multi-model-meta-analysis
✓Synthesize outputs from multiple AI models into a comprehensive, verified assessment. Use when: (1) User pastes feedback/analysis from multiple LLMs (Claude, GPT, Gemini, etc.) about code or a project, (2) User wants to consolidate model outputs into a single reliable document, (3) User needs conflicting model claims resolved against actual source code. This skill verifies model claims against the codebase, resolves contradictions with evidence, and produces a more reliable assessment than any single model.
Installation
SKILL.md
Combine outputs from multiple AI models into a verified, comprehensive assessment by cross-referencing claims against the actual codebase.
Models hallucinate and contradict each other. The source code is the source of truth. Every significant claim must be verified before inclusion in the final assessment.
Use Grep, Glob, and Read tools to locate and examine relevant code. Do not trust model claims without verification.
Synthesize outputs from multiple AI models into a comprehensive, verified assessment. Use when: (1) User pastes feedback/analysis from multiple LLMs (Claude, GPT, Gemini, etc.) about code or a project, (2) User wants to consolidate model outputs into a single reliable document, (3) User needs conflicting model claims resolved against actual source code. This skill verifies model claims against the codebase, resolves contradictions with evidence, and produces a more reliable assessment than any single model. Source: petekp/claude-code-setup.
Facts (cite-ready)
Stable fields and commands for AI/search citations.
- Install command
npx skills add https://github.com/petekp/claude-code-setup --skill multi-model-meta-analysis- Source
- petekp/claude-code-setup
- Category
- {}Data Analysis
- Verified
- ✓
- First Seen
- 2026-02-11
- Updated
- 2026-02-18
Quick answers
What is multi-model-meta-analysis?
Synthesize outputs from multiple AI models into a comprehensive, verified assessment. Use when: (1) User pastes feedback/analysis from multiple LLMs (Claude, GPT, Gemini, etc.) about code or a project, (2) User wants to consolidate model outputs into a single reliable document, (3) User needs conflicting model claims resolved against actual source code. This skill verifies model claims against the codebase, resolves contradictions with evidence, and produces a more reliable assessment than any single model. Source: petekp/claude-code-setup.
How do I install multi-model-meta-analysis?
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/petekp/claude-code-setup --skill multi-model-meta-analysis Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Where is the source repository?
https://github.com/petekp/claude-code-setup
Details
- Category
- {}Data Analysis
- Source
- skills.sh
- First Seen
- 2026-02-11