Return the current Bitcoin price snapshot and 24 hour change from satoshidata.ai.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| ok | Yes | ||
| data | No | ||
| error | No | ||
| endpoint | Yes | ||
| status_code | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It reveals the data source (satoshidata.ai) and the fact that it returns a snapshot and 24h change, which is honest but minimal. It does not mention data freshness, potential delays, or what happens if the source is unavailable, but for a simple read-only price lookup, this level of transparency is acceptable.
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, concise sentence with no filler. It front-loads the key action ('Return') and details the exact output in under 20 words. 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?
For a simple parameterless tool with an output schema present, the description provides the essential context: what data is returned and from where. It could optionally clarify the currency (e.g., USD) but the description is largely sufficient given the output schema handles return-value details. Slightly more context about refresh rate or source reliability would push this higher.
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 tool has zero parameters, so the baseline is 4. The schema already covers this fully (100% coverage), and the description adds no irrelevant parameter details. There is nothing else needed for parameter semantics.
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 'Return' with a clear resource: 'current Bitcoin price snapshot and 24 hour change'. It explicitly states the data source and distinguishes the tool from siblings focused on blockchain analytics, addresses, and mempool stats. This leaves no ambiguity about what the tool does.
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 for retrieving current Bitcoin price and 24h change, but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. Given the context of many sibling tools, some explicit comparison would strengthen this dimension, but the purpose is clear enough to infer typical use cases.
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.
Several tool clusters have unclear boundaries: address_evidence_pack, address_intelligence, address_risk, risk_check, wallet_detail, wallet_summary, and wallet_trust_safety all return address-related intelligence with subtle differences. Similarly, pulse_dormant, chain_awakenings, and dormancy_flushes all describe dormant-coin reactivation events, and whale_alerts overlaps heavily with pulse_whales. Agents will likely struggle to select the correct tool without deep domain knowledge.
Tool names predominantly follow a snake_case convention with domain-prefix patterns (address_*, batch_*, entity_*, mempool_*, pulse_*, timestamp_*, tx_*, wallet_*). There are minor deviations like op_return_decode (object-verb ordering) and some noun-only names, but overall the pattern is predictable and readable.
With 44 tools, this is a large surface that exceeds the 'too many' threshold in the calibration scale. While the server covers a broad Bitcoin intelligence domain, the sheer number of tools—especially with overlapping functionality—makes it feel bloated and difficult to navigate.
The tool set covers virtually every major aspect of Bitcoin intelligence: address analysis, entity rollups, mempool state, network stats, mining pools, on-chain pulse events, transaction verification, timestamping, and batch operations. There are no obvious dead ends or missing capabilities for the stated purpose.