Content
100%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A well-structured, executable skill body that pairs a clear four-step workflow with validation feedback loops and a real worked example, while offloading depth to a single one-level reference. Concise, actionable, and well organized throughout.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and information-dense; assumes competence and avoids explaining generic library mechanics or basic concepts, deferring the full mechanic table to a referenced file while keeping only the runnable core inline. | 3 / 3 |
Actionability | Provides fully executable, copy-paste-ready Python (Faker.seed, fake.unique, luhn check) with concrete asserts rather than pseudocode or abstract direction. | 3 / 3 |
Workflow Clarity | Four-step sequence with explicit validation checkpoints (injectivity assert, no-collision diff against source, before/after join-key cardinality assert) and an anti-patterns table that closes the feedback loop on each failure mode. | 3 / 3 |
Progressive Disclosure | SKILL.md is an overview that signals one clearly-labeled, one-level-deep reference (references/library-surface-and-seeding.md, which exists) for the mechanic tables; content is appropriately split with easy navigation. | 3 / 3 |
Total | 12 / 12 Passed |