtering, and date range. However, with no output schema, it does not describe the response structure (e.g., fields like date and amount) or what happens when start/end are omitted. This minor gap prevents a perfect score.
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 explain parameters. It does: segment lists all possible values and states 'Omit for aggregate totals,' while start and end are given explicit date format 'YYYY-MM-DD'. This adds significant meaning beyond the raw schema, making it easy for an agent to know valid inputs and behavior.
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 purpose: 'Get daily BTC holdings time series, optionally filtered by segment.' The verb 'Get' plus the resource 'daily BTC holdings time series' is specific and distinguishes it from sibling tools like current, weekly, or segments. The mention of 'aggregate totals' when segment is omitted further clarifies scope.
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 on when to use this tool: for daily holdings data, with optional filtering by a list of named segments. It implies that omitting segment returns aggregate totals. However, it does not explicitly mention alternative tools or when not to use it (e.g., for current holdings use orbuc_btc_holdings_current), so it stops 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.
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.