wallet_graphMap wallet connections: find counterparties, detect clusters of coordinated wallets, and identify suspicious patterns.
| Name | Required | Description | Default |
|---|---|---|---|
| depth | No | Hop depth (1 or 2) | |
| address | Yes | Solana wallet address (base58) |
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 fails to mention how the graph is constructed, whether the operation is read-only, limitations such as supported chains or depth semantics, or any details about output format or performance.
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 direct and front-loaded with the action verb. It effectively lists the tool's key capabilities without unnecessary filler.
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?
Without an output schema or annotations, the description must provide more context to be complete. It does not explain what a 'connection' is, how results are returned, or how a user should interpret the clusters/patterns. Given the large number of sibling tools, this leaves the tool's role under-specified.
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 already describes both parameters (address and depth) with 100% coverage, so the description adds no new parameter-level information. The baseline score of 3 applies because the schema does the heavy lifting.
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 with a specific verb 'Map' and resource 'wallet connections', and enumerates three concrete outputs: finding counterparties, detecting clusters, and identifying suspicious patterns. This distinguishes it from sibling tools like 'enrich_wallet' or 'wallet_history' which serve different purposes.
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 for network analysis of wallet relationships, but it does not explicitly state when to use this tool instead of alternatives like 'smart_money_flow' or 'whale_watch' which may overlap. No exclusions or alternative recommendations are provided.
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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With 32 tools, several have overlapping purposes, such as wallet_history vs portfolio_history (both track wallet portfolio over time) and smart_money_flow vs smart_money_trenches (both follow smart money movements). However, most tools have clearly distinct scopes, and detailed descriptions help differentiate them.
All tool names follow snake_case with a predictable verb_noun or noun phrase pattern (e.g., enrich_token, compare_wallets, perps_market_trend). The consistent structure makes the set easy to navigate, even the 'perps_' prefix group is uniform.
32 tools is well above the 25-tool threshold, making the surface feel heavy. While the breadth reflects the wide domain of Solana analytics, the sheer number can overwhelm agents and increase the chance of selecting the wrong tool.
The tool set covers most aspects of Solana token/wallet/perp analysis, including enrichment, comparison, trend tracking, smart money flows, and perp market structure. Minor gaps exist, such as no direct historical OHLCV endpoint, but the existing tools handle core workflows well.