analysis-orchestration

What problem does it solve?

This Skill guides qualitative researchers in configuring their AI-assisted analysis approach, helping them choose the optimal AI model (e.g., Claude Opus, Sonnet, Haiku) for specific coding tasks, estimate API costs, and plan efficient batch processing strategies. It ensures cost-effective and high-quality AI collaboration.

Core Features & Use Cases

• Model Selection Guidance: Recommends the best Claude model based on coding complexity, budget, and corpus size.
• Cost Estimation: Provides rough API cost estimates for processing documents, considering length, passes, and model choice.
• Batch Processing Strategy: Advises on how to group and process documents (e.g., individual, small batches, large batches) for different corpus sizes.
• Use Case: Before starting Stage 2 coding, use this skill to decide if Claude Sonnet is sufficient for initial categorization or if Opus is needed for deep interpretive coding, and estimate the budget impact.

Quick Start

Estimate the cost for coding 25 documents, each averaging 5 pages, using the Sonnet model for 2 passes: node skills/analysis-orchestration/scripts/estimate-costs.js --documents 25 --avg-pages 5 --model sonnet --passes 2