Content
81%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 highly actionable, well-sequenced editing framework with concrete tooling and examples. The main weakness is conciseness — significant redundancy across the sweeps, checklist, and problems-and-fixes sections — plus one orphaned reference file.
Suggestions
Consolidate the overlapping coverage of the seven dimensions: keep the detailed sweeps, and either drop or sharply shorten the 'Copy Editing Checklist' and 'Common Copy Problems & Fixes' sections that repeat the same material.
Link references/ai-detection-patterns.md from the AI-Pattern Check section so the existing bundle file is discoverable rather than orphaned.
Consider moving the word-, sentence-, and paragraph-level Quick-Pass tables into references/plain-english-alternatives.md (or a dedicated reference) to slim the SKILL.md overview.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly useful but structurally redundant: the seven sweeps are detailed, then re-stated as a checklist, then partly re-stated in 'Common Copy Problems & Fixes,' plus overlapping Quick-Pass checks. Could be tightened without losing value. | 3 / 5 |
Actionability | Provides executable commands (readability_scorer.py, ai_content_detector.py with --json), concrete before/after tables, a worked So-What example, and specific per-sweep steps that cover the common cases. | 5 / 5 |
Workflow Clarity | The seven sweeps are a clearly sequenced multi-step process with explicit feedback loops ('After this sweep: Return to…'), validation (re-run the scorer; Flesch must improve), and an accompanying checklist. | 5 / 5 |
Progressive Disclosure | Clear section structure with a References entry and inline script invocations, but references/ai-detection-patterns.md is not surfaced from the body and some inlined material (quick-pass checks) could live in reference files. | 4 / 5 |
Total | 17 / 20 Passed |