vargasjr-dev/mycadet-temp/influencer

Claude Code and agent skill by vargasjr-dev/mycadet-temp

Trust tier 2
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Research influencers on Instagram, TikTok, and X/Twitter through your browser

Install

npx vskill@latest install vargasjr-dev/mycadet-temp/influencer

SKILL.md

Use browser automation for collection and host_bash helper scripts for deterministic parsing, scoring, and comparison. All browser operations are executed through the assistant browser CLI, invoked via host_bash.

Required tools

  • host_bash for assistant browser CLI commands and helper scripts in scripts/.

Step graph (state machine)

Step 1: Route intent

Use deterministic routing when intent is unclear:

bash
bun {baseDir}/scripts/influencer-intent.ts --request "<latest user request>" --has-candidates <true|false> --has-shortlist <true|false>

Use returned step to route to discover, enrich_profile, or compare_shortlist.

Step 2: Discover candidates (discover)
Instagram
  1. Navigate to keyword search/post surfaces.
  2. Snapshot + extract:
bash
assistant browser --session influencer --json snapshot
assistant browser --session influencer --json extract --include-links
  1. Parse candidates:
bash
bun {baseDir}/scripts/influencer-parse-candidates.ts --platform instagram --input-json '<json payload with extracted text/links>'
TikTok
  1. Navigate to user search page for query.
  2. Use assistant browser --session influencer scroll + assistant browser --session influencer wait-for to load additional candidates.
  3. Extract and parse:
bash
bun {baseDir}/scripts/influencer-parse-candidates.ts --platform tiktok --input-json '<json payload with extracted text>'
X/Twitter
  1. Navigate to people search view (f=user).
  2. Snapshot + extract:
bash
assistant browser --session influencer --json snapshot
assistant browser --session influencer --json extract --include-links
  1. Parse:
bash
bun {baseDir}/scripts/influencer-parse-candidates.ts --platform twitter --input-json '<json payload with extracted text/links>'
Step 3: Enrich profiles (enrich_profile)

For each selected candidate profile:

  1. Navigate to profile URL.
  2. Snapshot + extract profile metadata (bio, follower counts, verification indicators).
  3. Score with criteria:
bash
bun {baseDir}/scripts/influencer-score.ts --query "<user query>" --min-followers <n> --max-followers <n> --verified-only <true|false> --input-json '<json payload with profiles>'
  1. If themes are missing, enrich using:
bash
bun {baseDir}/scripts/influencer-theme-extract.ts --bio "<bio>" --query "<user query>"
Step 4: Build shortlist (compare_shortlist)

Generate deterministic comparison output:

bash
bun {baseDir}/scripts/influencer-compare.ts --limit <n> --input-json '<json payload with profiles and criteria>'

Present results grouped by platform with:

  • Username / display name
  • Followers (normalized)
  • Verification status
  • Theme highlights
  • Profile URL

Retry and fallback policy

  • Retry budget: 3 attempts for each state-changing browser step.
  • After any navigation or click that changes DOM, run fresh assistant browser --session influencer --json snapshot.
  • If blocked by sign-in wall or challenge after retries, ask user to complete that step and resume from latest successful state.

Platform notes

  • Instagram search often surfaces posts/reels before profiles; use author-handle pivot logic.
  • TikTok search can require scroll cycles to load profile cards.
  • X/Twitter should use people-search surfaces to avoid irrelevant mixed-content feeds.

Example helper payload shape

json
{
"phase": "discover",
"context": { "platform": "instagram" },
"extracted": {
"text": "...",
"links": ["https://www.instagram.com/example/"]
},
"userIntent": "find fitness creators"
}

Security

  • Security scanPassed, 96 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

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Source

Popularity

Repository stars
58
Repository forks
6
7-day trend score
0

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