nl-to-constraints
Translates natural-language requirements into formal constraints — logical predicates, schemas, or property-based test generators — that a machine can check. Use when turning a spec into validation code, when writing property tests, or as the bridge between requirements and formal verification.
Install with Tessl CLI
npx tessl i github:santosomar/general-secure-coding-agent-skills --skill nl-to-constraints90
Quality
88%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Discovery
85%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-structured description that clearly articulates both capabilities and usage triggers. The main weakness is the use of technical jargon that may not match how users naturally phrase requests. The description excels at carving out a distinct niche but could benefit from more accessible trigger terms.
Suggestions
Add more natural user-facing trigger terms like 'convert requirements to tests', 'generate validation from spec', or 'turn rules into code' alongside the technical terminology.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'translates natural-language requirements into formal constraints', 'logical predicates, schemas, or property-based test generators'. These are concrete, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both what ('Translates natural-language requirements into formal constraints — logical predicates, schemas, or property-based test generators') AND when ('Use when turning a spec into validation code, when writing property tests, or as the bridge between requirements and formal verification'). | 3 / 3 |
Trigger Term Quality | Includes some relevant terms like 'spec', 'validation code', 'property tests', 'formal verification', but uses more technical jargon than natural user language. Missing common variations users might say like 'convert requirements', 'generate tests from specs', or 'validate against rules'. | 2 / 3 |
Distinctiveness Conflict Risk | Has a clear niche focused on the specific intersection of natural language requirements and formal verification/constraints. Distinct triggers like 'formal constraints', 'property-based test generators', and 'formal verification' make it unlikely to conflict with general coding or testing skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
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 constraint formalization through concrete mapping tables, executable code examples, and a clear output template with built-in validation. The 'only if' trap section and faithfulness check demonstrate sophisticated awareness of common errors. Minor improvement possible in progressive disclosure by better signaling related skills.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely efficient use of tokens. Tables compress English-to-logic mappings elegantly, no unnecessary explanations of basic concepts, and every section adds unique value. The skill assumes Claude's competence with logic and programming. | 3 / 3 |
Actionability | Provides fully executable code examples (JSON Schema, Hypothesis property tests), concrete mapping tables, and worked examples that demonstrate the complete translation process. The output format template is copy-paste ready. | 3 / 3 |
Workflow Clarity | Clear workflow: decompose requirement → map to constraints → formalize in target → verify faithfulness. The output format section provides an explicit checklist with validation steps (over-constrains?, under-constrains?, direction check). | 3 / 3 |
Progressive Disclosure | Content is well-organized with clear sections and tables, but it's a substantial single file. The reference to 'ambiguity-detector' and 'specification-to-temporal-logic-generator' suggests related skills exist but aren't clearly linked. Some content (like the full worked examples) could potentially be split out. | 2 / 3 |
Total | 11 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Reviewed
Table of Contents
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