fast_score

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

With no annotations, the description must carry behavioral disclosure, and it does add useful context by explaining that the tool returns a score, probability distribution, and confidence, and that confidence_floor is a threshold. It does not address side effects, failure modes, or nondeterminism, but for a stateless rating tool the disclosed behavior is not dangerously incomplete.

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?

Structured into purpose, usage, args, and returns with no filler; the main use case is front-loaded in the first line and each section earns its place.

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?

Four parameters are fully documented, the return shape is explicitly stated, and an output schema exists, so the agent has enough to invoke the tool correctly. It loses a point only because the relationship to fast_judge/fast_verify and the precise effect of confidence_floor on is_confident are left implicit.

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%, so the description must compensate, and it does. Each parameter is explained in plain terms: question gets an example, levels gets an ordering constraint and minimum length, content gets accepted types, and confidence_floor gets a default and purpose. This goes well beyond the bare schema.

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 first sentence states a specific action ('Rate content along a defined scale with ordered levels') and lists concrete use cases (severity, quality, relevance, complexity), so an agent knows what the tool does. It does not explicitly contrast with siblings such as fast_judge or fast_verify, so it misses the top marker for sibling differentiation.

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 says explicitly to 'Call this for severity, quality, relevance, complexity, or any custom rating', giving clear criteria for when to use it. It does not name alternatives, exclusions, or conditions for using fast_judge/fast_verify, so it lacks the when-not/alternative guidance needed for a 5.

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