Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must reveal behavior, but it only lists three high-level actions (score, surface, map) without detailing output format, data sources, limitations, or unexpected behaviors. The schema parameters already imply most of the behavior, so the description adds little 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 with no fluff. The first sentence grabs attention, and the second succinctly lists the core capabilities. Every word earns its place.

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?

The tool has five parameters and no output schema, yet the description does not explain what the tool returns or how to interpret the results (e.g., a ranked list, a graph structure, etc.). This is a significant gap for an agent deciding how to use the output.

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 schema covers 100% of parameters, but the description adds conceptual context: 'copy-trade metrics' ties to min_win_rate and lookback_days, 'tokens accumulating' maps to top_n_tokens, and 'wallet clusters' relates to include_graph. This enriches understanding beyond the schema.

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 it scores Solana wallets by copy-trade metrics, surfaces accumulated tokens, and maps wallet clusters, using specific verbs and resources. It distinguishes itself from similar siblings like copy_trade_signals by focusing on high-performing wallets and cluster analysis.

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 opening phrase 'Where high-performing Solana wallets are moving' implies a use case for tracking smart money flow, but it does not explicitly state when to use this tool over alternatives like smart_money_trenches or copy_trade_signals. No exclusions or alternative guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.