smithery/gtmagents

fraud-detection

Use to monitor, investigate, and prevent abuse within referral programs.

Installation

$ npx skills add smithery/gtmagents --skill fraud-detection

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from smithery/gtmagents · top by installs.

npx skills add smithery/gtmagents

Browse all from smithery/gtmagents

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,338 B
  • docs SUMMARY.md 95 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Referral Fraud Detection Skill

When to Use

  • Designing safeguards for new referral initiatives.
  • Investigating suspicious referral spikes, duplicate accounts, or payout anomalies.
  • Reporting on program integrity for finance, legal, or compliance teams.

Framework

  1. Signal Collection – IP/device matching, velocity checks, blacklist databases, manual reviews.
  2. Scoring Model – assign risk scores by cohort (new accounts, high-volume referrers, geo mismatch).
  3. Workflow Automation – auto-flag, queue for review, or pause rewards until verified.
  4. Investigation Runbook – define evidence gathering, communication templates, and resolution paths.
  5. Feedback Loop – update heuristics, adjust incentives, and communicate policy changes.

Templates

  • Fraud monitoring dashboard outline (metrics, thresholds, owners).
  • Investigation log (case ID, referrer, signals, action taken, notes).
  • Policy update checklist (legal, comms, ops, partner notifications).

Tips

  • Combine automated checks with random manual audits for accuracy.
  • Align with legal/finance on clawback procedures before launch.
  • Share learnings with incentive-design to discourage risky behavior.