Content
75%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, actionable multi-phase workflow for finding and fixing flaky tests with concrete commands, templates, and an explicit user-approval feedback loop. The main gap is the absence of a post-fix verification step to confirm the flake is resolved.
Suggestions
Add a Phase 3.4 verification step that re-runs the affected test (or re-checks CI) after a fix lands to confirm the flake is actually resolved.
Provide a copy-paste-ready prompt template for the parallel investigation agents rather than describing the agent's tasks as a numbered list.
Tighten the six-step agent investigation list; some sub-bullets (e.g. the root-cause enumeration) could be condensed without losing clarity.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly lean task-specific guidance (script command, report template, agent investigation steps, deflake principles) with only minor over-explanation, e.g. the six-step agent investigation list is detailed but justified for parallel subagents. | 4 / 5 |
Actionability | Provides a copy-paste script invocation `python3 .claude/skills/deflake/collect-flakes.py`, concrete markdown templates, and explicit agent spawn instructions (subagent_type: `general-purpose`); minor gaps are the template placeholders and the agent prompt being described as steps rather than a ready-to-send prompt. | 4 / 5 |
Workflow Clarity | Clear three-phase sequence with explicit checkpoints (categorization gate, '--report' stop condition, user-approval gate before implementation); the notable gap is no 'verify the fix actually deflaked the test' step after Phase 3.3. | 4 / 5 |
Progressive Disclosure | Well-organized with clear section headers (Phase 1/2/3, Deflake Principles, Anti-patterns) and a single one-level-deep script reference signaled in a code block; no bundle files are present, but the inline content is appropriately structured rather than monolithic. | 4 / 5 |
Total | 16 / 20 Passed |