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edubase_post_quiz_grading_preset

Create custom quiz grading presets by selecting type, title, and thresholds to assign grades based on result percentages.

Instructions

Create a new custom grading preset. Needs the custom grading feature to be enabled.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYestype of the grading preset (custom: freely named grades, at least 2 items - go-nogo-custom: successful/unsuccessful grading with a custom threshold, exactly 2 items - hungarian-school: Hungarian primary and secondary school grading (1-5), exactly 5 items - hungarian-university: Hungarian university grading (1-5), exactly 5 items)
titleYestitle of the grading preset
gradesYesthresholds and grades of the preset, in ascending order
languageNolanguage of the grading preset (default: content language of the API application owner)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
presetYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv2.0.0
    • removedOutput schema / properties / preset / description
      Removed value: -"grading preset identification string"
  2. Addedv1.2.15

TDQS

A3.5/5.0
Behavior3/5

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

The annotations indicate readOnlyHint=false (mutation) and destructiveHint=false, but the description adds a specific behavioral requirement: the custom grading feature must be enabled. This is valuable context not captured by annotations. However, it does not describe side effects, validation failures, or the response format beyond what the output schema covers. The added prerequisite is useful but the overall behavioral disclosure remains sparse.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the purpose and then states the prerequisite. It is concise, with no filler words, and every part adds value. It is appropriately sized for a tool with a rich schema that carries most of the details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The schema and annotations are quite detailed, covering parameters, types, and read-only/destructive hints. The description adds the feature requirement but does not clarify that non-custom preset types are also possible, nor does it explain the implications of the 'custom grading feature' requirement (e.g., what happens if disabled). Given the complexity of the tool (4 parameters, 3 required) and the rich schema, the description is adequate but not fully complete; it leaves the agent to infer some context from the schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so each parameter already has a detailed description in the schema. The tool description does not mention any parameters or add meaning beyond the schema. According to the rubric, a high coverage baseline is 3, and the description adds no additional parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: 'Create a new custom grading preset.' It uses a specific verb and resource, and the sibling list shows other operations (get, patch, delete), so the create intent is unambiguous. However, the word 'custom' is slightly misleading because the 'type' parameter accepts non-custom types (hungarian-school, hungarian-university), so the purpose is not perfectly aligned with the full scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a prerequisite: 'Needs the custom grading feature to be enabled.' This gives some context on when the tool can be used. However, it does not explicitly state when to prefer this over the patch/delete/get siblings, nor does it mention that it is the only way to create a new preset. The usage is implied rather than explicitly contrasted with alternatives.

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

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