| plugin | marketplace | version | license | research |
|---|---|---|---|---|
chain-of-verification |
vertti/se-cove-claude-plugin |
1.1.1 |
MIT |
arXiv:2309.11495 (ACL 2024 Findings) |
Software Engineering adaptation of Meta's Chain-of-Verification methodology for Claude Code.
Paper: "Chain-of-Verification Reduces Hallucination in Large Language Models" Authors: Dhuliawala et al. (Meta AI) Published: ACL 2024 Findings Sources: arXiv:2309.11495 | ACL Anthology
5-stage pipeline ensuring independent verification:
- Baseline: Generate initial solution
- Planner: Create verification questions from solution claims
- Executor: Answer questions independently (never sees baseline)
- Synthesizer: Compare findings, identify discrepancies
- Output: Produce verified solution
Critical innovation: Verifier operates without access to draft code, preventing confirmation bias.
Results from Meta's research paper (Llama 65B model):
| Task Type | Metric | Improvement | Computational Cost |
|---|---|---|---|
| Biography generation | FACTSCORE | +28% (55.9→71.4) | -26% output volume (16.6→12.3 facts) |
| Closed-book QA | F1 Score | +23% (0.39→0.48) | ~2x token consumption |
| List-based questions | Precision | +112% (0.17→0.36) | Fewer total answers |
Source: Dhuliawala et al., ACL 2024 Findings (Table 1, Section 4.3)
Key insight: Higher accuracy comes at cost of increased computation and reduced output volume.
- Critical code review: Architectural decisions, security-sensitive code
- Complex debugging: Multi-component failure analysis
- API/library integration: When correctness > speed
- Acceptable 2x cost: Token budget allows for quality premium
- Trivial changes: Simple fixes, formatting, typos
- Exploratory coding: Rapid prototyping, experimentation
- Tight token budgets: When cost is primary constraint
- Need comprehensive output: When you need all facts, not just accurate subset
# Add plugin marketplace
/plugin marketplace add vertti/se-cove-claude-plugin
# Install plugin (in separate command)
/plugin install chain-of-verificationNote: Commands must be pasted separately (Claude Code marketplace limitation).
# Invoke verification
/chain-of-verification:verify <your question>
# Autocomplete available
/ver<Tab>From the research paper (Section 6):
- Not a silver bullet: Reduces hallucinations but does not eliminate them
- Computational cost: ~2x token usage vs baseline generation (estimated from implementation)
- Output volume trade-off: Generates fewer but more accurate results
- Model-specific: Tested on Llama 65B; generalization to GPT-4/Claude/Sonnet unverified
- Task dependency: Performance varies significantly by task type (23-112%)
- Factual hallucinations only: Does not address incorrect reasoning steps or opinions
- GitHub: vertti/se-cove-claude-plugin
- Version: 1.1.1 (2026-01-23)
- License: MIT
- Author: Janne Sinivirta
- Main guide section: Plugin System
- Methodology: Multi-Agent Orchestration
- Verification Loops: Autonomous Iteration