Return recent large Bitcoin movements from satoshidata.ai's live on-chain Pulse feed.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| since | No | ||
| min_btc | 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 behavioral burden. It indicates a read-only operation via 'Return' and adds the 'live on-chain' context, but it does not mention pagination, rate limits, or whether the feed includes unconfirmed transactions, so behavioral disclosure is minimal.
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, front-loaded sentence that states the core function without any extraneous wording. It earns its place by conveying the tool's primary purpose efficiently.
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 extensive list of sibling tools, the description is too sparse to provide sufficient context for correct tool selection. It does not explain how pulse_whales differs from whale_alerts or pulse_dormant, and it omits any usage conditions, making the tool harder to use correctly in a complex environment.
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 compensate for the three parameters. It hints at 'recent' (since) and 'large' (min_btc) but does not explain limit, the format of 'since', or units for 'min_btc', leaving the agent with incomplete 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 the verb 'Return' with the resource 'recent large Bitcoin movements' and mentions the specific source 'satoshidata.ai's live on-chain Pulse feed', clearly indicating what the tool does. However, it does not compare itself to highly similar siblings like whale_alerts or pulse_dormant, so it loses the full sibling-distinguishing score.
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 no explicit guidance on when to choose this tool over the many sibling pulse/whale tools. There is no mention of exclusions, alternative tools, or use-case conditions, leaving the agent to infer applicability from the name alone.
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.