How do I choose between Claude Opus and Sonnet for research?

Use Claude Opus 4.5 for complex interpretive coding and nuanced themes requiring high theoretical sensitivity. Use Claude Sonnet for systematic coding where balancing quality and cost is a priority.

Can this skill help me stay within my research budget?

Yes, it includes an automated estimation script that calculates API costs based on document volume, page count, selected model, and the number of coding passes required.

How many documents should I process in a single session?

For deep interpretive coding using the dialogical-coder agent, we recommend 5-10 documents per session to allow for human reflection and theoretical integration.

What is the best way to process over 100 documents?

The skill recommends a strategic sampling approach: use a two-pass strategy with Haiku for initial categorization and Sonnet or Opus for deep coding on a meaningful subset.

Qualitative Analysis Orchestrator

Name: Qualitative Analysis Orchestrator
Author: linxule

bylinxule

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Data Science & ML

Optimizes model selection, API cost estimation, and batch processing strategies for AI-assisted qualitative document analysis.

Qualitative Analysis Orchestrator provides a robust infrastructure for researchers to manage the operational complexities of AI-assisted qualitative analysis. It streamlines the transition from manual coding to AI-augmented interpretation by offering precise guidance on model selection—balancing the high-fidelity reasoning of Claude Opus with the cost-efficiency of Sonnet and Haiku. With built-in cost estimation scripts and strategic batch processing decision trees, the skill ensures that large-scale document analysis remains rigorous, cost-effective, and aligned with interpretive research methodologies.

Key Features

01Claude Model Selection Guide (Opus vs. Sonnet vs. Haiku)

02Interpretive vs. Systematic Coding Decision Trees

03API Cost Estimation Script for Research Budgets

04Batch Processing Strategy for Large Document Corpora

052 GitHub stars

06Integration with Dialogical Coding Methodologies

Use Cases

01Budgeting and estimating API costs for a study involving 100+ interview transcripts

02Choosing the most appropriate Claude model for nuanced thematic abstraction versus simple categorization

03Designing a two-pass batch processing workflow to manage high-volume qualitative data

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add linxule/interpretive-orchestration analysis-orchestration

For use in Claude.ai and ChatGPT

Download Skill