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

Annotations already cover read-only/non-destructive safety, but the description adds genuinely new behavioral context: each lookup consumes paid X credits, so call volume has a real cost. It also discloses scope (public market data about the whole market, not the caller's wallet). It does not address why idempotentHint=false on what looks like a pure read, nor caching/freshness of the profile — a small remaining gap.

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 core value proposition and the cost warning are front-loaded in the first two clauses. The closing sentences about get_my_* tools are somewhat tangential to this tool's function, but they earn their place by preventing a common sibling-selection error.

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?

Output schema exists, so return values need no explanation, and annotations plus the cost note cover behavior well. What's missing is the one thing the schema can't supply: what token_address should look like and whether any preconditions apply. Adequate, but with a clear parameter-level hole.

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 0% and the description never mentions token_address or network. For a 2-param tool where one parameter is the sole required input, the agent gets no guidance on format (mint address vs. symbol) or on the solana-only const. The description leaves all parameter meaning to bare titles.

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?

States a specific verb+resource (the project's X/Twitter account) and enumerates what it returns: follower count, age, verification. The framing question ('is this project's social presence real or a two-day-old burner') makes the purpose unmistakable and separates it from token-market siblings like get_token_overview or get_token_risk_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?

Gives an explicit when-not ('Not for routine enrichment of every token in a list') plus an operational constraint ('CALL SPARINGLY'). It also routes the agent away from the whole get_my_* family by naming that prefix as the alternative for user-owned data, which is a concrete disambiguation rule rather than an inference.

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