Deep Solana liquidity-pool analysis for a token

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

Discloses all key behavioral aspects: real fee APR calculation, wash-trade risk checks, rug verdict, slippage ladder, recommendation. Also states it's paid ($0.04). With no annotations, description carries full burden and does it well.

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?

Concise paragraph front-loaded with purpose. Every sentence adds distinct information. No fluff.

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?

No output schema, but description lists all key outputs. Covers enough for an agent to understand return value. Could include response format or example but not necessary given brevity.

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 coverage 100% with good descriptions. Description adds context: mint example, optional trade sizes with default values. Adds value beyond schema without redundancy.

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 states specific verb 'analyze' and resource 'liquidity pools' across multiple DEXes. Lists detailed outputs (fee APR, wash-trade risk, rug verdict, slippage ladder, recommendation), distinguishing it from siblings like 'top_pools' or 'scan_honeypot'.

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?

Implies use for deep analysis and risk assessment, mentions paid nature. No explicit when-not or alternatives, but context makes intended use clear.

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