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program-to-model-extractor

Extract abstract mathematical models from functional code (Haskell, OCaml, F#) for formal reasoning in Isabelle/HOL. Use when users need to: (1) Convert functional programs to Isabelle definitions, (2) Extract high-level algorithm essence from implementation code, (3) Generate formal specifications and properties from code, (4) Create verification-ready models that capture mathematical properties while abstracting away implementation details. Focuses on structural recursion, algebraic data types, higher-order functions, and invariant extraction.

92

1.11x
Quality

89%

Does it follow best practices?

Impact

98%

1.11x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Well-structured, highly actionable content with executable Isabelle examples and clean progressive disclosure into two real reference files. The main gap is a missing explicit verification checkpoint in the workflow and minor Overview redundancy.

Suggestions

Add an explicit final workflow step to validate the extracted model, e.g. load the theory in Isabelle/jEdit and confirm it type-checks before declaring the extraction complete.

Trim the Overview paragraph since it restates the frontmatter description, or fold it into the workflow's first step.

Consider noting where generated Isabelle theories should be placed / how they should be named for verification-ready output.

DimensionReasoningScore

Conciseness

Mostly efficient with tight code examples and brief notes, but the Overview paragraph restates the description's "what" and the post-example Explanation bullets recap points already shown.

4 / 5

Actionability

Fully executable, copy-paste-ready Isabelle code covering datatypes, fun/function/definition constructs, lemmas, invariants, and a complete quicksort extraction — specific examples cover the common cases.

5 / 5

Workflow Clarity

Clear 5-step sequence (Analyze → Extract Data Types → Model Functions → State Properties → Identify Invariants) with decision points acting as implicit checkpoints, but no explicit "load in Isabelle to verify the model type-checks" validation step.

4 / 5

Progressive Disclosure

Body is a concise overview with well-signaled, one-level-deep references to real files (references/extraction_patterns.md with verified pattern anchors, references/isabelle_syntax.md); content appropriately split and easy to navigate.

5 / 5

Total

18

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, specific description that clearly states what the skill does and when to use it, with concrete enumerated triggers and a well-defined niche. Minor room to add a few more natural synonyms (prove, theorem, .hs).

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Convert functional programs to Isabelle definitions", "Extract high-level algorithm essence", "Generate formal specifications and properties", "Create verification-ready models" — with comprehensive coverage of the extraction task.

5 / 5

Completeness

Explicitly answers both what ("Extract abstract mathematical models from functional code ... for formal reasoning in Isabelle/HOL") and when ("Use when users need to: (1)... (4)...") with concrete trigger phrases.

5 / 5

Trigger Term Quality

Strong natural-domain keywords ("functional code (Haskell, OCaml, F#)", "Isabelle/HOL", "formal reasoning", "verification-ready models") but misses a few natural synonyms a user might say (e.g. "prove", "theorem", file extensions like .hs).

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche — functional-to-Isabelle/HOL model extraction with named source languages — making it unlikely to trigger for unrelated skills.

5 / 5

Total

19

/

20

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
ArabelaTso/Skills-4-SE
Reviewed

Table of Contents

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