Return the combined Bitcoin network summary for agents: price, fees, mempool, blocks, and satoshidata.ai chain-intelligence context. Set include_charts=true only when chart arrays are needed.
| Name | Required | Description | Default |
|---|---|---|---|
| include_charts | 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?
No annotations are provided, so the description must cover behavioral traits. It hints at read-only behavior through 'summary' but does not explicitly state that it is a safe read operation, rate limits, or any other behavioral context.
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 sentences: the first provides the core purpose, the second clarifies parameter usage. No extraneous information, efficient and front-loaded.
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?
With an output schema present, the description need not detail return values. It sufficiently covers what the tool provides (price, fees, mempool, etc.) and the optional chart inclusion, making it complete for this combined summary tool.
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?
For the single parameter include_charts, the description adds meaning beyond the schema by explaining when it should be used ('only when chart arrays are needed'). This compensates for the 0% schema description coverage.
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?
Clearly states 'Return the combined Bitcoin network summary' with specific components listed (price, fees, mempool, blocks, chain-intelligence). Distinguishes from sibling tools which are focused on individual aspects.
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?
Provides guidance on the include_charts parameter ('Set include_charts=true only when chart arrays are needed') but lacks explicit context on when to use this combined tool vs specific sibling tools like bitcoin_price or mempool_stats.
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.
Multiple tools cover similar address intelligence (e.g., address_intelligence, address_risk, risk_check, wallet_summary) and dormant coin detection (pulse_dormant, dormancy_flushes, chain_awakenings), causing potential confusion despite descriptive names. Some overlap exists but descriptions help differentiate.
Tools use snake_case and generally follow a verb_noun or noun_verb pattern (e.g., address_evidence_pack, batch_intelligence, fees_recommended). However, a few tools like submit_feedback and verify_timestamp start with verbs, while others start with resources, causing minor inconsistency.
44 tools is high for a wallet intelligence server, covering many subdomains (address, batch, blockchain, mempool, mining, timestamping, etc.). While each tool has a specific purpose, the count feels heavy and could be consolidated, but it's not extreme given the broad scope.
The tool set thoroughly covers Bitcoin wallet and on-chain intelligence: address lookup, risk, evidence, batches, blocks, mempool, fees, mining pools, timestamping, transaction broadcast/verification, pulse feeds, whales, and more. No obvious gaps for the stated purpose.