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 provides excellent actionable guidance for translating system descriptions into TLA+ specifications. The step-by-step workflow is clear, the worked example is complete and instructive, and the edge cases section addresses real-world complications. The only weakness is the document length could benefit from progressive disclosure to separate reference material.
Suggestions
Consider moving the 'Edge cases' section to a separate EDGE_CASES.md file and linking to it, reducing the main skill's token footprint
The worked example could be extracted to EXAMPLES.md with additional examples for different system types (message-passing, consensus, etc.)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, assuming Claude's competence with TLA+ syntax and focusing on decision-making guidance. Every section earns its place with actionable insights rather than explaining basic concepts Claude would already know. | 3 / 3 |
Actionability | Provides fully executable TLA+ code with complete module and .cfg file examples. The worked example is copy-paste ready, and the extraction tables give concrete patterns for translating prose to spec components. | 3 / 3 |
Workflow Clarity | Clear 5-step sequence from deciding if TLA+ is appropriate through assembling the module. Each step has explicit criteria and the final 'Do not' section includes validation guidance ('Don't hand over a spec you haven't run through TLC once'). | 3 / 3 |
Progressive Disclosure | Content is well-organized with clear sections, but it's a monolithic document (~200 lines) that could benefit from splitting edge cases or the worked example into separate files. References to other skills (cpp-to-dafny-translator, etc.) are good but inline content is heavy. | 2 / 3 |
Total | 11 / 12 Passed |