by bodepudimuneendra-netizen · Agent Tool · ★ 54
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/bodepudimuneendra-netizen/ConsciousDB.git
Taken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
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 | 54 |
| Forks | 3 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 64/100 |
| Last Updated | 2026-11-02 |
| Created | 2026-09-23 |
| Platforms | python |
| Est. Tokens | ~13k |
ConsciousDB ConsciousDB is a graph-database-agnostic Agentic GraphRAG framework — a production-ready intelligence layer you drop on top of your existing graph database to make it fully agentic. It doesn't replace your graph DB; it gives it a brain. Instead of hard-wiring GraphRAG logic to a single database, this framework completely decouples the AI decision layer from the storage layer.
These tools work well together with ConsciousDB for enhanced workflows:
Looking for a ConsciousDB alternative? If you're comparing ConsciousDB with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
High-throughput synthetic and pretraining dataset sifter for TypeSafe Jev. Rust streaming core, Parquet and JS
The pipe layer of an AI nervous system — one interface connecting provider neurons to your application, across
A community directory of projects built on Jev, TypeSafe AI's System One model.
GraphRAG, RAG, LlamaIndex, LangChain, 15 Prop Graph, 4 RDF, 10 Vector, 3 Search DBs. 14 data srcs, auto sync,
System 1 decision models (Jev, Laya, Cua-S1) as brain for agents: Browser use, computer use, games and robotic
Rust CLI powered by Jev from TypeSafe.ai that ranks agent skills for the next step using live session context.
Explore other popular agent 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: