Agent skill · Data & Analytics

amj-theory-development

Use when the theoretical argument and hypotheses are the bottleneck for an Academy of Management Journal (AMJ) manuscript — building a mechanism and deriving testable hypotheses a priori. Constructs the theory; it does not run the analysis (amj-data-analysis) or write the final contribution paragraph (amj-contribution-framing).

brycew6m878★ · +32/wk · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill amj-theory-development --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 5 KB
Bundled scripts: none
Path: Academy-of-Management-Journal-Skills/skills/amj-theory-development/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 909 · +31 this week
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Theory Development & Hypotheses (amj-theory-development) ## When to trigger - Hypotheses read as bald predictions ("A is positively related to B") with no mechanism - You have results and are tempted to write hypotheses around them (HARKing risk) - The argument leans on one borrowed citation rather than a developed logic - Mediators/moderators are present in the data but not theorized - A reviewer says "the theory is thin," "the logic is underdeveloped," or "why would this be true?" ## The AMJ theory bar AMJ does not publish atheoretical work — its mission is "to publish empirical research that tests, extends, or builds management theory." Every hypothesis must be **derived from an articulated theoretical mechanism**, written *before* the results are known. The argument should make a reader feel they understand *why* the effect occurs and *under what conditions* it strengthens or reverses. For **theory-building** (typically qualitative) papers, AMJ does *not* expect a priori hypotheses; it expects a grounded model with emergent propositions. Eisenhardt and Graebner's AMJ guidance on building theory from cases is the canonical exemplar for how rich data become crisp constructs and

What's inside
Steps it walks through
  1. When to trigger
  2. The AMJ theory bar
  3. Building a hypothesis (the mechanism chain)
  4. Mediation and moderation done right
  5. Hypothesis hygiene
  6. Checklist
  7. Anti-patterns
  8. Output format
More from Awesome-Journal-Skills
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About this skill
What does the amj-theory-development skill do?

Use when the theoretical argument and hypotheses are the bottleneck for an Academy of Management Journal (AMJ) manuscript — building a mechanism and deriving testable hypotheses a priori. Constructs the theory; it does not run the analysis (amj-data-analysis) or write the final contribution paragraph (amj-contribution-framing).

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill amj-theory-development --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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