# Data And Original Research

> >-

- **Type:** Skill
- **Install:** `agentstack add skill-social-media-skills-skills-data-and-original-research`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [social-media-skills](https://agentstack.voostack.com/s/social-media-skills)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [social-media-skills](https://github.com/social-media-skills)
- **Source:** https://github.com/social-media-skills/skills/tree/main/skills/data-and-original-research
- **Website:** https://social-media-skills.com

## Install

```sh
agentstack add skill-social-media-skills-skills-data-and-original-research
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# data-and-original-research

The **original-data content type** — find a question inside a data void, run a sound method, analyse it honestly,
voice the one finding that travels, and engineer it for citation. A study people *have to cite*; the **format
writers** turn it into cuts, **WoopSocial publishes**, and recurring studies map into the **content-calendar.**

## The POV: own a number and the internet has to come to you
Most content is undifferentiated — ~94% of published pages earn zero external links (per Backlinko). Original
data is the rare exception: publications link to **stories, not products**, and a data finding is a story. It's
also the **#1 GEO asset** — adding statistics is among the strongest levers for AI-answer visibility (per the
Princeton/KDD GEO study), and original data is statistics nobody else owns. Brands skip it because it's harder
than a listicle — which is exactly the moat. The catch: a study is worth **nothing the moment one number is
wrong.** Rigor isn't pedantry; it's the entire value. So the skill is knowing **what** to study, **how** to get
real data, and how to make the finding **impossible not to cite** — never inventing it.

## Read these first
1. **brand-profile** — the proprietary data/angle you actually own.
2. **audience-research** — the question your audience (and journalists/AI) would cite.

## The framework: PROVE
(Depth: `references/the-prove-framework.md`.)
- **P — Pick a question inside a data void:** a claim worth proving where good data doesn't exist and people
  would cite the answer; advantage order = proprietary data > recurring niche survey > public-dataset analysis.
- **R — Run a sound method:** define population, sample frame, target n, recruitment, and neutral (non-leading)
  questions **before** collecting; the agent designs, the human/tool fields it.
- **O — Observe honestly:** real data only; **never invent or AI-synthesize data points**; no p-hacking or
  cherry-picking; disclose n, dates, method, limitations; small n = directional, not "most people."
- **V — Voice the one finding that travels:** the surprising-but-defensible headline stat (X% of Y do Z),
  supported and never inflated (38% ≠ "nearly half"); one hero number, 2–3 supporting.
- **E — Engineer for citation, then distribute:** report page with visible methodology + date + "Last Updated"
  stamp + charts + a **copy-paste stat box with attribution link**; atomize into cuts → the format writers;
  pitch journalists; seed across publications (the citation multiplier); WoopSocial publishes.

## The reality (verify-quarterly)
Data-led content is the backbone of digital PR (~94.8% name it their primary tactic; original data ~+41% media
coverage — per BuzzStream); data studies attract ~3.2× more links than opinion/how-to (per Backlinko via
Searchlab). For AI search: adding statistics can lift AI-answer visibility ~30–41% (Princeton/KDD GEO study,
cited — attribute); brand **mentions** can correlate with AI visibility more than raw links (Ahrefs ~75k-brand
analysis); distributing across many publications multiplies citations; ~50% of AI-cited content is  survey > public dataset > experiment), designed before collection (population, sample frame, n,
neutral questions), analysed honestly (no p-hacking, no cherry-picking, limitations disclosed, small n framed as
directional), with one surprising-but-defensible headline stat that's supported and never inflated; engineered
for citation (visible methodology + date + "Last Updated" stamp + charts + copy-paste stat box with attribution
link), atomized into cuts routed to the right format writers, pitched/distributed across publications, and
published via WoopSocial; measured on referring domains/mentions/AI-citations/referral traffic/saves rather than
likes; YMYL, privacy/consent, and conflict-of-interest handled; **nothing fabricated**; and correctly
distinguished from educational-content-and-how-to, analytics-and-reporting, competitor-analysis, and trend-jacking.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [social-media-skills](https://github.com/social-media-skills)
- **Source:** [social-media-skills/skills](https://github.com/social-media-skills/skills)
- **License:** MIT
- **Homepage:** https://social-media-skills.com

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-social-media-skills-skills-data-and-original-research
- Seller: https://agentstack.voostack.com/s/social-media-skills
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.