Content
92%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a high-quality skill that efficiently teaches invariant inference with both dynamic and static approaches. The worked example with actual trace data is excellent, and the explicit validation steps (inductive check, sufficiency check) provide clear feedback loops. Minor improvement could come from linking to related skills or reference materials for advanced topics mentioned.
Suggestions
Consider adding links to related skills or reference files for advanced topics like polynomial domains, ghost variables, or SMT solver usage
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, assuming Claude's competence with verification concepts. No unnecessary explanations of basic programming or what invariants are conceptually—jumps straight to actionable methodology. | 3 / 3 |
Actionability | Provides concrete executable guidance with a complete worked example, specific template library, step-by-step process, and clear output format. The find_max example is fully traced with actual values. | 3 / 3 |
Workflow Clarity | Clear 5-step sequence with explicit validation checkpoints (inductive check, sufficiency check). The workflow includes feedback loops—if a candidate fails inductiveness, it's pruned; if insufficient, seek stronger invariants. | 3 / 3 |
Progressive Disclosure | Content is well-organized with clear sections and tables, but it's a moderately long single file. The reference to 'abstract-invariant-generator' suggests related tools that could be linked. No external file references for advanced topics like polynomial domains or ghost variables. | 2 / 3 |
Total | 11 / 12 Passed |