Content
65%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A highly actionable, well-structured skill body with concrete commands and a clear five-step workflow. Weaknesses are moderate verbosity from inline templates that overlap references and a broken example link, plus validation that lacks an explicit retry loop.
Suggestions
Fix or remove the broken reference to examples/opc-skills-case-study.md (the examples/ directory does not exist).
Move the inline FAQPage JSON and meta-tags HTML template into references/schema-templates.md and link to them, keeping the body lean.
Add an explicit validation feedback loop in Step 5 (e.g., 'if the Rich Results Test reports errors, fix the schema and re-run') to lift workflow clarity.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly actionable tables and commands, but inline blocks (full meta-tags HTML template, FAQPage JSON, report template) duplicate material that references/schema-templates.md is meant to hold, adding tokens that could be deferred. | 2 / 3 |
Actionability | Provides copy-paste-ready executable commands (`python3 scripts/seo_audit.py`, curl checks, `open` validator URLs) plus concrete JSON-LD and meta-tag templates — fully concrete rather than abstract. | 3 / 3 |
Workflow Clarity | Steps 1–5 are clearly sequenced with a Step 5 validation section and checklists, but validation is manual 'open this URL' style with no explicit fix-and-revalidate feedback loop on failure. | 2 / 3 |
Progressive Disclosure | References are well-signaled and one level deep (geo-research.md, schema-templates.md, platform-algorithms.md, etc. all exist), but references/opc-skills-case-study.md points to a missing examples/ directory and schema content is inlined rather than split out. | 2 / 3 |
Total | 9 / 12 Passed |