Centralized MCP Server — Serve AI skills & rules from a GitHub repo
Three tools with strong naming conventions (get_rules, list_skills, get_skill) and generally clear descriptions. All tools have descriptions and basic parameter schemas using Zod. However, output schemas are not formally documented in the server registration, and parameter descriptions contain example values (a pattern violation). Tool composition is sound, each tool has a single responsibility and names follow verb_noun convention. The server properly validates inputs (max_results 1-20) and returns structured text responses.
Get coding rules and best practices relevant to the current context. Pass the file path you're working on, and/or tags like 'testing', 'security'. Returns only matching rules to save context tokens.
Get a specific skill by name.
List all available skills with descriptions and tags.
Parameter descriptions contain example values (e.g., 'src/components/Button.tsx', 'testing', 'security'), LLMs may reuse examples literally rather than adapt to context
Output schema not formally documented, tool descriptions state what is returned in text form, but no structured schema definition is visible in tool registration. LLMs cannot reliably parse response structure.
get_skill returns a 'not found' text response rather than a structured error with recovery hints. Description lacks guidance on when this tool should be used vs list_skills.
Parameter names use underscores (file_path, max_results) but descriptions use inconsistent terminology ('current file path' vs 'max skills to return'). 'max_results' param description says 'Max skills' but tool is called get_rules, terminology mismatch may confuse LLMs.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | C | 63 | 2026-07-28+ | v2 |
| 2026-03-09 | D | 55 | - | v1 |