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 pseudocode extraction from verified code. The mapping table provides instant reference, the worked example demonstrates exactly what output should look like, and the 'Do not' section prevents common mistakes. The only minor weakness is that all content is inline rather than using progressive disclosure for the TLA+ variant or extended examples.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, assuming Claude's competence with formal verification languages. No unnecessary explanations of what Dafny/Lean/TLA+ are or how verification works—it jumps straight to actionable mapping tables and examples. | 3 / 3 |
Actionability | Provides a complete worked example with real Dafny code and its corresponding pseudocode output. The mapping table is concrete and copy-paste ready, and the output format template is fully specified. | 3 / 3 |
Workflow Clarity | The workflow is implicit but crystal clear: identify constructs → apply keep/drop rules → annotate inline at point-of-use → format output. The 'Do not' section serves as validation checkpoints for common errors. | 3 / 3 |
Progressive Disclosure | Content is well-organized with clear sections (mapping table, worked example, TLA+ variant, do-nots, output format), but it's a moderately long single file. The reference to 'python-to-dafny-translator' is good, but some content like the TLA+ section could potentially be split out for complex use cases. | 2 / 3 |
Total | 11 / 12 Passed |