No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by alfadur7 · Claude Skill · ★ 163
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is llm-wiki-newsroom safe to install? View the security audit →
LLM Wiki Newsroom A multi-agent AI knowledge base run by a five-role "newsroom" — open-source, local-first, no API keys, no vendor lock-in. Drop articles, documents, and PDFs into the folder, type a single command, and the newsroom — powered by an agent like Claude Code — reads them, extracts entities, concepts, and relationships, and organizes everything into a fully cross-referenced wiki, a structured and persistent alternative to RAG. Unlike most takes on the idea, the agent that writes a page is never the one that reviews it, and the authoring guidelines evolve themselves over time. Every new document you add also enriches the existing pages. This repo ships with a small example corpus — the debate over what "open source" means for AI — under , but the framework is domain-agnostic. Most knowledge tools leave the finding to you. This project makes the AI read and understand your collected documents first, then organizes them into a wiki — with cross-references between pages, automatic flagging of conflicting claims, and per-topic synthesis built in from the start, so later retrieval is fast.
| Stars | 163 |
| Forks | 27 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 65.5727916651446/100 |
| Last Updated | 2026-09-18 |
| Created | 2026-06-26 |
| Platforms | claude-code, python |
| Est. Tokens | ~25k |
These tools work well together with llm-wiki-newsroom for enhanced workflows:
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llm-wiki-newsroom is Harness engineering applied to knowledge production: a self-evolving multi-agent newsroom that turns your documents into a cross-linked markdown wiki. A "reground" loop pulls published pages back in b. It is categorized as a Claude Skill with 163 GitHub stars.
llm-wiki-newsroom is primarily written in Python. It covers topics such as agentic-ai, ai-agents, claude.
You can find installation instructions and usage details in the llm-wiki-newsroom GitHub repository at github.com/alfadur7/llm-wiki-newsroom. The project has 163 stars and 27 forks, indicating an active community.
llm-wiki-newsroom is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to llm-wiki-newsroom on Agent Skills Hub include swarmvault, ctx, agent-second-brain. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: