skills
Agent skills for Qdrant vector search, including scaling, performance optimization, and model migration.
GraphCanon updated 2w · GitHub synced 2w
Decision brief
Skills for Qdrant vector search provide tools for scaling, performance tuning, model migration, and more.
Good fit when
- Need help with optimizing or expanding your Qdrant deployment beyond millions of vectors
- Experience subpar search quality and seek targeted advice on improving relevance
Avoid when
- Your Qdrant instance is performing well with fewer than a million vectors
- Looking for help beyond vector search, such as database type selection or general AI agent tasks
Observed Jul 16, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of 2w
- Provenance
- Not a fork · Organization account
- As of 2w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Backing
Company context for Qdrant. Display-only - separate from trust and ranking.
- Company
- Qdrant·GitHub org profile·1mo
- Funding
- $28,000,000 (2024-01)·GraphCanon curated seed (public press)·1mo
- Commercial model
- Open core·GraphCanon curated seed·1mo
Install
git clone https://github.com/qdrant/skillsSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
This repository provides agent skills to assist in various operations related to the Qdrant vector search engine such as deployment, performance tuning, upgrading models, handling multitenancy, and SDK usage.
Capability facts
- Languages
- shell
Source: github.language · Aug 6, 2026
Categories
Graph entities
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 6, 2026)
npx skills add qdrant/skills/meta/qdrant-advisorSource link
Tags
README
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).
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"
For agents
This page has a .md twin and JSON over the API.