Evaluate context against ordered rubric criteria to assign a calibrated score. Provide the state, scoring question, and rubric levels in ascending order for consistent rating.
Calibrated rubric scoring across ordered levels (e.g. 0 to 3 severity/quality).
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes | Context to evaluate | |
| criteria | Yes | Rubric descriptions in ascending order | |
| question | Yes | Scoring goal or metric |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral disclosure. It says 'calibrated rubric scoring' but does not state whether this is a read-only computation, whether it has side effects, or what kind of result it returns.
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 a single sentence with no filler and the core concept appears immediately. It is not over-padded, and every word contributes to the stated purpose.
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 three-parameter tool with no annotations and no output schema, this description is too thin. It leaves the agent to infer what a score looks like, how criteria map to levels, and what 'calibrated' means operationally.
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 100%, so the baseline is 3. The description's 'ordered levels' loosely reinforces the schema's ascending-order criteria, but it adds no new meaning about state, question, or criteria interpretation beyond what the schema already provides.
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 operation ('Calibrated rubric scoring') and its domain ('ordered levels'), so an agent can tell this is a scoring tool. However, it never contrasts itself with siblings like jev_decide_choice or jev_decide_noul, so the differentiation is only implicit.
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?
No explicit guidance is given about when to use this tool versus jev_decide_choice, jev_decide_noul, or other siblings. The phrase 'rubric scoring' implies a use case, but there are no exclusions, triggers, or alternative-selection hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.