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

Annotations are empty, so the description carries the burden. It discloses that the tool uses an ML ensemble and returns a comprehensive risk profile, which is useful. However, it does not disclose potential side effects (e.g., rate limits, cost, latency, whether it writes data, or whether it requires external API calls). It also doesn't mention what 'temporal prediction' means in practice. The description is honest about what it returns but lacks behavioral depth.

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, information-dense sentence that front-loads the core purpose and then lists outputs. It earns its place with concrete details (score range, risk level, rug stage, honeypot detection, risk flags, temporal prediction). Slightly verbose with 'Full' and 'using an ML ensemble' but still efficient.

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 single-parameter tool with no output schema, the description is quite complete: it tells the agent what input is needed (mint) and what outputs to expect. The main gap is the lack of guidance on when to choose this over scan_token_preview, and no mention of any constraints (e.g., rate limits, token type). Given the tool's simplicity, this is a strong but not perfect definition.

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?

Schema description coverage is 100%, so the schema already documents the only parameter (mint) as 'Solana token mint address (base58)'. The description adds no additional parameter semantics beyond the schema. Baseline 3 is appropriate because the schema does the heavy lifting and the description doesn't need to compensate.

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: 'Full DrainBrain risk analysis for a Solana token using an ML ensemble.' It specifies the resource (Solana token), the action (scan/analyze), and the method (ML ensemble). It also lists concrete outputs (score 0-100, risk level, rug stage, honeypot detection, risk flags, temporal prediction), which distinguishes it from siblings like scan_token_preview and get_trading_signals.

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: when you need a full risk analysis of a Solana token. However, it does not explicitly state when to use this tool versus scan_token_preview or get_trading_signals. The sibling list includes scan_token_preview, which likely offers a lighter/faster check, but the description doesn't draw that contrast. The context is clear enough for a full analysis, but exclusions/alternatives are not stated.

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