Content
75%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, actionable instruction-only skill with concrete MCP tool guidance, a complete JSON example, and an explicit verification step. It sits just below the top band due to mild section redundancy, one vague sub-step, the absence of a retry feedback loop, and no progressive split into bundle files.
Suggestions
Tighten redundancy: fold "Core Principles" into the workflow steps or "When to Use" so each idea appears once.
Make Step 2 concrete by specifying the create-ai-config parameters and what a "variation" entails, or link to a reference for config creation.
Add an explicit feedback loop to Step 4, e.g. "If get-agent-graph shows a wrong edge, update via update-agent-graph and re-verify before reporting."
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is efficient and the product-specific model explanation is earned, but the "Core Principles" section restates the workflow and overlaps with "When to Use", leaving minor trimmable redundancy. | 4 / 5 |
Actionability | Named MCP tools with full parameter lists and a copy-paste JSON example make the core flow executable, but Step 2's "Set up variations with appropriate models and prompts" is vague, a minor gap. | 4 / 5 |
Workflow Clarity | A clear 4-step sequence ends in a dedicated Verify step with four concrete checks, but there is no explicit validate→fix→retry feedback loop, which the top anchor requires. | 4 / 5 |
Progressive Disclosure | Sections are well-organized with one clearly signaled external doc link and no nested references, but all content is inline in a ~145-line file with no split into separate reference files. | 4 / 5 |
Total | 16 / 20 Passed |