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experiment-plan

Generate canonical experiment-plan.md documents and update related project state files.

1|Updated Mar 23, 2026
Search Tags:#planning#documentation#branching#state-management#experiment#anchor#research-workflow
One-click install
npx skills add https://github.com/LinkDry/Link-Research --skill experiment-plan-linkdry
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: experiment-plan
Source: https://github.com/LinkDry/Link-Research/tree/main/skills/experiment-plan
Command: npx skills add https://github.com/LinkDry/Link-Research --skill experiment-plan-linkdry

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a disciplined framework to convert bootstrap ideation or branch continuations into a canonical active Experiment State by generating the canonical experiment-plan.md and updating related project state across files.

Core Features & Use Cases

  • Generate the canonical experiment-plan.md from bootstrap inputs or a branch continuation.
  • Ensure alignment with anchor lock procedures and update related project state (experiment-memory, STATE, and decision-tree).

Quick Start

Prompt the system to generate the canonical experiment-plan for the selected idea and its current branch.

Frequently Asked Questions about experiment-plan

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

FAQPage Schema
How do I convert ideation into a lockable experiment plan with falsifiability and metrics?▼

To convert ideation into a lockable experiment plan, this skill automates generating a canonical document with falsifiability, metrics, and required sections. It bridges initial concepts to an actionable research workflow by defining experiment identifiers and updating project state.

What is the best way to document experiment branching and update state files in a research workflow?▼

Documenting experiment branching requires generating a canonical plan and updating related project state files like experiment-memory, decision-tree, and STATE. This formalizes branch continuation into an active line while maintaining alignment across project documentation.

Do I need specific dependencies to generate canonical experiment-plan documents?▼

No specific dependencies are required to generate canonical experiment-plan documents. The skill operates independently to define experiment identifiers, write required plan sections, and update related project state files for research workflows.

How does state management work when creating a new active line for an experiment plan?▼

State management during experiment plan creation works by updating related project state files, including experiment-memory, decision-tree, and STATE documents. This ensures the newly defined active line or branch continuation is synchronized across the entire research workflow.

When should I formalize bootstrap ideation into a canonical active experiment state?▼

You should formalize bootstrap ideation into a canonical active experiment state when your research workflow requires falsifiability, defined metrics, and structured documentation. This transition supports turning initial ideas into an actionable, lockable plan across projects.

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