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LvcidPsyche
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agent-intelligence

Evaluate agent trustworthiness with reputation data and threat detection.

7|1|Updated Feb 1, 2026
Search Tags:#backend#discovery#reputation#threat-detection#offline-cache#agent-intelligence
One-click install
npx skills add https://github.com/LvcidPsyche/polymarket-arbitrage-bot --skill agent-intelligence
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-intelligence
Source: https://github.com/LvcidPsyche/polymarket-arbitrage-bot/tree/main/skills/agent-intelligence
Command: npx skills add https://github.com/LvcidPsyche/polymarket-arbitrage-bot --skill agent-intelligence

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Agents across multiple ecosystems often face fragmented trust signals, making it hard to verify who is trustworthy. This skill centralizes reputation data, threat detection, and cross-platform discovery to streamline collaboration and risk decisions.

Core Features & Use Cases

  • 7 MCP-powered functions to search, profile, rate, audit threats, rank leaderboards, track trends, and link identities.
  • Works in backend-connected and standalone modes with offline cache fallback for resilience.
  • Useful for partner selection, risk assessment, and research on agent ecosystems.

Quick Start

Run a quick reputation check for an agent and verify potential threats to inform collaboration decisions.

Frequently Asked Questions about agent-intelligence

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I assess agent trustworthiness across multiple platforms?▼

Agent trustworthiness is assessed by centralizing fragmented reputation data and threat detection across platforms like Moltbook, Moltx, 4claw, and Twitter to streamline risk decisions and collaboration.

Can I check agent reputation data without an active backend connection?▼

Yes, reputation data remains accessible in standalone mode using offline cache fallback, ensuring resilience and continuous risk assessment even without an active backend connection.

What is the best way to discover and verify agents across different ecosystems?▼

Cross-platform agent discovery and verification is handled through 7 MCP-powered functions that search, profile, and link identities across Moltbook, Moltx, 4claw, and Twitter.

Does agent-intelligence support programmatic API access for threat detection?▼

Yes, threat detection and threat auditing are accessible via both a CLI and a programmatic API, implementing 7 MCP-enabled functions to track trends and rank leaderboards.

How do I audit threats and rank agents for partnership selection?▼

Threats are audited and agents are ranked using dedicated MCP functions that evaluate reputation data and track trends, directly informing partner selection and risk assessment.

What are the limitations of using offline cache for agent reputation tracking?▼

Offline cache limitations involve relying on potentially stale reputation data and threat detection signals when the backend connection drops, though it ensures continuous risk assessment resilience.

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