benchmark-framework

Benchmark cognitive reasoning patterns via controlled experiments and store metrics in ChromaDB.

4|1|Updated Jan 19, 2026

Search Tags:#benchmarking #data-analytics #experimental-design #A/B/C testing #cognitive-reasoning #pattern-evaluation #chromadb

Ready to run

npx skills add https://github.com/kimasplund/claude_cognitive_reasoning --skill benchmark-framework

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: benchmark-framework
Source: https://github.com/kimasplund/claude_cognitive_reasoning/tree/main/cognitive-skills/benchmark-framework
Command: npx skills add https://github.com/kimasplund/claude_cognitive_reasoning --skill benchmark-framework

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a rigorous, data-driven framework for empirically evaluating and comparing cognitive reasoning patterns, enabling objective selection based on measured trade-offs.

Core Features & Use Cases

Empirical pattern evaluation: Quantitatively compare ToT, BoT, SRC, HE, AR, DR, AT, RTR, and NDF across defined tasks.
Experimental design support: Facilitates reproducible, controlled experiments with problem sets, randomization, and baseline controls.
Results governance: Centralized collection and storage of metrics (quality, cost, time, confidence) for cross-domain analysis and trend tracking.

Quick Start

Prepare an experiment_config.yaml describing problem domains, patterns, and evaluation criteria, then run the benchmark runner to start the evaluation.
After completion, review the generated reports and analyze results stored in the Chromadb-backed store for trend insights.

Frequently Asked Questions about benchmark-framework

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I benchmark cognitive reasoning patterns empirically?▼

To benchmark cognitive reasoning patterns, prepare an experiment_config.yaml defining problem domains, patterns, and criteria, then run the benchmark runner to evaluate patterns like ToT, BoT, and SRC across controlled experiments.

What metrics are collected during cognitive reasoning pattern evaluation?▼

Cognitive reasoning pattern evaluation collects metrics on quality, cost, time, and confidence. These results are stored in a ChromaDB-backed store to enable trend analysis and cross-project comparison across domains.

Can I use A/B/C testing to compare reasoning patterns across different domains?▼

Yes, the framework supports A/B/C testing across domains such as optimization, exploration, diagnosis, security, and governance, using reproducible experimental designs with randomization and baseline controls to evaluate patterns.

How do I analyze benchmark results after running reasoning pattern experiments?▼

After running experiments, review the generated reports and analyze the results stored in the ChromaDB-backed store to gain trend insights and compare trade-offs across different cognitive reasoning patterns.

What is the best way to ensure reproducibility when evaluating reasoning patterns?▼

To ensure reproducibility when evaluating reasoning patterns, use the framework's experimental design support, which facilitates controlled experiments with defined problem sets, randomization, and baseline controls.

Do I need a database to store cognitive reasoning benchmark data?▼

Yes, the framework uses a ChromaDB-backed store to centralize the collection and storage of benchmark metrics, enabling cross-domain analysis and trend tracking for cognitive reasoning pattern evaluation.