knowledge-updater

name	Knowledge Updater
description	Automated skill for keeping AI knowledge bases current with latest model versions, framework updates, and best practices
version	1.0.0
last_updated	"2026-01-06T00:00:00.000Z"
external_version	Self-updating
triggers	["update knowledge","check versions","outdated","latest versions"]

Knowledge Updater Skill

Purpose

Automate the process of keeping AI architecture knowledge current by systematically checking and updating version references across the toolkit.

Why This Matters

AI evolves rapidly:

• GPT-5.2 released December 2025 (just weeks ago)
• Claude Opus 4.5 released November 2025
• Next.js moved from 15 → 16 in months
• Framework versions change weekly

Stale knowledge = bad recommendations = lost credibility.

Update Workflow

Step 1: Discover Current Versions

LLM Models (check monthly)

Search: "[Provider] latest model [current year]"
- OpenAI: GPT-5.x series
- Anthropic: Claude Opus/Sonnet versions
- Google: Gemini versions
- Meta: Llama versions
- Mistral: Latest releases

Agent Frameworks (check weekly)

Sources:
- Vercel AI SDK: https://github.com/vercel/ai/releases
- OpenAI Agents: https://github.com/openai/openai-agents-python/releases
- LangGraph: https://github.com/langchain-ai/langgraph/releases
- Claude SDK: Check Anthropic announcements

Frontend (check monthly)

Sources:
- Next.js: https://github.com/vercel/next.js/releases
- React: https://github.com/facebook/react/releases

AI Gateways (check monthly)

- OpenRouter: Check model count at openrouter.ai/models
- New providers/features

Step 2: Compare Against VERSION-TRACKING.md

Read current versions from dev-docs/VERSION-TRACKING.md and identify deltas.

Step 3: Update Files

If changes detected:

1. VERSION-TRACKING.md

   • Update version numbers
   • Update Last Updated date
   • Add any new technologies

2. Affected Skills

   # In skills/*/SKILL.md frontmatter:
   version: X.Y.Z → X.Y.(Z+1)  # Increment patch
   last_updated: [today]
   external_version: "[new version]"
   

3. CLAUDE.md (if model changes)

   • Update model selection table
   • Update pricing if changed

4. CONTEXT.md

   • Add entry to Recent Changes table

Step 4: Generate Report

## Knowledge Update Report - [DATE]

### Summary
- Technologies checked: X
- Updates found: Y
- Files modified: Z

### Version Changes
| Technology | Previous | Current | Source |
|------------|----------|---------|--------|
| GPT | 5.1 | 5.2 | openai.com |
| ... | ... | ... | ... |

### Skills Updated
- skills/openai-agentkit/SKILL.md
- skills/azure-ai-services/SKILL.md

### Action Required
- [ ] Review changes
- [ ] Commit: `git commit -m "chore: update versions [date]"`
- [ ] Push to remote

Automation Patterns

Cron-Style Schedule

Weekly: Every Monday 9 AM
- Run full version check
- Update if changes found
- Generate report

Monthly: First of month
- Deep check including benchmarks
- Update pricing if changed
- Review deprecated technologies

Event-Triggered

Triggers:
- User says "outdated", "latest", "current version"
- Major AI announcement detected
- Before `/design-solution` command

Best Practices

DO

• Always cite sources for version claims
• Preserve existing skill content, only update metadata
• Generate diff-style report showing changes
• Include benchmark scores when available

DON'T

• Update without verification
• Change skill content beyond metadata
• Skip the report generation
• Forget to update CONTEXT.md changelog

Version Numbering Convention

For skills:

• Major (X.0.0): Complete rewrite, breaking changes
• Minor (X.Y.0): New sections, significant additions
• Patch (X.Y.Z): Version updates, typo fixes, metadata only

Integration with Other Commands

/update-knowledge → /design-solution
                 ↓
         (ensures latest versions used in recommendations)

/update-knowledge → /commit
                 ↓
         (saves updates to git)

---

Fresh knowledge = accurate recommendations = trusted architect