Ethereum address activity: ETH balance plus recent large transfers in and out. Call when a specific wallet or exchange address is named and needs to be tracked.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | Ethereum address (0x...) |
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | ||
| balanceEth | Yes | ||
| recentLargeTransfers | Yes | Transfers above 1 ETH, newest first. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful output context (ETH balance plus transfers) but does not disclose limits like 'recent' definition or pagination. With annotations present, the description provides reasonable additional transparency.
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 two sentences, front-loaded with the core function and followed by an explicit use case. Every word earns its place with no redundancy.
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 single-address lookup tool with an output schema, the description covers the essentials: what it returns, when to call it, and the input. It doesn't define 'recent' but the output schema likely clarifies the response. Overall, it is complete enough for an agent to select and invoke it correctly.
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 input schema covers 100% of parameters with 'address' described as 'Ethereum address (0x...)'. The description does not add extra parameter semantics beyond that, but since schema coverage is complete, the baseline score of 3 is appropriate.
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's function: 'Ethereum address activity: ETH balance plus recent large transfers in and out.' It is specific about the resource (Ethereum address) and distinguishes it from siblings like get_eth_whale_flows by focusing on individual address tracking rather than aggregate flows.
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 explicit guidance on when to use the tool: 'Call when a specific wallet or exchange address is named and needs to be tracked.' This gives clear context, though it does not explicitly mention alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct data domain—network health, market prices, news, DeFi, derivatives per-venue vs aggregate, economic calendar, ETH address, whale flows, execution cost, sentiment, implied volatility, macro rates, market brief, dominance, history, and traditional market quotes. The only similar pair (get_derivatives vs get_derivatives_aggregate) is clearly differentiated by level of detail, so there is no real ambiguity.
All tools follow the get_<domain> pattern with descriptive noun phrases (e.g., get_btc_network, get_eth_whale_flows, get_market_brief). No mixed verb styles or casing conventions appear, making the naming fully predictable and consistent.
At 17 tools, the surface is slightly above the ideal 3-15 range, but the breadth of the domain—spot, derivatives, on-chain, macro, sentiment, and execution—justifies each tool. It's borderline but each tool earns its place in a comprehensive market analysis agent.
The toolset covers nearly every major facet of crypto market analysis: prices, history, dominance, derivatives, on-chain activity, DeFi, macro, economic calendar, sentiment, implied volatility, execution cost, and a composite brief. Minor gaps like historical OHLCV or multi-chain on-chain analytics are not critical given the agent's stated focus.