Content
71%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured process guide that sequences a multi-phase workflow with verification steps and cleanly offloads detail to verified one-level-deep reference files. The main weakness is conciseness — several justifications and obvious statements could be trimmed to respect the context budget.
Suggestions
Trim explanatory padding that assumes Claude's ignorance, e.g. the TypeScript rationale ('Plus AI models are good at generating TypeScript code, benefiting from its broad usage...') and obvious restatements like 'Error messages should guide agents toward solutions'.
Make the validation feedback loop explicit in Phase 3, e.g. 'If build/inspector reports errors: fix the reported issues and re-run until clean — only proceed when validation passes,' to push workflow clarity toward 5.
Inline one small end-to-end tool example (a minimal @mcp.tool / server.registerTool snippet with a Zod/Pydantic schema) so the body is self-contained for the common case rather than deferring all executable code to the reference files.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly an efficient process guide, but includes unnecessary explanation/padding such as the TypeScript rationale ('Plus AI models are good at generating TypeScript code, benefiting from its broad usage...') and a few obvious statements ('Error messages should guide agents toward solutions'), so it could be tightened rather than reaching 'lean and efficient'. | 3 / 5 |
Actionability | Concrete executable commands are present (`npm run build`, `npx @modelcontextprotocol/inspector`, `python -m py_compile your_server.py`), specific SDK features are named (Zod, `outputSchema`, `structuredContent`, annotation hints), and a copy-pasteable XML template is included; the gap is that most full code lives in reference files rather than inline. | 4 / 5 |
Workflow Clarity | A clear four-phase sequence (Research/Planning, Implementation, Review/Test, Evaluations) with numbered subsections and a build/inspect verification checkpoint in Phase 3; it falls short of 5 because the validate→fix→retry feedback loop is not stated explicitly. | 4 / 5 |
Progressive Disclosure | SKILL.md acts as a clear overview pointing to well-signaled, one-level-deep references (mcp_best_practices.md, node_mcp_server.md, python_mcp_server.md, evaluation.md) and scripts, all of which exist in the bundle; navigation is easy and content is appropriately split. | 5 / 5 |
Total | 16 / 20 Passed |