mksc-literature-positioning
Use when positioning a Marketing Science manuscript in its literature — locating the contribution among structural and analytical modeling precedents and the relevant substantive stream (pricing, advertising/digital, channels/retail, branding, platforms, analytics), and disclosing self-overlap. Positions the paper; it does not state the headline contribution (mksc-contribution-framing).
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mksc-literature-positioning --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.
# Literature Positioning (mksc-literature-positioning) ## When to trigger - The intro reads as "no one has modeled X" (gap-spotting) rather than joining a modeling conversation - You are unsure which precedent papers define your model's baseline - Reviewers may say "this is a small extension of an existing model" - You build on your own prior work and must disclose how this paper goes beyond it ## Position on two axes at once A Marketing Science paper sits at the intersection of a **modeling lineage** and a **substantive stream**. Make both explicit. 1. **Modeling lineage.** Which model is your baseline — a BLP-style demand system, a dynamic discrete-choice model, a channel/Stackelberg pricing game, an auction or search model? State what you add to it (a new mechanism, richer dynamics, a novel identification strategy, a tractable closed form) and why prior models could not answer your question. 2. **Substantive stream.** Which marketing problem — pricing, advertising/digital and attribution, branding, distribution channels and retailing, platforms/two-sided markets, or marketing analytics/ML — does the paper speak to? Tie the model's payoff to that stream's open questions. ## From
- When to trigger
- Position on two axes at once
- From gap-spotting to a real contribution
- Self-overlap disclosure (required)
- Checklist
- Anti-patterns
- Positioning pass for Marketing Science
- Output format
What does the mksc-literature-positioning skill do?
Use when positioning a Marketing Science manuscript in its literature — locating the contribution among structural and analytical modeling precedents and the relevant substantive stream (pricing, advertising/digital, channels/retail, branding, platforms, analytics), and disclosing self-overlap. Positions the paper; it does not state the headline contribution (mksc-contribution-framing).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill mksc-literature-positioning --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.