Nicholls Inc avatar

Nicholls Inc

Official

@nicholls-inc · Canada

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9Public Repos
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29Published Skills

Offers formal verification, software assurance, and rigorous specification modeling for high-integrity codebases using Lean 4 and Dafny.

Skills Distribution
DomainCybersecurit...Formal Verification (40%)Software Assurance (30%)Specification Mode.. (30%)

Agent Skills by Nicholls Inc

Showing 29 vetted skills indexed across 1 GitHub repositories.

nicholls-incnicholls-inc
5

suggest-prompts

Fetch curated GitHub Copilot prompts and compare local versions for updates.

Official
Basic
nicholls-incnicholls-inc
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suggest-instructions

Fetch and compare GitHub Copilot instruction files against local repository files.

Official
Intermediate
nicholls-incnicholls-inc
5

suggest-skills

Analyze repository content to recommend relevant GitHub Copilot agent skills.

Official
Intermediate
nicholls-incnicholls-inc
5

assurance-roadmap-check

Validate assurance roadmap item statuses against repository activity and documentation.

Official
Advanced
nicholls-incnicholls-inc
5

lean-spec

Convert signed-off informal verification specs into type-checked Lean 4 stubs.

Official
Advanced
nicholls-incnicholls-inc
5

acceptance-oracle-draft

Generate YAML/JSON acceptance scenarios with CI integration for automated QA.

Official
Intermediate
nicholls-incnicholls-inc
5

extract-code

Convert verified Dafny code into Python or Go.

Official
Advanced
nicholls-incnicholls-inc
5

intent-check

Verify code diffs against documented invariants to prevent regressions.

Official
Intermediate
nicholls-incnicholls-inc
5

lean-impl

Translate Python, Go, or Dafny source code into formal Lean 4 models.

Official
Advanced
nicholls-incnicholls-inc
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correspondence-review

Classify Lean definitions against source code as exact, abstraction, approximation, or mismatch.

Official
Advanced
nicholls-incnicholls-inc
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lightweight-verify

Generate assertions, invariants, and property-based tests for functions.

Official
Intermediate
nicholls-incnicholls-inc
5

drt-oracle

Detect inconsistencies between Lean formal models and production implementations via randomized testing.

Official
Advanced
nicholls-incnicholls-inc
5

compare-patches

Analyze two code patches for semantic equivalence using structure and tests.

Official
Advanced
nicholls-incnicholls-inc
5

suggest-specs

Identify code functions and modules that benefit from formal specification generation.

Official
Intermediate
nicholls-incnicholls-inc
5

trace-execution

Trace code execution paths and build call graphs from entry points.

Official
Advanced
nicholls-incnicholls-inc
5

spec-adversary

Propose undocumented invariants for module specifications in software assurance workflows.

Official
Advanced
nicholls-incnicholls-inc
5

assurance-probe

Run mutation-based evaluation of Python property invariants and report weak tests via GitHub issues.

Official
Intermediate
nicholls-incnicholls-inc
5

assurance-layer-audit

Audit a code repository's tooling and verification signals against the formal assurance hierarchy.

Official
Intermediate
nicholls-incnicholls-inc
5

protected-surface-amend

Generate a governance amendment record for protected surface changes.

Official
Advanced
nicholls-incnicholls-inc
5

assurance-init

Create assurance governance files and directories in a code repository.

Official
Advanced
nicholls-incnicholls-inc
5

locate-fault

Trace code paths and predict root causes of failing tests.

Official
Advanced
nicholls-incnicholls-inc
5

assurance-status

Verify repository assurance documentation presence and analyze drift and coverage issues.

Official
Basic
nicholls-incnicholls-inc
5

generate-verified

Generate Dafny implementations that satisfy specified formal properties.

Official
Advanced
nicholls-incnicholls-inc
5

check-regressions

Detect Dafny specification changes requiring re-verification via git diffs and source hashes.

Official
Intermediate

Frequently Asked Questions About Nicholls Inc

FAQPage Schema
What specific tasks can I perform using Nicholls Inc skills?

You can perform formal verification of source code, generate property-based tests, translate natural language requirements into Dafny specifications, and audit repository governance documentation. These capabilities enable rigorous semantic analysis and ensure code correctness against documented invariants.

Which personas benefit most from these verification capabilities?

Software engineers, security researchers, and compliance officers working on high-integrity or safety-critical systems benefit most. These skills are designed for developers needing to bridge the gap between informal requirements and mathematically verified implementations.

What are the prerequisites for implementing these verification models?

Implementation requires a repository containing source code in Python, Go, or Dafny, alongside established formal verification environments like Lean 4. Users must define initial invariants or natural language specifications to enable the generation of formal models and property-based tests.