score

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

With no annotations provided, the description carries the full burden and does a good job: it explains the fractional 0-based index semantics, confidence, per-level probabilities, and the full JSON return shape. It could add side-effect or read-only clarity, but for a grading tool the described behavior is unusually well disclosed.

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 well organized with an introductory sentence followed by Args and Returns sections. It is reasonably tight, though a few phrases like 'Ask Jev' and 'The official score question type' add flavor without much technical value. Overall, every major 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?

The description covers all three parameters, return values, constraints, and an example. Since an output schema exists, the detailed return enumeration is a bonus. The main missing piece is explicit guidance on choosing this over sibling tools, but the tool is otherwise complete enough to call correctly.

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 0%, so the description must compensate, and it does: 'question' is explained with an example, 'levels' is constrained to 2-8 unique ordered scale points low-to-high, and 'context' is marked optional with usage guidance. This adds meaning 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 description states a specific action and resource: 'Ask Jev (TypeSafe System One) to grade something on an ORDERED scale of 2-8 levels.' It clearly identifies the 'official score question type' and gives concrete examples like risk/severity/quality rubrics. This makes it easy to distinguish from siblings such as classify or choice because the ordered-scale scoring semantics are explicit.

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 gives clear context for when to use the tool: grading on an ordered scale, with examples and a concrete question phrasing. It does not explicitly mention alternatives or when not to use it, but the contrast with classification-style tasks is strongly implied by the ordered-levels emphasis.

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