zer0dex
SkillDocs & knowledgeUse when you need a local dual-layer memory pattern for an AI agent, a compressed markdown index for cross-reference queries plus a local vector store queried before each model call, and want a reference implementation to seed and query without a hosted service. Local-first, Alpha.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the zer0dex skill
What this skill tells your AI
The instructions your AI receives, as published by hermes-labs-ai/zer0dex in .agents/skills/zer0dex/SKILL.md and read by ahel’s review.
zer0dex is a local dual-layer memory pattern for AI agents: a compact, human-readable markdown index paired with semantic retrieval from a local vector store, queried before each message. It targets cross-project recall where flat memory files or vector-only RAG fall short. Reference implementation, local-first, Alpha (0.1.x line).
Use it for
- Combining a compressed markdown memory index with vector retrieval in one local loop
- Running a local memory server an agent host queries before model calls
- Seeding and querying persistent memory without standing up a hosted service
- Prototyping the dual-layer (index + vector) pattern before adopting a heavier memory stack
Do not use it for
- A hosted or multi-tenant memory platform
- A governance or safety layer for memory content
- Proof that any benchmark result transfers unchanged to a different corpus or workload
Quickstart
pip install zer0dex
zer0dex check
Or without installing, via uv:
uvx zer0dex check
Real output from a working local setup (Ollama running, models pulled):
✅ Ollama is running at http://localhost:11434
✅ Model present: nomic-embed-text
✅ Model present: mistral:7b
✅ mem0ai is importable
✅ chromadb is importable
✅ Python Ollama client is importable
Commands
zer0dex check # validate prerequisites (Ollama, models, mem0ai, chromadb)
zer0dex init # initialize a new memory store
zer0dex seed --source <path> # seed from markdown files
zer0dex serve # start the local memory server
zer0dex query "<text>" # query memories
zer0dex status # check server health
Output shape
check: per-prerequisite pass/fail lines (Ollama reachability, model presence, library importability)serve/status: local HTTP health and query resultsquery: ranked memory matches from the vector store
Common gotchas
checkfails closed if Ollama isn't running locally or the required models (nomic-embed-text, an LLM tag) aren't pulled — read the specific failing line, it names the missing prerequisite.- This is a reference pattern, not a managed service: there is no built-in multi-user isolation or remote auth.
- 0.1.x is a developer-preview compatibility line; check
docs/compatibility.mdbefore pinning across upgrades.
More
Full docs, CLI/HTTP reference, and compatibility policy: https://github.com/hermes-labs-ai/zer0dex
Signals
- GitHub stars
- 62
- Forks
- 6
- Last commit
- Sep 2026
ahel review
K1binfo
installs-packages
Automated review, not a security audit. Ruleset v1+k2.
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zer0dex- Source
- github.com/hermes-labs-ai/zer0dex