Knowledge Updater

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)

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Fresh knowledge = accurate recommendations = trusted architect