Content
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
Highly actionable with a well-sequenced, validated workflow, but it carries minor conceptual padding and keeps all detail inline rather than splitting reference material into bundle files.
Suggestions
Trim the opening paragraph explaining why flaky tests are harmful — Claude already knows what flaky tests are; lead with the detection procedure instead.
Extract the engine-specific parsing details (Godot/Unity/Unreal/JUnit) and the cause-classification table into a references/ file, keeping SKILL.md as an overview with one-level-deep links.
Move the placeholder in-conversation report template into a reference file to reduce inline token weight while preserving the format for reuse.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient and actionable, but the opening framing ('Flaky tests are worse than no tests in some ways — they train the team to ignore red CI runs') explains a concept Claude already knows, and the placeholder report template adds inline tokens that could be trimmed. | 2 / 3 |
Actionability | Provides concrete, executable guidance: real shell/grep commands, engine-specific pass/fail patterns, exact skip annotations (@pytest.mark.skip, [Ignore], GdUnitSkip), and named fix helpers (is_equal_approx, await get_tree().process_frame). | 3 / 3 |
Workflow Clarity | A clear seven-step sequence with explicit checkpoints — the no-log-data branch stops and asks, sub-3-run results are flagged 'suspected', and writes require explicit approval with COMPLETE/BLOCKED verdicts. | 3 / 3 |
Progressive Disclosure | Well-organized into numbered sections but monolithic at ~200 lines with no bundle references; engine-specific parsing detail and the cause-classification table are inline content that could live in separate files. | 2 / 3 |
Total | 10 / 12 Passed |