Content
82%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, highly actionable generation workflow with complete JSON-LD templates and an explicit validation checklist. It is slightly verbose in places and lacks an explicit fix-and-retry feedback loop for error recovery.
Suggestions
Trim the "@graph pattern benefits" bullet list and redundant explanatory prose (e.g., that Google/AI systems parse @graph arrays) to tighten conciseness.
Add an explicit validate→fix→re-validate feedback loop in Step 8 so validation failures drive correction rather than just warnings.
Consider moving the per-surface support status table into a reference file to keep the core workflow lean and improve progressive disclosure.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is largely efficient and code-heavy, but the "@graph pattern benefits" bullet list and some explanatory prose (e.g., restating that Google/AI parse @graph arrays) could be trimmed, fitting efficient-with-minor-over-explanation rather than lean. | 4 / 5 |
Actionability | Full copy-paste-ready JSON templates for every entity type, a concrete 8-item validation checklist, and explicit script-safety escaping guidance (replace `</` with `<\/`, `<` with `\u003c`) cover the common cases fully. | 5 / 5 |
Workflow Clarity | A clear 9-step sequence with an explicit validation checklist in Step 8, but it prescribes validate-and-warn rather than an explicit validate→fix→re-validate feedback loop, so it stops short of the top anchor. | 4 / 5 |
Progressive Disclosure | Content is well-organized into clearly headed steps with templates appropriately inline for a generation skill; no bundle files exist and no nested references are present, giving good structure with no organization gaps rather than the one-level-deep-reference top anchor. | 4 / 5 |
Total | 17 / 20 Passed |