skills.rest
skywatch-bsky
skywatch-bskyOFFICIAL
Explore all skills by this author →
WebsiteGitHub

skywatch-assess-account

Assess AT Protocol accounts by aggregating behavioral signals and moderation history.

6|Updated Feb 21, 2026
Search Tags:#investigation#moderation#atproto#trust-and-safety#osprey#account-profiling
One-click install
npx skills add https://github.com/skywatch-bsky/skywatch-agent-skills --skill skywatch-assess-account
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skywatch-assess-account
Source: https://github.com/skywatch-bsky/skywatch-agent-skills/tree/main/polytoken/skills/skywatch-assess-account
Command: npx skills add https://github.com/skywatch-bsky/skywatch-agent-skills --skill skywatch-assess-account

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill eliminates inconsistent, ad-hoc manual profiling of AT Protocol accounts by providing a structured, repeatable framework for data collection, classification, and moderation recommendations.

Core Features & Use Cases

  • Structured Assessment: Orchestrates multi-phase data collection across ClickHouse, PDS records, and Ozone moderation logs to build a comprehensive account profile.
  • Automated Classification: Applies a rigorous schema to categorize accounts as genuine, bot, IO, scam, spam, or policy violator based on statistical signals and policy precedents.
  • Use Case: Use this skill during Phase 2 of an investigation to determine if a suspicious account is a coordinated bot network participant or a genuine user, ensuring consistent enforcement actions.

Quick Start

Use the skywatch-assess-account skill to perform a full investigation on the account with DID did:plc:example12345.

Frequently Asked Questions about skywatch-assess-account

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

FAQPage Schema
How do I conduct a structured AT Protocol account investigation?▼

Structured account assessment orchestrates multi-phase data collection across ClickHouse, PDS records, and Ozone moderation logs to build comprehensive profiles for consistent, evidence-based moderation recommendations.

What is the best way to classify suspicious AT Protocol accounts as bots or spam?▼

Automated classification applies a rigorous schema to categorize AT Protocol accounts as genuine, bot, IO, scam, spam, or policy violator based on statistical signals and policy precedents for consistent enforcement.

Do I need ClickHouse and Ozone moderation APIs to assess AT Protocol accounts?▼

Yes, full account assessment requires integration with ClickHouse, PDSx tools, and Ozone moderation APIs to aggregate behavioral signals and generate consistent, evidence-based moderation recommendations.

Can I use this approach to identify coordinated bot network participants on AT Protocol?▼

Yes, structured account assessment during Phase 2 of an investigation determines if a suspicious account is a coordinated bot network participant or a genuine user, ensuring consistent enforcement actions.

Why does manual profiling of AT Protocol accounts produce inconsistent moderation results?▼

Manual profiling produces inconsistent results because it relies on ad-hoc data collection and classification, whereas a structured, repeatable framework ensures consistent, evidence-based moderation recommendations.

Related Skills

Explore More Data & Analytics Skills→
skywatch-bskyskywatch-bsky
6

assess-account

Aggregate ClickHouse, PDS, and Ozone data to classify AT Protocol accounts.

Official
Advanced
skywatch-bskyskywatch-bsky
6

working-the-queue

Automate moderation queue triage by gathering context and recommending classifications.

Official
Advanced
skywatch-bskyskywatch-bsky
6

skywatch-conducting-investigations

Investigate suspicious AT Protocol accounts using a six-phase methodology.

Official
Advanced
xenotaurxenotaur
1

lrh-implement

Execute software development tasks through a structured planning, implementation, and validation workflow.

Community
Advanced