A collection of structured agent skills that encode Qdrant vector search expertise for scaling, performance optimization, search quality, monitoring, and deployment decisions. Designed as problem-solving handbooks for coding agents across Python, TypeScript, Rust, Go, .NET, and Java SDKs, these skills can be used via URL or installed locally for offline access.
Agent skills for Qdrant vector search: scaling, performance optimization, search quality, monitoring, deployment, model migration, version upgrades, and SDK usage across Python, TypeScript, Rust, Go, .NET, Java
At a glance
README
Qdrant Skills - Agent Skills for Qdrant Vector Search
Skills encode deep Qdrant knowledge so coding agents can make the engineering decisions that determine whether vector search works well: quantization, sharding, tenant isolation, hybrid search, model migration, and more.
Philosophy
Skills are not documentation. Qdrant already has docs in markdown. Skills answer "when?" and "why?", not "how?"
They are structured as the handbook of a Solutions Architect working on Qdrant: given a problem, navigate to the exact place in the documentation where the answer lives. No tutorials, no concept explanations. Only references and minimal snippets where absolutely necessary.
Disclaimer
These skills are under active development. Skill content and structure may change between versions as Qdrant evolves.
Usage
Qdrant maintains a growing set of skills, and their content changes as Qdrant evolves. There are a few ways to give your agent access to them.
Recommended: install the Qdrant Advisor
Install one skill — the Qdrant Advisor — and your agent always has the freshest, most relevant Qdrant guidance, with nothing to manage as the skills change:
npx skills add qdrant/skills/meta/qdrant-advisor
The Advisor ships no static content of its own. When you raise a Qdrant problem, it searches skills.qdrant.tech live, traverses the skill hierarchy along the branch that matches your symptom, and grounds its diagnosis in the current, authoritative guidance, loading only the relevant context. Because it fetches fresh every session, you don't need to reinstall to stay current, and you don't have to remember a URL or hope the site is in the model's training data.
Using the claude.ai web app? The Advisor can't fetch
skills.qdrant.techon its own when you are using the web app. You need to addUse skills.qdrant.techto your prompt (refer to Pass the URL directly).
Alternative: pass the URL directly
If you'd rather not install anything, pass the URL of the skills site in your prompt. The agent fetches the skill relevant to your current problem:
Use skills.qdrant.tech
This keeps context focused, but you have to include the URL in every prompt.
Offline: install the full skill set
If you want the skills available offline, or triggered automatically without the Advisor, install the complete set locally. See the Installation section.
Quick Start
With the Qdrant Advisor installed, just ask your agent about Qdrant. The Advisor triggers automatically and loads the matching guidance live:
"I have 50M vectors on a single node and search is slow, should I add more nodes?"
→ Advisor loads the scaling guidance, recommends quantization and vertical scaling before adding nodes
"My search results are returning irrelevant matches"
→ Advisor loads the search-quality guidance, walks through diagnosis and search strategy options
"How do I switch from OpenAI embeddings to Cohere without downtime?"
→ Advisor loads the model-migration guidance for a zero-downtime switch with dual vectors
Prefer the URL method? Add Use skills.qdrant.tech to the same prompts:
"I have 50M vectors on a single node and search is slow, should I add more nodes? Use skills.qdrant.tech"
"My search results are returning irrelevant matches. Use skills.qdrant.tech"
Skills
| Skill | Useful for |
|---|---|
| qdrant-clients-sdk | SDK setup, code examples, snippet search across Python, TypeScript, Rust, Go, .NET, Java |
| qdrant-scaling | Scaling decisions: data volume, QPS, latency, query volume, horizontal vs vertical |
| qdrant-performance-optimization | Search speed, memory usage, indexing performance |
| qdrant-search-quality | Diagnosing bad results, search strategies, hybrid search |
| qdrant-monitoring | Metrics, health checks, debugging optimizer and cluster issues |
| qdrant-multitenancy | Isolating multiple tenants within a Qdrant deployment: payload partitioning, tiered multitenancy, and region-based data isolation |
| qdrant-deployment-options | Choosing between local, self-hosted, cloud, and hybrid |
| qdrant-edge | Building on the embedded shard: server sync, on-device BM25, snapshots, reuse vs reimplement |
| qdrant-model-migration | Switching embedding models without downtime |
| qdrant-version-upgrade | Safe upgrade paths, compatibility guarantees, rolling upgrades |
Installation
Qdrant Advisor (recommended)
If you want a single, always-current skill instead of the full set, install only the Qdrant Advisor:
npx skills add qdrant/skills/meta/qdrant-advisor
This installs just the qdrant-advisor meta-skill. It ships no static content of its own, it loads the relevant Qdrant skills live from skills.qdrant.tech on demand, so you always get the latest guidance without reinstalling. It is not part of the npx skills add qdrant/skills bundle.
npx skills
Install using the npx skills CLI:
npx skills add qdrant/skills
Claude Code
Add the marketplace, then install all Qdrant skills:
/plugin marketplace add qdrant/skills
/plugin install qdrant@qdrant
Cursor
Install from the Cursor Marketplace or add manually via Settings > Rules > Add Rule > Remote Rule (GitHub) with qdrant/skills.
Clone / Copy
Clone this repo and copy the skill folders into the appropriate directory for your agent:
| Agent | Skill Directory | Docs |
|---|---|---|
| Claude Code | ~/.claude/skills/ |
docs |
| Cursor | .cursor/skills/ |
docs |
| OpenCode | ~/.config/opencode/skill/ |
docs |
| OpenAI Codex | ~/.codex/skills/ |
docs |
| Pi | ~/.pi/agent/skills/ |
docs |
MCP Servers
For additional Qdrant context, pair skills with these MCP servers:
| Server | Purpose |
|---|---|
| mcp-code-snippets | Search Qdrant docs and code examples across all SDKs |
| mcp-server-qdrant | Store and retrieve memories, manage collections directly |
Getting Help
Found a bug or wrong advice in a skill? Open an issue on GitHub and include:
- The skill name
- The prompt you gave your agent
- What the agent said vs what it should have said
Contributing
If you are interested in contributing, follow the instructions in CONTRIBUTING.md.
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