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research-design

Use when debating hypotheses, turning claims into predictions, planning experiments, or checking causal and empirical designs.

Skill by AbubakarAmin

IndexedMIT★ 1
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/abubakaramin-research-design

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Use when debating hypotheses, turning claims into predictions, planning experiments, or checking causal and empirical designs.

Use cases: design, research

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/research-design

What's inside

Skill name
research-design
Description
Use when debating hypotheses, turning claims into predictions, planning experiments, or checking causal and empirical designs.
License
MIT
Metadata
scholargraph-roles: HypothesisDebateSystem, PlannerAgent · scholargraph-stage: hypothesis-and-planning
Instructions
14 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Falsifiable Research Design

## Procedure
1. Turn each claim into an observable prediction with outcome, comparator, population/data, and decision window.
2. Define support, falsification, and inconclusive outcomes before seeing results.
3. Name the strongest rival explanation and the baseline/control that tests it.
4. Match measures, sample/seed plan, uncertainty, test, and multiplicity correction to the prediction; never choose tests for significance.
5. For causal claims, state estimand, identification assumptions, confounding risks, and robustness checks. Otherwise use associational scope.
6. Check dataset, compute, sandbox, and contract feasibility; expose blockers.

## Output Check
Every contribution has a falsifiable prediction, failure condition, relevant controls, and feasible measurement plan.

From AbubakarAmin/scholargraph-harness, MIT.

More from AbubakarAmin/scholargraph-harness

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Last commit (this folder)
Oct 23, 2026 (8 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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research-design skill. Agent Mart. https://agentmart.dev/skills/abubakaramin-research-design (last updated 2026-10-24)