Return one named Bitcoin entity rollup and a bounded member-address sample. coverage_status indicates whether the rollup is full, substantial, partial, or seed-only coverage; last_activity_at is label-DB activity, not last on-chain transaction time.
| Name | Required | Description | Default |
|---|---|---|---|
| entity_name | Yes | ||
| member_limit | No |
| 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 of behavioral disclosure. It adds valuable caveats: coverage_status explains different levels of completeness, and last_activity_at is clarified as label-DB activity, not on-chain time. It also discloses that the member-address list is only a bounded sample, giving the agent crucial expectations about the data. It does not mention error cases or autf requirements, but the disclosed semantics are genuinely informative.
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?
Two concise sentences; the first states the core function, the second adds two essential clarifications about output fields. No fluff, every word contributes to understanding.
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 presence of an output schema (which can document return fields), the description appropriately highlights non-obvious aspects like coverage_status meanings and the distinction of last_activity_at. It also communicates the sampling behavior. It could mention error handling or whether the entity must exist, but for a simple lookup tool this is reasonably complete.
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?
Input schema property descriptions cover 0% of the parameters, so the description must compensate. It only hints at member_limit via 'bounded sample' and does not explicitly describe either parameter. entity_name is self-explanatory from context, but member_limit's role and default are left to the schema (which lacks descriptions). The description adds minimal semantic value for the parameters.
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 returns a rollup for one named Bitcoin entity plus a bounded sample of member addresses. It distinguishes the tool from siblings like entity_list by emphasizing 'one named' entity and the 'bounded' sample, making its specific role clear.
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 when you need a single entity's rollup, but it does not explicitly state when to choose this over alternatives like entity_list or batch intelligence. There are no exclusions or comparisons, so the guidance is only implicit.
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.