query_preview_student_paper

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

No annotations are provided, so the description bears full burden for behavioral disclosure. It only mentions what the tool returns, but does not disclose that it is a read-only operation, any authentication requirements, rate limits, or potential side effects. This is insufficient for a tool with no output schema or annotations.

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, efficient sentence that conveys the core purpose and output without any redundancy. It is front-loaded with the step context, making it easy to scan.

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?

Despite 7 parameters and no output schema or annotations, the description is minimal. It does not explain the return format beyond two IDs, or how this tool fits into the larger grading workflow (e.g., relationship to submit_student_mark). More detail is needed for complete understanding.

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?

The input schema has 100% coverage with descriptions for each parameter, including their source (e.g., from query_teacher_groups). The description adds no parameter-specific information beyond what the schema already provides, so it meets the baseline without adding value.

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 clearly states the tool's purpose: querying a single student's complete answer content, and identifies it as step 2 in grading. It specifies the returned data (mark_paper_record_id and answer_ids) needed for scoring, distinguishing it from sibling tools like query_test_result or query_paper.

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 provides implicit usage context by labeling it as 'step 2 in grading' and noting the returned IDs are required for scoring. However, it does not explicitly state when not to use this tool or compare it to alternatives such as query_test_result, limiting its guidance for selection.

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