Content
85%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.
This is a strong, highly executable audit skill: concrete grep patterns with verification steps, a clear five-phase workflow with validation checkpoints, and a copy-paste output template. The main weakness is structure — everything lives in one long SKILL.md with no bundle files, where the 12-pattern detection catalog and cross-reference tables are natural candidates for a one-level-deep references file.
Suggestions
Move the 12 detection patterns into a references/patterns.md (or split by severity) and keep a one-line index of pattern names in SKILL.md, so the main file stays a navigable overview.
Consider moving the Phase 3 completeness table and Phase 4 compound-severity matrix into the same reference file — they are lookup material the auditor consults after scanning, not upfront instructions.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and assumes SwiftUI competence — pattern entries like "GeometryReader has no intrinsic size, so a stack gives it the space left after fixed-size siblings" convey non-obvious facts in one line. It stays at anchor 4 rather than 5 because the five invocation examples, the 'why it matters' column in Phase 3, and some repeated iOS-26/27 resizing rationale across sections could be trimmed without losing guidance. | 4 / 5 |
Actionability | Every detection pattern ships an exact grep regex (e.g. `\.frame\(width:\s*\d{3,}`, with explicit caveats about what the regex over-matches and how to Read-verify), fixes include copy-paste code (`.containerRelativeFrame(.horizontal) { w, _ in w * 0.5 }`), and the output format is a complete fill-in markdown template with per-issue fields. | 5 / 5 |
Workflow Clarity | Five phases are clearly sequenced with an explicit checkpoint ("Present this map in the output before proceeding") and validation throughout: "use Read to verify the surrounding context before reporting", a dedicated False Positives section, and output limits for large findings. The operation is read-only auditing, so the destructive-operation cap does not apply. | 5 / 5 |
Progressive Disclosure | The body is well-sectioned but entirely monolithic — no references/, scripts/, or assets/ bundle files exist, and all 12 detection patterns, the Phase 3/4 tables, and scoring rubric are inlined in one 300+ line file. The only pointers ("axiom-swiftui skills/toolbars.md, skills/iphone-duo.md") target an external skill not in this bundle. This matches anchor 3 ('content that should be separate is inline') — structure is good, but the per-pattern detail could be split into a references file so the main file stays an overview. | 3 / 5 |
Total | 17 / 20 Passed |