Content
92%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.
Excellent content: fully executable code with a validation checkpoint step and per-test state checks, and a clean one-level reference split for per-database differences. Only minor conciseness trims are available (known-concept anomaly definitions and environment version notes).
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and assumes competence, but the anomaly-shape table re-defines concepts Claude already knows (e.g. 'T2 reads T1's uncommitted write') and the version-specific 'ran 5/5 green on PostgreSQL 16 with psycopg 3' is trimmable detail outside any deprecated/old-patterns section. | 4 / 5 |
Actionability | The skill ships a complete, copy-paste-ready pytest harness (fixture, run_pair, four anomaly tests, retry wrapper) plus an exact run command with TEST_DSN and a table mapping business invariants to test shapes. | 5 / 5 |
Workflow Clarity | Steps 1-4 are clearly sequenced and Step 4 is an explicit validation checklist ('must fail when you raise the isolation level by one step. Try it.'), while the harness itself validates starting state per test, asserts recorded errors, and detects hangs - feedback loops are present in this database context. | 5 / 5 |
Progressive Disclosure | Content is appropriately split: the PostgreSQL matrix and harness stay inline while MySQL/SQL Server differences live in the real, well-signaled, one-level-deep references/per-database.md, linked in three places and listed under References. | 5 / 5 |
Total | 19 / 20 Passed |