Return grouped satoshidata.ai label evidence and detail for a single Bitcoin address.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes |
| 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Return' (implying read-only) and 'grouped label evidence,' but does not disclose permissions, rate limits, or any side effects. With no annotations, this is insufficient.
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 sentence that is front-loaded with 'Return' and contains no filler. Every word contributes meaning, making it appropriately concise and well-structured.
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?
An output schema exists, so return-value details are covered. For a one-parameter lookup tool, the description conveys the core scope adequately, though it lacks usage alternatives and deeper behavioral context.
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 schema has one required 'address' parameter with no description (0% coverage). The description clarifies it is a 'single Bitcoin address,' which adds minimal semantic context beyond the schema's type/title and is enough to understand the parameter's purpose.
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 'Return grouped satoshidata.ai label evidence and detail for a single Bitcoin address,' which clearly identifies the verb, resource, and scope. It distinguishes itself from siblings by emphasizing 'grouped label evidence' and 'single address.'
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?
No guidance is provided on when to use wallet_detail versus alternatives like address_evidence_pack or wallet_summary. The description does not mention exclusions, prerequisites, or alternative tools.
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.