tiktok-influencer-finder — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited tiktok-influencer-finder (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Search for TikTok influencers matching a specific niche using Apify's Influencer Discovery Agent.
Requires requests and either GOOSEWORKS_API_KEY or APIFY_API_TOKEN env var.
# Basic search
python3 skills/tiktok-influencer-finder/scripts/find_influencers.py \
--description "fitness coaches for women over 40"
# With follower filters
python3 skills/tiktok-influencer-finder/scripts/find_influencers.py \
--description "AI and tech reviewers" \
--min-followers 10000 --max-followers 500000
# Summary table output
python3 skills/tiktok-influencer-finder/scripts/find_influencers.py \
--description "vegan cooking creators" --output summary
# CSV export
python3 skills/tiktok-influencer-finder/scripts/find_influencers.py \
--description "sustainable fashion" --output csvBefore running the search, ask the user for their filtering criteria. Collect ALL of the following:
Ask all 5 criteria in a single question to minimize back-and-forth. Provide sensible default options but always allow custom input.
Compose a detailed --description combining the user's niche, content style preferences, and target audience. Be specific and descriptive.
python3 skills/tiktok-influencer-finder/scripts/find_influencers.py \
--description "fitness coaches targeting women over 40, focus on home workouts and healthy aging" \
--min-followers 5000 --max-followers 500000 \
--min-fit 0.6 \
--output jsonThe script uses apify~influencer-discovery-agent actor. It routes through the GooseWorks proxy when GOOSEWORKS_API_KEY is set, or directly to Apify when APIFY_API_TOKEN is set.
After receiving results, apply the user's criteria:
fit score and fitDescription to judge relevance; generally exclude fit < 0.6)Present filtered results in a clean markdown table:
| Creator | Handle | Followers | Engagement | Location | Focus | Fit Score |
Include:
After the table, include:
| Flag | Default | Description |
|---|---|---|
--description | required | Describe the type of influencer to find |
--keywords | 5 | Number of search keywords to generate (max 5) |
--profiles-per-keyword | 10 | Profiles per keyword (max 10) |
--min-followers | none | Minimum follower count filter |
--max-followers | none | Maximum follower count filter |
--min-fit | 0.0 | Minimum fit score (0.0-1.0) |
--output | json | Output format: json, csv, summary |
--token | env var | Apify token (overrides env vars) |
--timeout | 300 | Max seconds for Apify run |
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.