jm-topic-selection
Use when choosing or sharpening a research question for the Journal of Marketing (JM) — testing whether it is substantive, managerially/societally relevant, and JM-fit (vs. JMR, Marketing Science, or JCR). Locks the question; it does not build the conceptual logic (jm-theory-development) or frame the contribution (jm-contribution-framing).
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jm-topic-selection --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Substantive Topic Selection (jm-topic-selection) ## When to trigger - You have a dataset, a phenomenon, or a managerial puzzle but no sharp JM-fit question - You are unsure whether the idea belongs in JM versus JMR, Marketing Science, or JCR - A coauthor says "this is interesting" but no one can name who outside academia should care - Your question feels like "X also matters in setting Y" (a new-context risk) ## The JM fit test JM exists to publish **the most impactful, thought-leading substantive research in the marketing discipline** — knowledge about **real-world marketing questions** useful to scholars, educators, managers, policy makers, consumers, and other societal stakeholders. A JM-fit question must clear three bars at once: 1. **Substantive importance** — it is about a real, consequential marketing phenomenon (a market, a customer, a brand, a channel, a policy, a societal outcome), not a methodological curiosity. 2. **New insight** — it offers a *compelling new understanding*, not a replication of existing theory or an application of known findings to a fresh context. JM explicitly rejects "merely applies an existing set of findings to a new context." 3. **Dual relevanc
- When to trigger
- The JM fit test
- Sharpen the question
- Is it JM — or a sibling?
- Worked example: sharpening a dataset into a JM question
- Early screening questions
- Checklist
- Anti-patterns
- Output format
What does the jm-topic-selection skill do?
Use when choosing or sharpening a research question for the Journal of Marketing (JM) — testing whether it is substantive, managerially/societally relevant, and JM-fit (vs. JMR, Marketing Science, or JCR). Locks the question; it does not build the conceptual logic (jm-theory-development) or frame the contribution (jm-contribution-framing).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jm-topic-selection --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.