SE-CoVe: Software Engineering Chain-of-Verification

A Claude Code plugin that catches bugs in AI-generated code by verifying against requirements, not implementation.

Why This Works

When you ask an AI to review its own code, it's biased toward its solution. Meta's Chain-of-Verification research showed that independent verification improves accuracy by 28% - because the verifier checks against requirements, not the (possibly flawed) implementation.

SE-CoVe applies this to code: the verifier never sees the draft solution. It answers verification questions by checking docs, searching your codebase, and reasoning about requirements - then a synthesizer compares findings and corrects errors.

Built for Software Engineering

Unlike general-purpose verification, SE-CoVe is designed specifically for code. Each agent understands 35+ software engineering claim categories across three domains:

Correctness

Behaviors, logic flow, boundary conditions, error handling, API usage patterns

Security

Input validation, authentication, authorization, injection prevention, data exposure

Performance

Time/space complexity, caching, memory management, async patterns, N+1 queries

The verification pipeline includes:

• Confidence scoring on all claims (High/Medium/Low)
• Severity ranking of issues (Critical/High/Medium/Low)
• Parallel verification tracks for thorough analysis
• Domain-specific checklists for security, performance, and error handling
• Evidence quality scoring with source authority ranking

How It Works

Question → Baseline (generate + extract claims)
              ↓
          Planner (create verification tasks)
              ↓
          Executor (verify independently - never sees draft)
              ↓
          Synthesizer (compare + correct)
              ↓
          Verified Solution

Installation

First add the marketplace

/plugin marketplace add vertti/se-cove-claude-plugin

then install the plugin

/plugin install chain-of-verification

Usage

/chain-of-verification:verify <your question>

Tip: Type /ver and press Tab to autocomplete the command.

Options

Flag	Short	Description
--quick	-q	Fast verification (haiku models, 1 executor)
--thorough	-t	Comprehensive verification (opus models, 4+ parallel executors)
--focus=X	-f X	Prioritize a specific area (see below)

Focus Areas

Focus	What It Checks
security	Auth, input validation, injection, data exposure
performance	Complexity, caching, memory, N+1 queries
api	Contracts, versioning, error responses, compatibility
testing	Coverage, edge cases, integration, mocks
error-handling	Exceptions, recovery, logging, user feedback
style	Naming, organization, documentation, types
scalability	Bottlenecks, resource limits, horizontal scaling

Examples

# Standard verification (default)
/chain-of-verification:verify How do I implement debounced search in React?

# Quick sanity check
/chain-of-verification:verify --quick Is this null check correct?

# Thorough security review (4 parallel executors)
/chain-of-verification:verify --thorough --focus=security Review the authentication flow

# API-focused verification
/chain-of-verification:verify -f api Does this endpoint handle errors correctly?

# Test coverage analysis
/chain-of-verification:verify --focus=testing Are these unit tests comprehensive?

# Error handling review
/chain-of-verification:verify -f error-handling How should this handle failures?

When to Use

Good for: Complex code generation, architectural decisions, bug investigations, library/API questions

Skip for: Trivial changes, simple questions, exploratory coding

References

Based on Meta's Chain-of-Verification research, which demonstrated 28% improvement in factual accuracy through independent verification.

License

MIT