A Java Agent CLI like Claude Code - AI programming assistant with desktop and CLI interfaces
Wraith exposes 2 tools for resource discovery and reading. Both tools have descriptions in Chinese, but they are minimal (under 100 chars) and lack critical details about when to use them, what they return, and error handling. Input schemas are present but sparse: list_resources has an empty properties object (no parameters), and read_resource has only a uri string parameter with minimal description. No output schemas are documented. No error handling guidance, no parameter validation rules, and no indication of pagination or result limits. The tools appear to be meta-tools for introspecting the MCP server itself rather than domain-specific functionality.
列出 MCP server 暴露的 resources,返回 URI、名称、MIME 类型和描述
读取 MCP resource 内容。参数 uri 必须来自 list_resources 或用户明确提供的 resource URI
Descriptions are minimal and in Chinese; lack WHAT/WHEN/WHY context. 'List MCP server exposed resources' (translated) does not explain when an LLM should call this vs other discovery tools, what structure is returned, or how to use results downstream.
No output schemas documented. LLMs cannot plan downstream calls or extract required fields (e.g., resource URIs from list_resources) without knowing the response structure.
read_resource parameter 'uri' has minimal description ('要读取的 MCP resource URI'). No guidance on format, valid values, or what happens if URI is invalid. No error recovery hints.
No error handling or recovery guidance. If read_resource fails (invalid URI, permission denied, resource not found), LLM has no actionable next step.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 42 | 2026-07-28+ | v2 |
list_resources returns no parameters but likely returns a list. No pagination, limit, or result count documented. Large resource lists could blow context window.