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A skill/service for generating mindmaps from central topics, providing hierarchical concept graph generation
This server has a single tool with severe definition gaps. The tool has a basic name and minimal description, but the implementation is trivial (hardcoded output unrelated to input), lacks proper error handling, output schema documentation, and parameter descriptions. The codebase provides no evidence of MCP framework integration, it appears to be a standalone Python class with no visible MCP server implementation, protocol bindings, or transport layer. The tool name 'generate_mindmap' is a verb_noun structure (acceptable) but the description is too brief (37 chars, below the 50-char baseline for context). The input schema is present but the parameter 'central_topic' lacks a description. Most critically, the output is hardcoded and unrelated to the input ('Machine Learning' → ['Supervised', 'Unsupervised', 'RL']), indicating the tool does not actually implement its claimed function. No evidence of MCP server registration, prompts, resources, or protocol compliance.
Generates a mindmap for a given central topic
Tool description is too brief (37 chars) and lacks context for LLM selection. Per pattern:tool-description, descriptions should be 50-200 chars and answer WHAT, WHEN, and WHY.
Input parameter 'central_topic' has no description. Per pattern:tool-description, every parameter must have a non-empty description so the LLM understands what to pass.
Output schema is not documented. The tool returns a dict with a 'nodes' key, but there is no schema specification of the output structure, field types, or semantics. Per pattern:tool, the return type must be documented.
Implementation is hardcoded and does not actually use the input parameter. The tool always returns ['Supervised', 'Unsupervised', 'RL'] regardless of the central_topic passed, rendering the tool non-functional for its stated purpose.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 29 | 2026-07-28+ | v2 |
No MCP server integration detected. The codebase shows a standalone Python class with no visible MCP framework (asyncio, SSE, HTTP, or STDIO transport), no tool registration mechanism, and no protocol message handling. Cannot verify this is a functional MCP server.
No error handling or validation. The tool accepts any string for central_topic with no validation, bounds checking, or error guidance per pattern:recovery-guide.
No idempotence guarantee. The tool returns static output on every call, this may be idempotent by accident, but there is no explicit design or documentation of idempotence per pattern:idempotent-operation.