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edubase_post_exam_summary

Submit an AI-generated exam summary to EduBase by specifying the exam ID and summary text, with optional language and model details.

Instructions

Submit a new AI exam summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
examYesexam identification string
languageNosummary language
typeNotype of summary (default: ai)
summaryYessummary text (basic HTML formatting allowed, keep concise, avoid personal information)
llmNoname of the Large Language Model used to generate the summary (preferred: openai / claude / gemini)
modelNoexact LLM model name used to generate the summary (requires llm)
Behavior2/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds no behavioral context beyond 'Submit'. It does not explain side effects (e.g., whether existing summaries are overwritten), required permissions, or rate limits. The openWorldHint=true suggests external factors, but the description offers no clarification.

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

Conciseness4/5

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

The description is a single sentence, making it very concise. However, it is too minimal, sacrificing needed detail. A slightly longer description that front-loads key constraints would be ideal. It earns its place but could be more informative without significant added length.

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

Completeness2/5

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

Given the tool has 6 parameters (2 required) and no output schema, the description is insufficient. It does not explain the purpose of optional parameters like 'language', 'type', 'llm', or 'model', nor the relationship between 'llm' and 'model'. The schema description for 'summary' already mentions HTML and personal information, but the tool description should summarize these constraints. The lack of output schema means the description should hint at return values, which it does not.

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 the schema already documents all parameters. The description adds no extra meaning beyond the schema. For example, the 'llm' and 'model' parameters have schema descriptions that are adequate. Thus, baseline score of 3 is appropriate.

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 ('Submit') and the resource ('a new AI exam summary'). The tool name 'edubase_post_exam_summary' aligns with the description, and it is distinct from sibling tools like 'edubase_post_exam' which likely creates the exam itself. However, it does not elaborate on what constitutes an 'AI exam summary' or how this differs from other summary actions.

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

Usage Guidelines2/5

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

No usage guidance is provided. The description does not indicate when to use this tool, such as prerequisites (e.g., the exam must exist) or situations where alternatives might be preferred. The sibling tools are not differentiated, leaving the agent without context for selection.

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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