| name | influencer-discovery |
| slug | influencer-discovery |
| displayName | Influencer Discovery · 红人发现 |
| summary | 多平台红人挖掘:候选池、画像与互动指标、真实性红旗筛查、分层短名单 |
| description | Use when the user asks to "find influencers", "build an influencer list", or "discover creators in [niche]"; produces a multi-platform candidate pool, per-influencer profiles, authenticity red-flag screening, and a tiered shortlist with preliminary triage signals. Not for STAR scoring or ranking a known shortlist — use fit-scorer. 达人挖掘/找达人/创作者名单 |
| version | 19.2.0 |
| license | Apache-2.0 |
| compatibility | Claude Code and compatible agent-skill hosts |
| homepage | https://github.com/aaron-he-zhu/aaron-marketing-skills |
| when_to_use | Activate when building an influencer roster from scratch, expanding into a new platform or niche, replacing churned partners, finding micro and nano creators at scale, identifying which influencers a competitor partners with, or standing up an always-on discovery pipeline. The user names a niche, platform, follower band, or brand and wants a list of candidate creators to evaluate. |
| argument-hint | <brand or niche> [platform] [follower-range] |
| metadata | {"author":"aaron-he-zhu","version":"19.2.0","discipline":"influencer","phase":"scout","geo-relevance":"low","hermes":{"tags":["marketing","influencer","scout"],"category":"influencer"},"openclaw":{"emoji":"📣","homepage":"https://github.com/aaron-he-zhu/aaron-marketing-skills"}} |
Influencer Discovery
Find the right influencers for your brand by searching across platforms, screening for audience fit and authenticity, and building a tiered candidate list ready for scoring.
Quick Start
Find 20 influencers in [niche] for [brand/product]
Find influencers in [niche] with 50K-200K followers on TikTok and Instagram,
based in [location], engagement above 4%, who have worked with brands like [brand]
Skill Contract
- Reads: brand/product, niche or category, target platforms, follower range, engagement floor, location/language, audience demographics, exclusions; prior
entity-registry brand profile and any audience-mapper output if present in memory; existing roster records under memory/creators/ (dedupe the candidate pool against creators already rostered by creator-registry).
- Writes: only with separate exact authorization, discovery results to
memory/influencer/influencer-discovery/YYYY-MM-DD-<topic>.md — search criteria, candidate pool stats, per-influencer profiles, tiered shortlist with preliminary triage signals. Roster-worthy shortlisted creators (verified handles, contact path, audience stats) go as one-line updates to memory/events/creators.ndjson only via a separately authorized operation: propose request to registry-events.py — only creator-registry writes canonical records under memory/creators/.
- Promotes: only with separate exact authorization, durable facts (top-tier handles, confirmed niche/platform mix, competitor-saturated creators) to
memory/hot-cache.md.
- Done when:
- The required search criteria are present; otherwise stop with
NEEDS_INPUT and name the missing criteria without fabricating candidates.
- A candidate pool exists with at least the requested count screened past follower, engagement, and brand-safety filters.
- Each shortlisted influencer has a profile with metrics, audience read, and a preliminary discovery-triage signal that is not a STAR Suitability score.
- A tiered shortlist (must-reach / strong / consider) is compiled with next-step pointers.
- Primary next skill: fit-scorer — score and rank the discovered candidates with weighted criteria.
