Content
77%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, highly actionable workflow with real validation checkpoints and a closing feedback loop. The main weaknesses are the inlined inventory script that its own comment says belongs in scripts/, and stack-specific runtime-measurement commands that assume a JavaScript toolchain.
Suggestions
Move the inventory script into an actual scripts/test-mix-inventory.py bundle file and reference it from Step 1, keeping SKILL.md as an overview (progressive_disclosure).
Make Step 2 runtime measurement stack-agnostic: give per-stack commands or a generic JUnit-XML aggregation recipe instead of assuming Jest + Playwright (actionability).
Trim the References section's Mike Cohn quotation to a one-line link and drop the hourglass fix's repetition of the Step 1 content-signal heuristics (conciseness).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and assumes Claude's competence (no generic test-pyramid primer), but there is minor trimmable material: the Mike Cohn quotation block in References and the hourglass fix re-explaining the content-signal hints already shown in Step 1's classifier. This matches the 4 anchor ('efficient; minor instances of over-explanation'), not the 5 anchor's 'every token earns its place'. | 4 / 5 |
Actionability | The Step 1 classifier is executable copy-paste Python, Step 5 includes a specific grep for migration candidates and a complete output template, and Step 6 names the re-run command. The main gap is Step 2: 'time npm test' / 'npx playwright test' hardcodes a JavaScript stack with only a passing 'OR via JUnit XML aggregation' nod for other languages — mostly executable with minor gaps, matching the 4 anchor. | 4 / 5 |
Workflow Clarity | Seven clearly sequenced steps with explicit validation checkpoints — Step 1 requires sampling 5-10 tests per bucket and reclassifying misclassified ones, Step 4 requires user confirmation before recommending large-scale test moves — plus a genuine feedback loop in Step 6 ('If any layer is still outside its target band, return to Step 4'). This matches the 5 anchor's explicit validation steps and error-recovery loops; this is an analysis/recommendation skill, so the destructive-operation cap does not apply. | 5 / 5 |
Progressive Disclosure | Sections are well organized and external references (test-pyramid link, test-effort-estimation's change-shape-classifier, test-coverage-targeter, e2e-suite-budget) are clearly signaled and one level deep. However, the ~30-line inventory script is inlined in the body while labeling itself 'scripts/test-mix-inventory.py' — and no scripts/ bundle file actually exists — so content that belongs in a separate file is inline, matching the 3 anchor rather than 4. | 3 / 5 |
Total | 16 / 20 Passed |