Wiki Gap Analysis: Status Tracker (April 2026)#
Generated from 6 conversational query tests against the wiki. 20 gaps identified, 15 addressed, 5 remaining.
Addressed (15 ✅)#
| # | Gap | How Addressed |
|---|---|---|
| 1 | Getting started tutorial | getting-started-guide — 5-phase roadmap from single agent to multi-agent |
| 2 | LangGraph + Mem0 integration | langgraph-mem0-integration — DigitalOcean step-by-step tutorial |
| 5 | Agent observability tooling | multi-agent-observability — OpenTelemetry spans, debugging patterns |
| 6 | Memory quality metrics | memory-lifecycle-drift — decay scoring, confidence, contradiction detection |
| 7 | Memory regression testing | memory-lifecycle-drift — lifecycle components as automated maintenance |
| 9 | CrewAI practical examples | crewai-production-guide — content pipeline, customer support, event-driven patterns |
| 10 | Multi-agent debugging | multi-agent-observability — trace hierarchy, span-level failure diagnosis |
| 11 | Agent role design patterns | crewai-production-guide — role+backstory patterns, per-agent model selection |
| 12 | Environmental impact data | ai-environmental-impact — 30 models benchmarked, energy/carbon/water per query |
| 13 | Sustainable AI practices | ai-environmental-impact — eco-efficiency rankings, batching strategies, Jevons Paradox |
| 14 | Multi-agent memory conflict | shared-agent-memory — implicit resolution via recency; explicit conflict confirmed as open problem |
| 15 | CRDTs / shared state | shared-agent-memory — shared solution store pattern (store + write hook + retrieval + threshold) |
| 16 | Agent consensus mechanisms | shared-agent-memory — implicit via similarity threshold; explicit consensus unsolved |
Partially Addressed (2 🟡)#
| # | Gap | Status |
|---|---|---|
| 8 | Memory debugging tools | Covered by multi-agent-observability (span-level tracing) but no memory-specific debugging source |
| 20 | Memory debugging tools | Same as #8 |
Open (5 ⬜)#
| # | Gap | Category | Next Action |
|---|---|---|---|
| 3 | Team knowledge management agents | Non-Code | Research: sources on AI agents for team wikis, shared knowledge bases |
| 4 | Knowledge quality eval metrics | Eval | Research/Create: metrics for cross-reference accuracy, entity extraction completeness, freshness |
| 17 | Content creation workflow (analysis → blog) | Wiki Pattern | Create: define workflow for turning wiki analyses into publishable content |
| 18 | AI-assisted writing/editing for prose | Non-Code | Research: sources on using agents for drafting, editing, refining articles |
| 19 | Wiki “publish” operation | Wiki Pattern | Create: add publish workflow to AGENTS.md alongside ingest/query/lint |
Remaining Gaps Cluster Into Two Groups#
Content Pipeline (#17, 18, 19): How to turn wiki knowledge into blog posts, articles, and teaching materials. This is the user’s stated 6-month goal. Addressing these would complete the wiki’s lifecycle from ingest → query → analyze → publish.
Knowledge Management (#3, 4): Team-level knowledge agents and quality evaluation. Lower priority but relevant to scaling the wiki pattern beyond solo use.
Wiki Status#
- 39 sources (up from 17 at start of Six Thinking Hats session)
- 20 concepts, 17 entities, 11 analyses
- 12 themes identified in cross-source-themes
- 14 key insights in key-insights-agentic-landscape