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lychee20000105

wechat-miniapp-engineering-mcp

miniapp_project_map

Generate a visual map of a WeChat mini-program project, including pages, files, cloud functions, and their dependency relationships, to understand code structure and connections.

Instructions

借鉴 Understand-Anything 的知识图谱思路,生成本地小程序项目地图:页面、文件、云函数、集合和依赖边。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathNo小程序项目根目录,默认读取配置里的当前项目。
limitNo最多扫描多少个安全文本文件,默认 700。
formatNo默认 markdown;json 返回轻量图谱数据。
detail_levelNo输出详细程度,默认 standard。
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states it 'generates a map' implying a read operation, but does not mention permissions, resource usage (e.g., scanning many files), or whether it modifies the project. The agent cannot determine side effects or constraints.

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, concise and front-loaded. It begins with a reference to Understand-Anything which, while informative, adds slight overhead. Overall, it is efficient and to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description should explain return values, but it only lists components ('pages, files, cloud functions, collections, and dependency edges'). The format parameter covers output format. However, the description lacks scope, performance implications, and explicit read-only nature. It is adequate but not comprehensive for a tool with 4 parameters and many siblings.

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% with each parameter having a description. The tool description adds high-level context (knowledge graph approach, types of elements) but does not provide additional meaning beyond the schema for any parameter. Baseline 3 is appropriate as the schema already documents what each parameter does.

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 it generates a project map with specific components (pages, files, cloud functions, collections, and dependency edges) using a knowledge graph approach. It differentiates from siblings by mentioning a broader set of elements, but does not explicitly distinguish from similar tools like miniapp_dependency_diagram.

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

Usage Guidelines2/5

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

No usage guidance is provided. The description does not indicate when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. This forces the agent to infer context from the tool name and parameters.

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

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