Full DrainBrain risk analysis for a Solana token using a 5-model AI ensemble. Returns score 0-100, risk level, rug stage, honeypot detection, risk flags, and temporal prediction.
| Name | Required | Description | Default |
|---|---|---|---|
| mint | Yes | Solana token mint address (base58) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden and does disclose the return payload, the 5-model ensemble methodology, and the analytical scope. It does not mention latency, failure modes, or safety guarantees, but the analysis framing reasonably implies read-only behavior.
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?
One sentence with high information density, placing the primary purpose first and then listing concrete outputs. No wasted words or redundant restatement of the schema.
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 a single well-documented parameter and no output schema, the description sufficiently explains what the tool returns. It could add guidance on error handling or when to prefer other tools, but it is functionally complete for invocation.
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 documents the only parameter (mint) with a clear description ('Solana token mint address (base58)'), achieving 100% coverage. The tool description adds no additional parameter semantics, so 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?
Clearly identifies a full risk-analysis function for a Solana token and explicitly lists the output fields (score, risk level, rug stage, honeypot detection, risk flags, temporal prediction). This distinguishes it from sibling tools such as scan_token_preview.
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 word 'Full' implies a comprehensive scan relative to scan_token_preview, but there is no explicit instruction on when to use this tool instead of alternatives or what context warrants the full analysis. Usage is implied rather than stated.
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.
Each tool targets a distinct domain: competitor intel, market regime, social trends, trading signals, token risk analysis, server health, and tool discovery. Even scan_token and scan_token_preview are clearly differentiated as full analysis vs. quick preview.
Four tools follow a consistent get_* pattern, and two follow scan_* pattern, but 'health' and 'list_tools' break the convention. Mixed verb styles and one bare noun reduce consistency.
Eight tools is well-scoped for a specialized crypto intelligence server, covering market analysis, social trends, competitor intel, and risk scanning without unnecessary bloat.
The core lifecycle of intelligence gathering and risk assessment is covered, including full and preview token scans. Minor gaps exist (e.g., no direct token metadata endpoint), but agents can work around them with existing tools.