record_socratic_answers

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that data is recorded to 'data_trap.jsonl' and for training data collection with user consent, but it lacks details on file handling (e.g., appending vs. overwriting), error conditions, permissions needed, or rate limits. For a tool that writes data without annotation coverage, this is a significant gap in transparency.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by usage context and parameter details. It avoids redundancy, with each sentence adding value (e.g., explaining parameters and returns). However, the structure could be slightly improved by separating usage guidelines more clearly from parameter semantics.

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 complexity (4 parameters, no annotations, 0% schema coverage, but has an output schema), the description is moderately complete. It covers the purpose, basic usage, parameters, and return value ('記錄狀態'), but lacks behavioral details like file operations or error handling. The output schema existence reduces the need to explain returns, but without annotations, more context on data mutation and safety is needed for full completeness.

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 lists all 4 parameters (requirement, questions, answers, framework) with brief explanations, but the input schema has 0% description coverage. The description adds some semantic context (e.g., '原始需求' for requirement, '問題列表（JSON字符串）' for questions), but it doesn't fully compensate for the schema gap—details like JSON structure, format constraints, or the meaning of 'framework' are unclear. With 4 parameters and low schema coverage, the baseline is 3 as the description provides basic but incomplete parameter info.

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: '記錄蘇格拉底面試的答案到 data_trap.jsonl' (records Socratic interview answers to data_trap.jsonl). It specifies the verb ('記錄' - record) and resource ('答案' - answers), and mentions the target file. However, it doesn't explicitly differentiate this from sibling tools like 'analyze_requirement_trap' or 'mmla_create_node', which could have overlapping data collection functions.

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 minimal usage guidance: '用於訓練數據收集（如果用戶允許）' (for training data collection if the user allows). This implies a context of data collection with user consent, but it doesn't specify when to use this tool versus alternatives like 'analyze_requirement_trap' or other sibling tools. No explicit when-not-to-use scenarios or prerequisites are mentioned.

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