Skip to main content
Glama

interview

Read-onlyIdempotent

Clarify vague requirements through structured questioning, generating interview records to guide feature development and prevent misunderstandings.

Instructions

当用户需求不明确、需要澄清需求时使用。需求访谈工具,在开发前通过结构化提问澄清需求,避免理解偏差和返工;生成访谈记录文件供后续 start_feature/add_feature 使用;仅支持 feature 类型

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
answersNo访谈问题的回答(JSON 对象,key 为问题 ID,value 为回答内容)。用于提交访谈结果
descriptionNo功能描述(如'实现用户登录功能'),用于开始访谈。可以是简短的自然语言描述
feature_nameNo功能名称(kebab-case 格式,如 user-login)。可选,会自动从描述中提取
Behavior1/5

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

The description claims the tool generates interview record files (side effects), but annotations declare readOnlyHint=true and idempotentHint=true, which imply no state changes. This is a direct contradiction, severely undermining transparency. Without annotations, the description itself would provide some behavioral context, but the contradiction makes it misleading.

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 that packs essential information: use case, function, output, and type constraint. It is concise but could be better structured (e.g., separate sentences for clarity). Still, it efficiently conveys key points.

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?

The tool has a nested object parameter ('answers') and no output schema. The description fails to explain the structure of the interview answers or the format of the generated record file. It mentions the output is used by other tools but lacks details needed for correct invocation and understanding the tool's full behavior.

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 coverage is 100%, so the baseline is 3. The description does not add significant meaning beyond the schema descriptions for 'answers', 'description', and 'feature_name'. It mentions that 'answers' are for submitting results and 'description' starts the interview, but this is already captured in the schema.

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 tool's purpose: clarify requirements through structured questions when they are unclear. It specifies that it generates interview record files for subsequent tools and only supports 'feature' type. While it lacks explicit differentiation from sibling tools like 'ask_user', the purpose is well-defined.

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

Usage Guidelines4/5

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

The description explicitly states when to use: when user requirements are unclear and need clarification. It also mentions the output is used by start_feature/add_feature, indicating the tool's place in the workflow. However, it does not provide when-not-to-use scenarios or alternative tools.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mybolide/mcp-probe-kit'

If you have feedback or need assistance with the MCP directory API, please join our Discord server