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

No annotations are present, so the description carries the transparency burden. It clearly describes the informational output and recommendations, which implies a read-only analysis tool, but it never explicitly states that no orders or state changes occur, nor does it mention data freshness or error behavior. This is adequate but not fully transparent.

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 purpose is front-loaded, followed by a dense but relevant list of return metrics and a workflow pointer. No filler or repetition of the title/schema, though the metric list makes it longer than strictly necessary.

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?

With no output schema, the description compensates by detailing per-quote metrics, overall stats, and plain recommendations, giving an agent a solid mental model of the response. Combined with fully schema-documented optional parameters, the information is nearly complete; only operational details like freshness or non-mutating guarantees are absent.

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 describes all four optional parameters with enums and meanings, so the description does not need to restate them. It adds helpful output-context terms like demand score and survival, but does not materially deepen the meaning of the parameters themselves; baseline 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?

The description opens with a concrete purpose: deciding what to launch on StonkFun and against which quote asset. It enumerates the computed metrics and distinguishes itself from siblings by naming stonk_pairs and stonk_preflight, so an agent can tell when this tool applies.

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?

It gives an explicit workflow instruction: 'Use BEFORE stonk_pairs / stonk_preflight when deciding what to launch.' This tells the agent both when to use it and which sibling tools come later, eliminating ambiguity about orchestration.

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