compose_xingce_answer_prompt

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

With no annotations, the description carries full burden. It discloses that the tool is non-destructive (composes a prompt, no side effects) and specifies what it does not do. However, it does not explain the 'conservative' nature or describe the safety contract in detail, and behavioral traits like idempotency or error handling are missing.

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 three concise sentences with no fluff. It front-loads the main purpose, adds detail on parameters, and ends with exclusions. Minor improvement could be structure with bullet points, but it is efficient for the content.

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 11 parameters, 0% schema coverage, no annotations, but an output schema exists (not shown). The description mentions returning an answer_prompt with constraints, but lacks detail on most input parameters and does not describe the output schema's fields. This leaves significant gaps for an agent to use correctly.

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 0%, yet the description only mentions module_hint and section_context, leaving 9 parameters (e.g., question_text, options, image_present, strict_mode, allow_answer, etc.) unexplained. This fails to add meaning beyond the schema for most parameters, despite the high parameter count.

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 it composes a 'conservative answer prompt' for LLM-in-the-loop answering, mentions specific parameters like module_hint and section_context, and explicitly lists what it does not do (answer questions, call external LLM, select options). This provides a specific verb and resource, but does not explicitly distinguish from sibling compose tools like compose_xingce_analysis_prompt, though the 'conservative' hint differentiates somewhat.

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 indicates when to use module_hint and section_context for routing by exam section context, and states negative behavior (does not answer, call LLM, select options), implying when not to use. However, it lacks explicit guidance on when to choose this tool over siblings like compose_xingce_analysis_prompt or route_xingce_question.

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