queryAsk a plain English question about any Solana wallet, token, or market. Single-intent routes to one enricher; compound intents chain 2-3 in parallel and return a unified briefing. Examples: "should I buy ?" (DD + trend + whales), "wallet deep dive on " (profile + history + perps), "is safe?", "what's trending right now", "SOL-PERP funding rate".
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Natural language question about a Solana wallet or token |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the orchestration behavior (routing to enrichers, chaining parallel intents, returning a unified briefing), which is valuable. However, it does not mention error handling, ambiguity resolution, or limitations (e.g., unsupported question types). This is acceptable but not exhaustive.
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, tightly packed paragraph that front-loads the core purpose and follows with concrete examples. Every sentence earns its place—no fluff, no restating of the tool name, and the examples are illustrative rather than redundant.
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?
Given the tool's orchestrator role and the absence of an output schema, the description provides a clear mental model of how input maps to behavior (routing and chaining) and indicates the output type ('unified briefing'). It could add a bit more about the content or structure of the briefing, but overall it's sufficiently complete for a query 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?
The schema already defines the 'question' parameter at 100% coverage. The description adds significant semantic value by enumerating example intents ('should I buy <mint>?', 'wallet deep dive', 'SOL-PERP funding rate') that clarify what constitutes a good question, which goes beyond the schema's minimal 'natural language question' description.
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 purpose: to ask plain English questions about Solana wallets, tokens, or markets. It goes beyond a simple definition by explaining the routing behavior (single-intent to one enricher, compound to chained enrichers) and provides concrete examples, making it highly distinguishable from the 30+ sibling tools.
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 this tool: for natural language questions that may require one or multiple data points, with examples showing how to phrase intents. It lacks explicit 'when not to use' or direct mentions of alternative tools, but the routing explanation and examples effectively convey its role as a general-purpose entry point.
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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Several tools cluster around the same action: trending/discovery tools like feed_latest, trending_signals, runner_scan, trenches_scan, smart_money_trenches, attention_momentum, and consensus_signal heavily overlap, and perps_basis_signal, perps_cross_venue_funding, and perps_venue_comparison all cover similar venue/funding comparisons. An agent can distinguish them only by reading fine print, increasing misselection risk.
Most tools follow readable snake_case with strong domain prefixes (perps_*, stonk_*, smart_money_*, hyperliquid_*) and clear verb_noun actions for core operations like enrich_token and compare_wallets. Minor outliers like query, feed_latest, attention_momentum, and new_tokens break the pattern but remain predictable.
41 tools is well over the 25-tool threshold for a coherent agent surface. The set fragments into many micro-specialties—five stonk tools, six perps tools, and several overlapping memecoin scanners—that could be consolidated into broader composite tools without losing capability.
For a Solana token/wallet/perps intelligence platform, the surface is exceptionally broad: discovery, enrichment, due diligence, exit signals, wallet history, transaction parsing, protocol profiles, perps, stonk, and composite querying are all covered. Missing pieces are minor, such as general holder lists or raw transaction history, and can be worked around with existing tools.