devrel-projects

Search and store knowledge locally using Qdrant Edge. No server needed.

Guides developers through building community Qdrant skills that embed domain knowledge into Claude. Use when someone wants to "create a community qdrant skill", "build an external skill for qdrant", "make a qdrant skill for the community", "build a public qdrant skill", or asks how to "create a skill for qdrant memory issues for developers". Also trigger when someone says "I want to build an open source qdrant skill" or "help me create a qdrant skill for public use". Do NOT use for internal SA skills, general non-Qdrant skill creation, or Python project skills unrelated to Qdrant.

Diagnoses when and why to recommend specific cost optimization techniques for Qdrant customers. Use when a customer or SA says "too expensive", "need to reduce cost", "pricing too high", "how to lower price", "sticker shock", or asks about scaling costs. Also trigger when a deal is blocked by pricing, a customer compares competitor pricing, a startup says the quote is too high, or someone needs a formula to predict costs at scale. This skill answers "when should I recommend scalar vs binary quantization?" not "how to configure quantization." Do NOT use for general Qdrant setup, feature requests, or implementation how-tos.

Handles technical objections that block Qdrant deals and provides proven response playbooks. Use when a deal is stalled due to pricing concerns, missing features, performance issues, or competitive pressure. Triggers on "deal blocked", "customer concerned about cost", "proposal too expensive", "missing feature blocking production", "latency issues on call", "why not use pinecone", "customer built workaround", or "champion lost budget battle". Do NOT use for general product questions, documentation lookups, or technical implementation.

Guides Qdrant SAs through building internal skills that embed domain knowledge into Claude. Use when someone wants to "create a qdrant skill", "build a skill for qdrant diagnostics", "make an internal skill for qdrant customers", "create a qdrant troubleshooting skill", or asks how to "turn SA knowledge into a skill". Also trigger when someone says "help me build a skill for qdrant deal objections" or "I want to create a skill for qdrant cluster sizing". Do NOT use for general skill creation unrelated to Qdrant, external community skills, or Python/JS project skills.

Diagnoses and fixes Qdrant memory problems. Use when a developer reports OOM crashes, high RAM usage, HNSW consuming too much memory, latency spiking after switching storage, or needing to fit more vectors on existing hardware. Also trigger when someone asks which quantization to use, how to choose between mmap and RAM, how to estimate memory for scaling, or why their Qdrant node keeps dying. Do NOT use for initial Qdrant setup, API scripting, embedding model selection, search accuracy tuning, backups, or vector DB comparisons.

Edit and create content on the Qdrant website (Hugo static site). Code agent for page structure, content agent for writing.

Expert guidance for Qdrant vector database development. Use when working with vector search, embeddings, similarity search, Qdrant collections, points, payloads, filtering, Qdrant Cloud, clusters, API keys, or any Qdrant client library (Python, JavaScript/TypeScript, Rust, Go, Java, .NET/C#). Covers client setup, collection management, vector indexing, search operations, and cloud deployment.

Internal analytics skill for Qdrant.

Internal design skill for Qdrant.

Triage and respond to community questions about Qdrant. Use when someone asks a question on Discord, GitHub, Reddit, Stack Overflow, or any community channel. Classifies question type, routes to the right resource, and provides response templates.

Step-by-step guide for contributing to the qdrant/landing_page repo. Use when someone needs to add a blog post, article, documentation page, customer logo, or any content to qdrant.tech.

Internal developer relations skill for Qdrant.

Plan and create developer-focused content for Qdrant. Use when planning blog posts, tutorials, demos, conference talks, or social content. Covers content types, competitive positioning, channel strategy, and Qdrant-specific messaging.

Internal go-to-market skill for Qdrant.

Internal sales skill for Qdrant.

Internal solutions architecture skill for Qdrant.

Internal support skill for Qdrant.

Qdrant provides client SDKs for various programming languages, allowing easy integration with Qdrant deployments.

There are multiple ways to deploy Qdrant, this document navigates through different deployment options and provides guidance on how to choose the right one for your use case.

Guides embedding model migration in Qdrant without downtime. Use when someone asks 'how to switch embedding models', 'how to migrate vectors', 'how to update to a new model', 'zero-downtime model change', 'how to re-embed my data', or 'can I use two models at once'. Also use when upgrading model dimensions, switching providers, or A/B testing models.

Qdrant provides monitoring and observability tools available for both self-hosted and cloud deployments. This document provides an overview of monitoring options and best practices for monitoring Qdrant performance and health.

Diagnoses and fixes slow Qdrant indexing and data ingestion. Use when someone reports 'uploads are slow', 'indexing takes forever', 'optimizer is stuck', 'HNSW build time too long', or 'data uploaded but search is bad'. Also use when optimizer status shows errors, segments won't merge, or indexing threshold questions arise.

Diagnoses and reduces Qdrant memory usage. Use when someone reports 'memory too high', 'RAM keeps growing', 'node crashed', 'out of memory', 'memory leak', or asks 'why is memory usage so high?', 'how to reduce RAM?'. Also use when memory doesn't match calculations, quantization didn't help, or nodes crash during recovery.

Diagnoses and fixes slow Qdrant search. Use when someone reports 'search is slow', 'high latency', 'queries take too long', 'low QPS', 'throughput too low', 'filtered search is slow', or 'search was fast but now it's slow'. Also use when search performance degrades after config changes or data growth.

Different techniques to optimize the performance of Qdrant, including indexing strategies, query optimization, and hardware considerations. Use when you want to improve the speed and efficiency of your Qdrant deployment.

How to handle scaling of Qdrant, including horizontal and vertical scaling strategies, sharding, replication, and load balancing. Use when you want to scale your Qdrant deployment to handle increased load or larger datasets.

Guidance on how to improve the search quality in Qdrant, including tips on tuning parameters, and applying information retrieval best practices. Use when you want to enhance the relevance and accuracy of search results in your Qdrant deployment.

Guidance on how to upgrade your Qdrant version without interrupting the availability of your application and ensuring data integrity.