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Filter AI Relevant

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filter-ai-relevant

Filter AI Relevant is an Agent Skill for documents published in the majiayu000/claude-skill-registry repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

DEPRECATED: This skill has been replaced by the analyze-article skill which provides more accurate AI-relevance filtering through LLM analysis rather than simple keyword matching.

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How to use this skill

Bring this guide into your coding agent with a prompt tailored to the tool you use.

  1. Open your project in Codex.
  2. Copy and paste the prompt below.
  3. Review files and risks before approving any action.
Prompt to paste
Inspect the Agent Skill at https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/other/filter-ai-relevant/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/filter-ai-relevant, but wait for my approval before writing files or running scripts.

Copying this prompt does not install or run the skill. Review third-party files before use.

Filter AI-Relevant Articles (DEPRECATED)

⚠️ DEPRECATED: This skill has been deprecated as of v2.0.0.

AI relevance filtering is now handled by the analyze-article skill, which uses LLM analysis to accurately categorize and filter articles rather than simple keyword matching.

Migration Guide

Before (v1.0)

Filtering used keyword matching:

  1. fetch-rss-feeds - Collect articles
  2. filter-ai-relevant - Keyword-based filtering
  3. analyze-article - LLM analysis

After (v2.0)

LLM analysis handles relevance determination:

  1. fetch-rss-feeds - Collect articles (with dedup)
  2. analyze-article - LLM categorizes AND filters for relevance

How to Migrate

If you were using filter-ai-relevant, update your workflow to rely on analyze-article for relevance filtering.

The new approach:

  • analyze-article categorizes articles as: research, business, product, security, policy, general
  • Articles can be filtered by category after analysis
  • LLM provides more nuanced relevance determination than keywords

Replacement Skill

Old ApproachNew Approach
Keyword matchingLLM-based analysis
Binary AI/not-AICategory classification
Hardcoded keyword listContext-aware analysis
False positives on "meta"Semantic understanding

Why Deprecated

  1. Better accuracy: LLM understands context, not just keywords
  2. Richer output: Categories instead of binary relevance
  3. No maintenance: No keyword list to maintain
  4. Semantic matching: Understands synonyms and related concepts

Example Comparison

Keyword approach (old):

  • "Meta releases new AI model" → filtered (contains "AI")
  • "Facebook updates metadata API" → filtered (contains "meta")
  • "Novel transformer architecture for proteins" → missed (no exact keyword)

LLM approach (new):

  • "Meta releases new AI model" → category: product, AI-relevant
  • "Facebook updates metadata API" → category: general, not AI-focused
  • "Novel transformer architecture for proteins" → category: research, AI-relevant

See Also