Agent skill
Knowledge Updater
Automated skill for keeping AI knowledge bases current with latest model versions, framework updates, and best practices
Install this agent skill to your Project
npx add-skill https://github.com/frankxai/ai-architect/tree/main/skills/knowledge-updater
SKILL.md
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:
-
VERSION-TRACKING.md
- Update version numbers
- Update
Last Updateddate - Add any new technologies
-
Affected Skills
yaml# In skills/*/SKILL.md frontmatter: version: X.Y.Z → X.Y.(Z+1) # Increment patch last_updated: [today] external_version: "[new version]" -
CLAUDE.md (if model changes)
- Update model selection table
- Update pricing if changed
-
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
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