This server exhibits critical definition quality gaps across all four tools. All tools have empty input schemas ({}), no parameter descriptions, minimal tool descriptions (15-17 chars), and no documented output schemas. The tools are hardcoded to return literal strings with no context for when/why an LLM should call them. Per the rubric hard rules: tools with NO input schema must score 0 on schema; descriptions under 20 chars must score 0-20 on description. All four tools violate both rules. The naming convention (get_* verbs) is acceptable, but without schemas, descriptions, and error handling, the tools are barely usable by an agent.
Fetch ABC code
Fetch MCP code
Fetch XYZ code
Fetch company code
All tools have empty input schemas ({}). This prevents LLMs from understanding what parameters (if any) are accepted.
All tool descriptions are under 20 characters ('Fetch company code', 'Fetch ABC code', 'Fetch XYZ code', 'Fetch MCP code'). These descriptions lack context for WHEN to use each tool, WHAT differentiates them, and WHAT the agent should do with the returned code.
No output schema documented. The tools return hardcoded strings, but there is no formal schema describing the return type, structure, or meaning. LLMs cannot plan downstream operations or understand how to use the returned codes.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | F | 36 | 2026-07-28+ | v2 |
| 2026-03-09 | F | 0 | - | v1 |
Tool names are ambiguous and do not distinguish their purposes. 'get_companycode', 'get_ABCcode', 'get_XYZcode', 'get_MCPcode' provide no semantic clarity. The agent cannot determine which to call without external knowledge. Names like 'get_employee_company_code' or 'get_department_abc_identifier' would be clearer.
No error handling or recovery guidance. If a tool fails or returns an unexpected result, there is no mechanism to tell the LLM what to do next or how to self-correct.
Tools return hardcoded literal values ('#123456', '#ABC123', '#XYZ1237', 'MCP#123@456') with no context. It is unclear what these codes represent, why an agent would need them, or how to use them in downstream operations.