Preview the exact lamport fee the given Solana wallet would pay for its next paid validation (fees escalate with consecutive failures).
| Name | Required | Description | Default |
|---|---|---|---|
| wallet_address | Yes | Solana wallet address. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the safety burden. It discloses the behavioral trait of fee escalation and uses 'preview' to suggest a non-mutating read operation. It does not explicitly state 'no side effects' but 'preview' reasonably implies a read-only check.
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 clear, front-loaded with the main action, and contains no filler or redundant information.
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 tool with one well-documented parameter and no output schema, the description adequately explains what the tool does and what it returns (a lamport fee). The only minor gap is not specifying the exact return format or whether the fee is returned as a number or string.
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 the single parameter ('Solana wallet address'), providing 100% coverage. The description adds minimal extra meaning beyond linking the wallet to the fee context, but it does not elaborate on address format or validation requirements.
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 a specific verb ('preview') and identifies the exact resource ('exact lamport fee the given Solana wallet would pay for its next paid validation'), clearly distinguishing this from sibling tools that deal with network stats, pricing, profiles, or text scoring.
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 clearly implies when to use it (before a paid validation to know the fee) and adds important context about fee escalation with consecutive failures. It does not explicitly name alternatives, but the sibling tools are obviously different in scope, so no exclusion is needed.
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.
Most tools target clearly distinct resources: scoring, profiles, pricing, network stats, fee quotes, and feature requests. The only mild ambiguity is between get_pricing and preview_fee, since both deal with fees, but their descriptions clarify one is a general manifest and the other is a wallet-specific quote.
The set mostly follows a snake_case verb_noun convention: get_network_stats, list_profiles, preview_fee, request_feature, score_text. storelayer_widget_menu is the clear outlier, using a noun-heavy compound with no verb and a different naming pattern.
Seven tools is a reasonable size for a platform-facing MCP server and avoids bloat. However, storelayer_widget_menu is an unrelated promotional detour that makes the set feel slightly less well-scoped to its core EQ-scoring purpose.
Core discovery and free scoring are covered well: stats, pricing, profiles, fee previews, feature requests, and score_text. However, paid benchmark submission, progress/trajectory retrieval, and bundle purchasing are only described as external REST endpoints rather than actual tools, leaving notable gaps in the full validation loop.