Source: ai-research/agentwikis-platform-overview-2026-06-12.md — scraped from agentwikis.com 2026-06-12
Agent Wikis (agentwikis.com) is a commercial service that builds and maintains structured knowledge bases using the Karpathy LLM-wiki pattern, then publishes them as free, agent-readable Markdown with llms.txt indexes. Built by a developer on the Hermes Agent team — the Hermes wiki is the service’s flagship and the research backbone for their YouTube video series. Agent Wikis is the first commercially-operated multi-wiki Karpathy implementation with published empirical accuracy benchmarks proving why compiled wikis outperform raw-source RAG.
Key Takeaways
- Compiled wiki vs raw-source RAG — same model, same retrieval, same token budget: compiled wiki hits 89% correct / 7% hallucination vs raw-source RAG’s 63% / 26%. Maintenance (curation) is the lever, not retrieval method.
- vs. web search — web search scores 48% / 48% on niche fast-moving domains; compiled wiki is reproducible where search varies ±10–14 points between runs. On synthesis/decision questions: web scored 0%, wiki held 100%.
- Karpathy attribution — explicitly credits Karpathy’s GitHub gist and
llm-wiki-template; README on each wiki is the standard Karpathy pattern (raw/ → wiki/ → CLAUDE.md schema). - Agent-native architecture — every wiki exposes
llms.txt,llms-full.txt,index.json, and an MCP server (calibrated search + section-level reads) — the exact configuration that scored 89% in their eval. - Multi-domain catalog — 15 live wikis across AI agents, inference/serving, image/video gen, DeFi, trading, and paid ads (2026-06-12).
- Routing beats either source — “wiki first, web on gaps” scored 93%, above either source alone.
The Benchmark in Full
27 tasks on Hermes Agent (releasing every 3–5 days), same model and token budget, blind LLM judge, replicated across two model families:
| Condition | Correct | Hallucination |
|---|---|---|
| Parametric (no context) | 4% | 85% |
| Web search | 48% | 48% |
| RAG over raw sources | 63% | 26% |
| RAG over compiled wiki | 89% | 7% |
| Whole curated pages (static) | 81% | 22% |
| Agent navigates wiki | 70% | 30% |
Cost: ~0.0054/query (~3x cheaper than web search), ~1.2s vs ~3.6s (~3x faster).
Wiki Catalog (2026-06-12)
AI Agents: Hermes (105 docs), Claude Code (33), Codex (36), Agent Workflows (15) Inference/Serving: llama.cpp (63), vLLM (19), LM Studio (23) Image/Video Gen: ComfyUI (31), HyperFrames (167), Remotion (31) DeFi: Hyperliquid (18), Solana (16) Trading: Trading (44), Stock Options (16) Ads: Google Ads (27), Meta Ads (25)
How It Differs from Other Karpathy-Pattern Implementations
| Implementation | Scale | Access | Benchmarks |
|---|---|---|---|
| Stride starter | Single vault, personal | Obsidian only | None |
| Synthadoc | Single vault, self-hosted | Obsidian + API | None |
| Matt Wolfe second brain | Single vault + CRM/journal | Codex | None |
| Agent Wikis | 15+ wikis, hosted service | Web + llms.txt + MCP | Published (89% vs 48%) |
The key distinction: Agent Wikis is the only implementation that (1) runs as a service maintaining many wikis simultaneously, (2) exposes an agent-native access path without requiring users to run their own LLM loop, and (3) has published a controlled eval proving the pattern’s accuracy advantage over web search.
Pricing
- Free — browse all public wikis, raw Markdown + llms.txt, no account required
- Sponsor — $50 one-time, you pick the topic, published as free public wiki
- Private — 20/mo, compiled from your private sources, delivered as private git repo
- Project — 100/mo, claim the public wiki for your product, includes eval report
Try It
- Browse a wiki: https://agentwikis.com/wiki/hermes
- Point an agent at
llms.txt:curl https://agentwikis.com/wiki/hermes/llms.txt - Read the eval methodology: https://agentwikis.com/why-wikis
- Sponsor a topic via the waitlist if a domain you work in isn’t covered yet
Related
- Stride Starter Vault — minimal template counterpart
- Synthadoc — Python engine counterpart
- Dream Labs Walkthrough — adoption tutorial
- Hermes Agent — the flagship Agent Wikis use case; see GAPA and Memory Providers
- The Agent-Readable Web — broader llms.txt + agent-native context
- Pipeline Diagram — how this vault’s own pipeline works