MCP server for Go code review using Google and Uber Go style guides with live-fetched content and curated guidelines
Three tools with complete schemas and descriptions, but descriptions are generic and lack LLM-optimized guidance. All tools are read-only with proper enums for constrained inputs. Missing output schema documentation, error handling guidance, and parameter relationship documentation. Tool names follow verb_noun pattern correctly. No security or composition issues detected.
Get all Go language style guide content related to a specific topic from all live-fetched guides. This tool is specifically for Go code review only.
Get curated Go language code review guidelines covering major topics. This tool is specifically for Go code review only.
Search through all live-fetched Go language style guides for specific topics or patterns. This tool is specifically for Go code review only.
Output schemas not documented. LLMs cannot plan downstream operations or extract structured data from responses. Tool handlers return CallToolResult but response structure is not declared in tool definitions.
Descriptions lack LLM-optimized guidance. All three descriptions are 100-120 chars and generic ('Search through...', 'Get all...'). Missing WHEN to use, prerequisites, and what to expect. Baseline for A+ tools is 50-200 chars with explicit context.
Parameter descriptions are minimal. 'query' in search_live_guide is described as 'Search query to find in Go style guide content' (56 chars), lacks format guidance, example patterns, or length constraints. Baseline is 72 chars average for A+ tools.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 59 | 2026-07-28+ | v2 |
No error handling guidance in tool descriptions. Handlers return CallToolResult but descriptions do not explain failure modes, recovery steps, or when to retry. Pattern: recovery-guide missing.
Tool composition not optimized for chat data model. All three tools require exact enum values ('naming', 'errors', etc.) but descriptions do not explain what each topic covers or when to choose one over another. LLMs may guess wrong between similar tools.