liuku-xianzei

Score knowledge items by claims, evidence, and application with contamination risk.

10|1|Updated May 4, 2026
One-click install
npx skills add https://github.com/isLinXu/under-one --skill liuku-xianzei
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: liuku-xianzei
Source: https://github.com/isLinXu/under-one/tree/main/underone/skills/liuku-xianzei
Command: npx skills add https://github.com/isLinXu/under-one --skill liuku-xianzei

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Helps transform messy, mixed-credibility information into structured knowledge units while preventing low-quality or potentially contaminated content from polluting long-term memory through risk scoring and quarantine/inheritance queues.

Core Features & Use Cases

  • Gradient knowledge digestion: Scores each item on core claim, evidence, and application using configurable keyword gradients plus semantic signals, then outputs a digestion report.
  • Freshness & review scheduling: Computes category-based freshness windows and generates a review (反刍) schedule to keep knowledge actionable over time.
  • Contamination risk control: Produces a contamination risk score and separates knowledge into inheritance_queue (safe to keep) and quarantine_queue (requires review).
  • Use case: You ingest research notes, blog posts, and forum discussions; this skill digests them into units with freshness days, decides which ones to inherit vs quarantine, and tells you when to review each unit.

Quick Start

Use the liuku-xianzei skill to digest an input file named info.json and produce digest_report.json with knowledge units, freshness windows, and review plans.

Frequently Asked Questions about liuku-xianzei

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

FAQPage Schema
How do I schedule review plans for ingested research notes?

To schedule review plans, this skill digests input knowledge items and generates structured units with freshness-days and expiry dates. It then creates a configurable re-review schedule to maintain long-term retention of your research notes.

What is contamination risk scoring in knowledge management?

Contamination risk scoring evaluates mixed-credibility information to prevent low-quality content from polluting memory. It calculates a risk score to separate knowledge into an inheritance queue for safe items and a quarantine queue for content requiring review.

How do I digest forum discussions into structured knowledge units?

You digest forum discussions by computing a gradient digestion score across core claims, evidence, and application. The skill applies information density and credibility weighting to transform messy inputs into structured knowledge units.

Can I use this skill to manage memory inheritance for blog posts?

Yes, you can manage memory inheritance for blog posts. The skill evaluates content credibility and contamination risk, routing safe knowledge units into an inheritance queue to support secure long-term memory inheritance.

What is the best way to prevent knowledge contamination from low-quality sources?

The best way to prevent knowledge contamination is applying contamination risk scoring to incoming information. This process identifies potentially polluted content and isolates it into a quarantine queue before it can enter long-term memory.

Why does my knowledge freshness scheduling expire important information?

Knowledge freshness scheduling expires information because it computes category-based freshness windows with expiry dates. This ensures outdated content is flagged for a re-review schedule, keeping your actionable knowledge base accurate over time.