obsidian-experiment-log

Update canonical experiment and result notes in Obsidian.

Updated Mar 27, 2026

Search Tags:#research #metrics #data #obsidian #notes #log #experiments

Ready to run

npx skills add https://github.com/EmaRimoldi/Claude-scholar-extended --skill obsidian-experiment-log

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: obsidian-experiment-log
Source: https://github.com/EmaRimoldi/Claude-scholar-extended/tree/main/skills/obsidian-experiment-log
Command: npx skills add https://github.com/EmaRimoldi/Claude-scholar-extended --skill obsidian-experiment-log

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Maintain canonical experiment and result notes in Obsidian as work progresses, preventing note sprawl and improving traceability.

Core Features & Use Cases

Update existing experiment notes under Experiments/ rather than creating duplicates, and promote stable findings into Results/ when appropriate.
Link experiments and results to Daily/ notes and hub/plans so project state changes are reflected in the main surface.
Use a structured note template for experiments and results, ensuring essential sections like goal, dataset, metrics, status, findings, and next steps are present.

Quick Start

Create or update the canonical Experiment note under Experiments/ and the corresponding Result note under Results/ when a new experiment is started or findings become durable.

Frequently Asked Questions about obsidian-experiment-log

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

FAQPage Schema

How do I log experiments and results in Obsidian without creating duplicate notes?▼

To log experiments in Obsidian without duplicates, this Skill updates existing notes under Experiments/ and promotes durable findings into Results/ rather than creating new files. It ensures canonical notes are maintained automatically as work progresses. It prevents note sprawl by updating existing files instead of duplicating them.

What is the best way to track metrics and datasets for AI research in Obsidian?▼

Tracking metrics and datasets for AI research in Obsidian uses a structured note template ensuring essential sections like goal, dataset, metrics, status, and findings are present. This approach maintains canonical experiment notes automatically. It enforces a structured note template containing goal, dataset, metrics, status, and findings sections for AI research projects.

Can I link experiment notes to hub plans and daily notes in Obsidian?▼

Yes, you can link experiment notes to hub plans and daily notes in Obsidian. This Skill ensures experiments and results link to Daily/ notes and hub/plans so project state changes reflect on the main surface. It automatically links experiments and results to Daily/ notes and hub/plans to reflect project state changes on the main surface.

How do I prevent note sprawl when logging research experiments in Obsidian?▼

Preventing note sprawl when logging research experiments in Obsidian involves maintaining canonical notes and updating existing files under Experiments/ rather than creating duplicates. This Skill automates that process to improve traceability. It prevents note sprawl by updating existing experiment notes instead of creating duplicates, improving project traceability.

Does this experiment logging workflow support CS and AI research projects specifically?▼

Yes, this experiment logging workflow supports CS and AI research projects specifically. It captures goals, datasets, metrics, status, and findings across experiments tailored for computer science and AI research workflows. It applies to CS/AI research projects by capturing goals, datasets, metrics, status, and findings across experiments.

When should I promote an experiment finding into a separate results note?▼

You should promote an experiment finding into a separate results note when findings become durable. This Skill creates the corresponding Result note under Results/ once stable findings emerge from the active experiment. You should promote stable findings into Results/ notes when findings become durable during the research process.