get_treasury_holdingsBitcoin held on the balance sheets of tracked public companies, in aggregate and by largest holder. Takes no arguments. Returns { as_of, total_btc, company_count, total_value_usd, top[], why, disclaimer }, where top[] lists the largest holders as { name, symbol, btc }. Example: {}. Information, not financial advice.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnly and idempotent hints. The description adds valuable context by specifying the exact return structure ({ as_of, total_btc, company_count, total_value_usd, top[], why, disclaimer }), clarifying that it covers 'tracked' companies only, and including a 'not financial advice' disclaimer. This goes beyond the 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 compact and efficiently structured: it states the purpose, notes the lack of arguments, details the return fields, provides an example, and includes a disclaimer—all in four short sentences with no redundancy.
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?
Despite lacking an output schema, the description fully defines the return format, including the nested top[] structure. It also includes an example and a disclaimer, making the tool's output and limitations clear for a parameterless operation.
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?
There are no parameters, and the description explicitly confirms 'Takes no arguments,' matching the empty input schema. With zero parameters, the baseline is 4, and nothing needs further explanation.
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 explicitly states the tool's function: reporting Bitcoin held on balance sheets of tracked public companies, both in aggregate and by largest holder. This clearly differentiates it from sibling tools like get_etf_flows or get_sovereign_reserves, which focus on other data domains.
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 intended use case is implied by the description (analyzing corporate bitcoin treasuries), but there is no explicit guidance on when to use this tool versus alternatives, nor any exclusion criteria. It relies on the user to infer appropriate usage.
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 targets a distinct Bitcoin intelligence domain—ETF flows, hiring, hashrate, sovereign reserves, treasury holdings, daily digest, and cross-signal scan—with no functional overlap. Even similar-sounding holdings tools are clearly separated by nation-state vs. corporate focus.
Six of seven tools follow a consistent get_<domain> pattern, making them predictable and discoverable. The single outlier, scan_signals, breaks the pattern slightly but remains readable and within the same verb_noun style.
Seven tools is well-scoped for a Bitcoin signals server—broad enough to cover multiple indicator categories without bloat. Each tool serves a clear, non-redundant purpose.
The tool set covers the stated domain of leading non-price indicators comprehensively, including individual domain-specific queries and an aggregated, filterable scan. No obvious missing operations or dead-ends; the daily brew provides a digest while scan_signals offers detailed rankings.