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

With no annotations, the description carries full behavioral disclosure. It reveals the score range, transparent components, confidence definition, and the policy of returning 'unknown' over guessing. It also includes a disclaimer that it is not financial advice. This is exemplary transparency for a tool with no annotation support.

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 information-dense but not bloated; each sentence contributes distinct value (purpose, components, use case, behavior, disclaimer, requirement). It front-loads the core purpose and stays focused, though slightly 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?

For a single-parameter tool with no output schema, the description covers all essential aspects: output format, behavioral nuances, and invocation requirement. An agent can confidently decide to call this tool and understand what to expect. Nothing critical is missing.

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 is 100%, so the schema already documents the mint parameter thoroughly. The tool description only repeats the requirement without adding new semantics beyond the schema's own description and example. Per the rubric, 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 clearly identifies the tool's function: computing a 0-100 safety score for an SPL token, with explicit components and output characteristics. It distinguishes itself from siblings by positioning as the 'cheap, high-frequency score behind /v1/decision' and noting it is 'verdict-free', which separates it from decision-oriented tools like solmachina_decision.

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 states when to use it ('for agents that just want the number') and hints at its role relative to /v1/decision, but it does not explicitly name alternative tools or exclusion conditions. The requirement for a mint parameter is clear, and the 'verdict-free' note implies not for full decisions. Overall, context is provided but not exhaustive.

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