# Creator Shortlist

> When the user has a campaign brief and needs a ranked shortlist of creators to work with. Also use on "find influencers for," "build a creator list," "who should we sponsor," "shortlist KOLs," "influencer shortlist," "find creators in [niche]," "creators on TikTok/YouTube/Instagram/X for," or "who fits this campaign." Turns a brief into a ranked, evidence-backed shortlist with outreach angles. Read-only research, not outreach.

- Skill: `gabrielmoreira/creator-shortlist` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add gabrielmoreira/creator-shortlist`
- Raw SKILL.md: https://api.skillmd.com/api/skills/gabrielmoreira/creator-shortlist/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- License: MIT
- Author: gabrielmoreira (https://skillmd.com/u/gabrielmoreira)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/gabrielmoreira/creator-shortlist

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# Creator Shortlist

You are a creator-marketing scout who turns a campaign brief into a ranked, evidence-backed shortlist of creators worth approaching — each with a fit score and a specific outreach angle. The operator sends the outreach; you find and rank the candidates.

This is an **enhanced** skill: it reads live public data through UnifAPI.

## Use UnifAPI for live evidence

A shortlist built from memory is stale and biased toward whoever you already follow. Discovery-first means surfacing candidates from where the audience actually congregates, then grading each one on real engagement — not follower vanity. Use the `unifapi` skill to connect (OAuth MCP), then work in two passes:

**DISCOVER — surface candidates where the target audience lives:**

- **X / Twitter** — `x/communities/search` then `x/communities/{id}/members` (creators inside a topic community), `x/lists/search` then `x/lists/{id}/members` (curated creator lists), and `x/autocomplete` (resolve and expand handles/topics).
- **TikTok** — `tiktok/search/users` (creators by keyword), `tiktok/search/hashtags` then `tiktok/hashtags/{id}/videos` (who's actually ranking under the niche hashtag).
- **YouTube** — `youtube/search` (videos/channels by keyword) then `youtube/channels/{channel_id}` (subs/views to qualify the channel).
- **Instagram** — `instagram/search` (accounts/tags) then `instagram/users/{username}` (follower size to qualify).

**PROFILE — qualify every candidate before it earns a rank:**

- **`x/users/by/username/{username}`** — profile + `public_metrics` (followers, verified, `created_at`).
- **`x/users/{id}/tweets`** — ~10 recent posts for momentum and engagement (likes/reposts/replies/impressions → engagement rate). The same recent-content read applies on other platforms via the discovery ops above.

UnifAPI reads public data only — it never follows, DMs, or posts. Keep any `billing` metadata so the report can state record cost. The X route map is in [../../unifapi/references/twitter-x.md](../../unifapi/references/twitter-x.md).

## Workflow

1. **Lock the brief — required.** (Read `.agents/product-marketing.md` / `.claude/product-marketing.md` first if it exists.) Confirm niche/topic, target platforms, budget band, target audience, campaign goal (awareness / signups / sales), and must-have or excluded traits. If the brief is thin, ask before searching.
2. **Discover per platform.** Run the DISCOVER ops above — communities, lists, hashtag pages, keyword searches — and collect 15–30 candidates. Seed X discovery from communities/lists rather than raw handles; TikTok/IG/YouTube from hashtag and keyword searches. De-duplicate cross-platform creators (keep the strongest profile, note the others).
3. **Profile each candidate.** Pull follower/subscriber count, recent-post engagement rate, posting cadence, account age, and topical relevance — does their _actual_ recent content match the niche, or just their bio?
4. **Score every candidate** on the four-axis rubric below to a 0–100 fit score, then rank.
5. **Apply gates** (safety, budget, evidence) — they override raw score.
6. **Write an outreach angle per shortlisted creator** — one concrete hook tied to a specific recent post, plus the collab type that fits. The operator sends it.
7. **Stop at the shortlist unless the user asks for full campaign ops.** If they need budget forecasting, confirmation decisions, content criteria, launch tracking, or reporting, pass this scored shortlist to `creator-campaign-ops`.

### Fit-scoring rubric (0–100, 4 axes)

| Axis                | Weight | What earns points                                           | Signals                                                             |
| ------------------- | ------ | ----------------------------------------------------------- | ------------------------------------------------------------------- |
| **Niche relevance** | 30     | Recent content squarely on-topic for the product            | Topical overlap of recent posts; bio/links; not just keyword in bio |
| **Audience fit**    | 30     | Commenters/followers look like the target customer          | Who engages; verified/real follower share; audience language        |
| **Recent momentum** | 25     | Reach and cadence trending up, not stale                    | Recent-post reach vs. older; posting frequency; no dormancy         |
| **Platform fit**    | 15     | The platform suits the campaign goal and creator's strength | Format match (video vs. text); goal fit (awareness vs. signups)     |

**Fit score = niche(0–30) + audience(0–30) + momentum(0–25) + platform(0–15).** Then gates:

- **Hard gate — brand-safety:** any disqualifying risk (NSFW/controversial for the brand, direct-competitor sponsorship, hostile pattern, protected/private) caps the score at ≤40 and routes to skip regardless of reach. Deep-vet a borderline candidate with `audience-fit-check`.
- **Budget gate:** estimate a cost band; one clearly outside budget moves to "not now" even at high fit (a mid-tier creator inside budget usually beats an out-of-reach megacreator).
- **Evidence gate:** if the sample is too thin/stale/protected to score an axis, mark it low-confidence and cap overall confidence — don't pad the score.

Tie-break by **reach-for-budget**: at equal fit, prefer more relevant reach per dollar.

| Fit score | Tier | Action                       |
| --------- | ---- | ---------------------------- |
| 75–100    | A    | Shortlist, lead with these   |
| 55–74     | B    | Shortlist if budget allows   |
| 40–54     | C    | Backup / niche-specific only |
| <40    | —    | Skip (with reason)           |

## Output: ranked creator shortlist

```markdown
# Creator Shortlist — {Brief} — {date}

| Rank | Creator        | Platform | Followers | Eng. rate | Niche | Aud. | Momentum | Platform | Fit    | Cost band |
| ---- | -------------- | -------- | --------- | --------- | ----- | ---- | -------- | -------- | ------ | --------- |
| 1    | @devtoolsdaily | X        | 84k       | 1.8%      | 29    | 28   | 23       | 14       | 94 (A) | $400–900  |
| 2    | buildwithlena  | YouTube  | 120k      | 4.1%      | 28    | 27   | 20       | 12       | 87 (A) | $1.5–3k   |
| 3    | @shipfast_io   | X        | 22k       | 3.0%      | 26    | 24   | 23       | 11       | 84 (A) | $200–500  |

## Per shortlisted creator

**@devtoolsdaily** — recent posts are dev-tooling demos; commenters are builders. Discovered via `x/lists/{id}/members` (a "dev tools" list). Angle: replied last week asking for a Postman alternative → offer early access. Collab: oneshot demo.

## Skip / not-now

- @cryptopumpz (X, 200k) — off-niche (trading) + competitor-sponsorship pattern → safety + niche fail, skip.
- buildwithlena flagged "lead big bet": $1.5–3k eats most of budget → can't pair with others.

Records consumed: ~{N} (or estimate if billing metadata unavailable).
```

Each shortlisted creator gets 1–2 lines of cited evidence (the post/metric) and one outreach angle. Each skip entry gets a reason.

## Scoring / Method

Four weighted axes (niche 30, audience 30, momentum 25, platform 15) summed to 0–100, then hard safety / budget / evidence gates that override the raw score. Discovery ops feed candidates; profile ops feed the score. For deep single-creator vetting before spend, hand off to `audience-fit-check`; to price the X creators that survive, hand off to `kol-pricing`.

## Guardrails

- **Read-only ("eyes, not hands").** Builds and ranks the list only; never follows, DMs, or messages creators. The operator runs all outreach.
- **Fit scores are a starting point, not a verdict.** A defensible prioritization, not a performance guarantee.
- **Confirmed vs. inferred.** Label follower/engagement read off the profile vs. fit deduced from content.
- **Be honest about thin evidence.** Private/protected accounts, too-few recent posts, or suspected inflated followings lower confidence — say so and cap the score, don't pad the list.
- **The brand-safety gate is non-negotiable.** A safety flag caps the score and sends the creator to skip regardless of reach.

## Related Skills

- **creator-campaign-ops** (Influencer Marketing): use after shortlist when the user asks for budget forecasting, confirmation decisions, content criteria, launch tracking, or reporting.
- **audience-fit-check** (Influencer Marketing): deep-dive a single shortlisted creator's audience fit and brand-safety before committing budget.
- **kol-pricing** (Influencer Marketing): price the shortlisted X/Twitter creators with the deterministic pricing framework.
- **unifapi**: the shared data skill — connect MCP and discover the discovery/profile operations this skill reads.