Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/laramohan/wikillmTaken from the project's README on GitHub. Check the security audit before running it.
Flagged: sudo usage, opens a tunnel service. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 56 |
| Forks | 4 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 52/100 |
| Last Updated | 2026-02-08 |
| Created | 2024-02-03 |
| Platforms | python |
| Est. Tokens | ~14k |
LLMs as Collaboratively Edited Knowledge Bases 🐦 Twitter WikiLLM Algorithms like MEMIT enable us to inject facts into an LLM by editing its parameters 💉🧠. Could we use fact editing to crowdsource a continually updated neural knowledge base—with no RAG or external documents? WikiLLM uses fact editing to transform the static piles of floats that are current LLMs into dynamically evolving...
Looking for a wikillm alternative? If you're comparing wikillm with other ai tool tools, these 3 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Skip to content github / docs Code Issues 80 Pull requests 35 Discussions Actions Projects 2 Security Insights
Skill to talk to Claude about your projects over the phone
.NET MAUI skills for GitHub Copilot and Claude Code
Explore other popular ai tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: