MCP server that generates Claude Code skill files from any documentation URL or GitHub repo — create, test, and iterate on skills for Claude Code, Cursor, and Windsurf
Server has 6 tools with basic descriptions and input schemas present. However, critical gaps undermine quality: (1) parameter descriptions are minimal or absent, most params lack detail on format, constraints, or expected values; (2) output schemas are not documented anywhere in the source; (3) error handling is not visible, no recovery guidance or error categorization; (4) descriptions are functional but generic, averaging ~60 chars, below the 194-char baseline for A+ tools; (5) no tool annotations (readOnlyHint, destructiveHint) despite clear risk levels (WRITE vs READ_ONLY). Tools like 'save_skill' and 'generate_skill' modify state but lack confirmation/dry-run patterns. Parameter naming is reasonable (skill_name, documentation, content) but lacks type suffixes where ambiguous. Overall, definitions are present but sparse, typical of a C-grade community server.
Fetch and parse a documentation page from a URL
Fetch documentation from a GitHub repository using the GitHub API
Generate a Claude Code skill file from documentation content
Get the full skill-creator skill instructions and resources
Read an existing skill file
Save a generated skill file to disk
No output schemas documented. Tools return data but LLMs cannot infer response structure, forcing guesswork on field names and types. Breaks downstream tool chaining.
Parameter descriptions are minimal or absent. 'skill_name', 'documentation', 'content', 'extra_files' lack format constraints, length limits, or usage guidance. LLMs cannot validate inputs before calling.
No error handling or recovery guidance visible. Tools that write to disk (save_skill) or fetch external content (fetch_doc_page, fetch_github_repo) can fail, but no error messages or retry logic documented.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 41 | 2026-07-28+ | v2 |
Destructive tools (save_skill, generate_skill) lack confirmation or dry-run patterns. Agents can overwrite existing skills without safeguards.
Tool annotations missing. Despite clear risk levels (READ_ONLY vs WRITE), no readOnlyHint or destructiveHint metadata present. LLMs cannot distinguish safe from risky operations.