Creator Outreach

Follow shared release-shell rules in:

```
postplus-shared
```
release-shell rules

Use this skill when the user wants to:

find creator or influencer leads across TikTok, Instagram, and X
combine multiple discovery routes into one candidate pool
extract public contact signals such as email or link-in-bio URLs
convert normalized platform datasets into a single outreach-ready lead table
prepare outreach drafts before Gmail or CRM delivery

Read these references before implementation:

skills/50-publishing/creator-outreach/references/lead-schema.md

skills/50-publishing/creator-outreach/references/routing.md

Core Method

Do not lock this skill to one niche, one follower band, or one creator archetype.

Use a two-stage model:

build a candidate pool from one or more discovery routes
run one shared shortlist pass across those candidates

This skill is the shortlist and outreach layer above the platform skills. It should not assume:

only mid-tier creators matter
only one niche matters
keyword account search is the only discovery path
content-first is always the best path

Choose the route that fits the job.

Default posture:

keep the default flow light
add deeper evidence only when the user request clearly needs it

Do not turn every creator discovery task into a full competitor-plus-comments-plus-market-fit investigation by default.

Discovery Routes

Use one or more of these routes before lead building:

1. Official pool route

Examples:

TikTok Shop Seller Center creator marketplace
platform-native creator marketplace exports
manually assembled seller-center handle lists

Use when:

the user already has an official marketplace export
the platform exposes filtering for category, market, follower band, or engagement
the goal is to build a first-pass candidate pool quickly

Current capability:

this skill can ingest exported or manually copied handle lists after they are normalized into local datasets
this skill does not currently automate clicking through seller-center UI
use this route only when the user already has official-pool data or explicitly wants that route

2. Keyword search route

Do not search only category nouns.

Prefer combinations like:

core product term +
```
review
```
core product term +
```
unboxing
```
core product term +
```
haul
```
problem/use-case term +
```
routine
```
commerce tags such as
```
TikTokMadeMeBuyIt
```
,
```
TikTokShop
```
, or platform-native shopping tags when relevant

Use when:

the user needs broad market discovery
the user wants creators actively posting around a product or use case
there is no strong seed list yet

This is a common default discovery route when no stronger seed source exists.

3. Competitor backtracking route

Start from:

competitor brand accounts
competitor product videos
competitor collab posts
competitor comment sections

Inspect:

creators already collaborating with the competitor
posts with shopping or partner signals
active commenters asking for link, shade, size, price, or buying help
likely KOC accounts that can be expanded later

Use when:

the user wants faster conversion-oriented discovery
the user has direct competitors with visible creator activity
the goal is to shorten the path from discovery to outreach

This is an optional enhancement layer, not a default requirement.

4. Content-first route

Find relevant posts first, then pull the authors, then enrich the profiles.

Use when:

the user wants people who are clearly publishing the right content
account names and bios are weak signals
the job is format-aware or content-angle-aware discovery

This is often the best default when follower band and content fit both matter.

5. Known-handle enrichment route

Use when:

the user already has handles
the next step is profile enrichment, contact extraction, or outreach prep

Screening Dimensions

After discovery, shortlist candidates with a shared framework.

Always consider:

account type:
- individual creator
- KOC
- educator / consultant
- brand / product account
- aggregator / media page
content fit:
- does the account repeatedly post around the product, problem, use case, or audience
audience fit:
- target market
- likely audience segment
- language
- market relevance
style fit:
- visual style
- creator tone
- trustworthiness
- cultural fit
engagement quality:
- likes
- comments
- shares
- comment intent quality
outreach readiness:
- public email
- link-in-bio
- past collab signals
- stable posting behavior

Do not treat follower count as the only priority.

Follower band should be chosen per campaign:

head creators for reach
mid-tier creators for repeatable paid or affiliate work
small creators or KOCs for low-cost seeding or testing

Default vs Optional Depth

Default flow:

pick one sensible discovery route
collect platform data
build leads
extract public contact signals
score and shortlist

Optional enhancement layers:

official-pool import
competitor backtracking
comment-intent evidence
TikTok Shop commerce signals
deeper market / language / style review

Only add these when:

the user explicitly asks for them
the core shortlist is weak and the next-best move is to deepen evidence
the campaign type clearly depends on that signal

Avoid stacking all optional layers into the first pass.

Current Automation vs Manual Judgment

This skill can score automatically from local normalized data:

follower scale
visible contact signals
niche overlap from bio and profile text
platform preference
coarse account type inference

This skill cannot reliably infer from current data unless the platform dataset already includes it:

follower geography
precise audience market distribution
deep style quality judgment
language nuance and cultural fit
competitor collaboration history from off-platform evidence
comment-level purchase intent unless comments were explicitly collected upstream

When these factors matter, treat them as required manual or upstream-research checks, not hidden assumptions.

Workflow

1. Choose the discovery route first

Pick the route based on the user request:

official pool export -> normalize or manually structure it, then enrich
broad discovery -> platform search route
competitor scouting -> collect creator candidates from competitor content first
content-angle discovery -> content-first route
known handles -> direct enrichment route

If the user gives no special constraints, prefer the lightest route that is likely to produce a usable shortlist.

2. Collect platform data

Do not scrape raw platform data directly from this skill unless the platform skill is missing something critical.

Use:

```
skills/20-research/tiktok-research
```

skills/20-research/instagram-account-research

```
skills/20-research/x-research
```

The expected input to this skill is normalized profile data or normalized profile-like exports from those platform skills.

The lead builder can also accept richer candidate-like datasets when they already include fields such as:

```
route
```
```
topicFit
```
```
audienceFit
```
```
sourceEvidence
```
engagement proxies
comment or commerce evidence

3. Build a unified lead table

Convert normalized profile datasets into one shared lead schema:

bash

node ${CLAUDE_SKILL_DIR}/scripts/build_creator_leads.mjs \
  --inputs <work-folder>/.postplus/tiktok-profiles.json,<work-folder>/.postplus/instagram-profiles.json,<work-folder>/.postplus/x-profiles.json \
  --output <work-folder>/.postplus/creator-leads.json

4. Extract contact signals

Only use public signals already visible in platform data:

email in bio / signature / description
website or link-in-bio

Do not guess email addresses.

bash

node ${CLAUDE_SKILL_DIR}/scripts/extract_contact_signals.mjs \
  --input <work-folder>/.postplus/creator-leads.json \
  --output <work-folder>/.postplus/creator-leads-enriched.json

5. Score and shortlist

Before drafting, score and filter the lead list when the user wants a shortlist rather than the full dataset.

Important:

treat score as a first-pass ranking, not final truth
apply campaign-specific overrides for market fit, style fit, and creator type
if the dataset does not support those checks, call them out explicitly
do not add deeper evidence collection unless the user request or result quality justifies it

bash

node ${CLAUDE_SKILL_DIR}/scripts/score_creator_leads.mjs \
  --input <work-folder>/.postplus/creator-leads-enriched.json \
  --brief <work-folder>/.postplus/brand-brief.json \
  --platforms tiktok,instagram,x \
  --output <work-folder>/.postplus/creator-leads-scored.json

node ${CLAUDE_SKILL_DIR}/scripts/shortlist_creator_leads.mjs \
  --input <work-folder>/.postplus/creator-leads-scored.json \
  --min-score 45 \
  --top 20 \
  --output <work-folder>/.postplus/creator-leads-shortlist.json

6. Generate outreach drafts

Use a structured brief to generate a draft set.

Minimal brief:

json

{
  "brandName": "Example Brand",
  "productName": "Example Product",
  "niche": "creators relevant to the product, audience, or use case",
  "offer": "a creator partnership or product collaboration",
  "whyYou": "your content feels relevant to this product and audience",
  "cta": "Would you be open to hearing more?",
  "signature": "Name | Brand"
}

Then generate drafts:

bash

node ${CLAUDE_SKILL_DIR}/scripts/generate_outreach_drafts.mjs \
  --leads <work-folder>/.postplus/creator-leads-shortlist.json \
  --brief <work-folder>/.postplus/brand-brief.json \
  --output <work-folder>/.postplus/creator-outreach-drafts.json

Output Expectations

Return:

a shortlist of creators worth contacting
fit scores and fit reasons that explain ordering
contact signals with explicit provenance
explicit notes on missing evidence when market fit or style fit could not be verified from the dataset
risks:
- no email found
- only link-in-bio found
- niche mismatch
- weak audience scale
- uncertain target-market fit
- uncertain style or cultural fit
outreach drafts ready for review or Gmail draft creation

Decision Rules

If the user asks for generic creator discovery, choose the discovery route first instead of defaulting to one search pattern.
If the user already has normalized profile datasets, jump straight to lead building.
If the user has official marketplace exports or a seller-center shortlist, treat that as a first-class input.
If the user wants competitor-based discovery, collect creator candidates from competitor assets before running enrichment.
If the user does not explicitly ask for competitor, comment, official-pool, or commerce-layer evidence, do not force those layers into the default pass.
If the user wants cold email or partnership prep, always extract contact signals before drafting.
Default to drafting, not sending.

Notes

This skill is the cross-platform layer above individual platform research skills.
Gmail sending should stay in a separate delivery step.

creator-outreach

NPX Install

Tags

SKILL.md Content

Creator Outreach

Core Method

Discovery Routes

1. Official pool route

2. Keyword search route

3. Competitor backtracking route

4. Content-first route

5. Known-handle enrichment route

Screening Dimensions

Default vs Optional Depth

Current Automation vs Manual Judgment

Workflow

1. Choose the discovery route first

2. Collect platform data

3. Build a unified lead table

4. Extract contact signals

5. Score and shortlist

6. Generate outreach drafts

Output Expectations

Decision Rules

Notes