generate_calc_paper

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

With no annotations, the description adequately covers behavioral details: deterministic seeding, constraint handling (carrying, division, fractions), fill_rows behavior, answer sheet toggle, and group labeling restrictions. It lacks explicit permission or side-effect information, but the generation nature implies safe operation.

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 verbose but structured with bullet points and emojis for readability. It front-loads the core purpose and then details parameters. Some repetition and informal formatting slightly reduce conciseness, but it remains efficient for the complexity.

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?

Given the absence of annotations and output schema details, the description covers all necessary aspects: input parameters, return format, constraints, and behavioral expectations. It provides sufficient context for correct invocation, even including a note for a 2026-07-19 specification.

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 description provides extensive parameter explanations beyond the schema, including defaults, valid values (e.g., type must be from list_calc_types), and nuanced behaviors (e.g., fill_rows rounding, with_answer default false for oral arithmetic). This fully compensates for the 0% schema description coverage.

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 generates a calculation paper PDF ('一键生成计算题卷') and specifies it's a deterministic program (not LLM), and distinguishes the default behavior for oral arithmetic (no answer sheet). It includes the output format and usage constraints, making the purpose unambiguous.

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 includes some usage guidance, such as referencing list_calc_types for valid types and noting default behaviors. However, it does not explicitly differentiate from sibling tools like generate_calc_items or compose_paper, nor does it state prerequisites or when not to use this tool.

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