Browse Skills — Page 235

python-testing

affaan-m/ECC

Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.

python-testing-patterns

benjaminasterA/antigravity-awesome-skills

Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.

python-testing-patterns

wshobson/agents

Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.

python-testing-patterns-v2

diegosouzapw/awesome-omni-skills

Python Testing Patterns workflow skill. Use this skill when the user needs Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

python-testing-patterns-v3

diegosouzapw/awesome-omni-skills

Python Testing Patterns workflow skill. Use this skill when the user needs Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

python-type-safety

wshobson/agents

Python type safety with type hints, generics, protocols, and strict type checking. Use when adding type annotations, implementing generic classes, defining structural interfaces, or configuring mypy/pyright.

python-type-system

TheBushidoCollective/han

Use when Python's type system including type hints, mypy, Protocol, TypedDict, and Generics. Use when working with Python type annotations.

python-web-debug

wgpsec/AboutSecurity

Python Web 框架 Debug 模式利用。当目标是 Flask/Django/FastAPI/Tornado 应用且开启了 Debug 模式时使用。当看到 Werkzeug Debugger 页面（交互式 Python console）、Django 黄色调试页面（Settings/Traceback）、FastAPI 自动文档(/docs /redoc)、或错误页面泄露了 Python 堆栈跟踪和源码路径时使用。Werkzeug debugger PIN 计算是 CTF 和实战中的经典考点——通过读取 /etc/machine-id 和 MAC 地址即可算出 PIN 码获取 RCE。任何 Python Web 应用的错误页面、/console 路径、或泄露了 Flask/Django/Werkzeug 版本信息时都应使用此 skill

python-workspace

terrylica/cc-skills

Python workspace for MQL5 integration. TRIGGERS - MetaTrader 5 Python, mt5 package, MQL5-Python setup.

pytorch

TerminalSkills/skills

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pytorch-fsdp

NousResearch/hermes-agent

Expert guidance for Fully Sharded Data Parallel training with PyTorch FSDP - parameter sharding, mixed precision, CPU offloading, FSDP2

pytorch-fsdp2

Orchestra-Research/AI-Research-SKILLs

Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with DeviceMesh.

pytorch-lightning

NousResearch/hermes-agent

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

pytorch-patterns

affaan-m/ECC

PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.

pyvene-interventions

Orchestra-Research/AI-Research-SKILLs

Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching, interchange intervention training, or testing causal hypotheses about model behavior.

pywencai

lzwme/finance-quant-skills

同花顺问财数据查询：使用中文自然语言查询A股、指数、基金、港美股、可转债等市场数据；当用户需要通过自然语言从问财获取选股、财务、资金流、技术指标等数据时使用。

pyzotero

K-Dense-AI/scientific-agent-skills

Interact with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.

q-and-a-prep-partner

aipoch/medical-research-skills

Predict challenging questions for presentations and prepare structured responses.

qa

SethGammon/Citadel

>-

qa

browser-use/browser-use

QA-test a website or web app and return a 1-5 quality score (5 = flawless, 1 = broken) with evidence. Use when the user wants to test, QA, evaluate, score, or "check how good" a site, page, flow, or app — including a local dev server (e.g. "qa test localhost:5173", "does the checkout work?", "rate this landing page"). Drives a real Browser Use cloud browser, tunneling localhost automatically.

qa-acceptance

microsoft/amplifier-app-paperclip

Produce QA acceptance criteria and a manual validation plan for a feature change — golden path, edge cases, error states, performance limits, and explicit pass/fail evidence.

qa-browser-automation

borghei/Claude-Skills

>

qa-execution

compozy/agh

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qa-expert

daymade/claude-code-skills

This skill should be used when establishing comprehensive QA testing processes for any software project. Use when creating test strategies, writing test cases following Google Testing Standards, executing test plans, tracking bugs with P0-P4 classification, calculating quality metrics, or generating progress reports. Includes autonomous execution capability via master prompts and complete documentation templates for third-party QA team handoffs. Implements OWASP security testing and achieves 90% coverage targets.

qa-loop-ui

Fr-e-d/GAAI-framework

Presents up to 5 questions from smart-question-generator one at a time, records answers, handles per-question skip and skip-all, captures per-question response time and total session duration. Renders a streaming progress header with question count and time estimate. Used as the interaction layer of Stage 4 of the /gaai:bootstrap pipeline.

qa-phase

popup-studio-ai/bkit-claude-code

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qa-plan

striderZA/OpenCodeGameStudios

Generate a QA test plan for a sprint or feature. Reads GDDs and story files, classifies stories by test type (Logic/Integration/Visual/UI), and produces a structured test plan covering automated tests required, manual test cases, smoke test scope, and playtest sign-off requirements. Run before sprint begins or when starting a major feature.

qa-report

compozy/agh

>-

qa-review

Fr-e-d/GAAI-framework

Validate that implemented code fully satisfies Story acceptance criteria, respects rules, and introduces no regressions. This is the hard quality gate — no pass means no delivery. Activate after implementation is complete.

qa-session

softspark/ai-toolkit

Interactive QA: user reports bugs conversationally, agent files GitHub issues. Triggers: QA session, report bug, file issue, conversational QA, bug intake.

qa-testing

rampstackco/claude-skills

Run QA testing on a page, feature, or full site at one of three depth tiers (smoke, standard, full). Use this skill whenever the user asks to test a page, audit a site, check for bugs, verify a deploy, run a QA sweep, or review accessibility, performance, or SEO basics. Triggers on test, QA, audit, verify, check, is it working, does it look right, broken, 404, image not loading, post-deploy check, regression test. Also triggers proactively after any significant code change or new page launch where verification matters.

qbr-builder

t0ddc3by/claude-for-customer-success

>

qbr-deck

mohitagw15856/pm-claude-skills

Build a Quarterly Business Review (QBR) deck structure and narrative for a customer account. Use when asked to prepare a QBR, business review meeting, executive review, or quarterly check-in with a customer. Produces a slide-by-slide QBR structure with talking points, metrics review, value narrative, and mutual next steps.

qbr-plan

indranilbanerjee/digital-marketing-pro

Prepare a Quarterly Business Review. Use when: building QBR presentations, client performance reviews, or strategy updates.

qbr-preparation

guia-matthieu/clawfu-skills

Automate QBR preparation with account summaries, success metrics, challenges, and strategic recommendations

qbr-report

langchain-ai/lca-deepagents

Generate a Quarterly Business Review (QBR) report for the DVD rental business, covering revenue and rental volume with breakdowns by film language, category (genre), and actor. Use whenever someone asks for a QBR, a quarterly report, or a quarterly business review.

qdrant

giuseppe-trisciuoglio/developer-kit

Provides Qdrant vector database integration patterns with LangChain4j. Handles embedding storage, similarity search, and vector management for Java applications. Use when implementing vector-based retrieval for RAG systems, semantic search, or recommendation engines.

qdrant-advisor

qdrant/skills

Diagnose, troubleshoot, and advise on any Qdrant deployment by loading the latest official Qdrant skills live from skills.qdrant.tech. Use this whenever someone raises a Qdrant problem or question — slow or degraded search, high or growing memory / OOM crashes, optimizer stuck or slow, indexing slowness, scaling and sharding decisions (node count, QPS, latency, multitenancy, vertical vs horizontal), poor or irrelevant search results, hybrid search and reranking, embedding-model migration, version upgrades and compatibility, monitoring and observability (Prometheus, Grafana, health checks, /metrics, /telemetry), deployment choices (local, Docker, self-hosted, Qdrant Cloud, embedded), or client-SDK questions (Python, TypeScript, Rust, Go, .NET, Java). Trigger especially when the context is clearly a Qdrant cluster, collection, or vector-search deployment. Always prefer this skill over answering from memory: it pulls current, authoritative guidance and only the relevant context.

qdrant-clients-sdk

github/awesome-copilot

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

qdrant-clients-sdk

qdrant/skills

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

qdrant-deployment-options

github/awesome-copilot

Guides Qdrant deployment selection. Use when someone asks 'how to deploy Qdrant', 'Docker vs Cloud', 'local mode', 'embedded Qdrant', 'Qdrant EDGE', 'which deployment option', 'self-hosted vs cloud', or 'need lowest latency deployment'. Also use when choosing between deployment types for a new project.

qdrant-deployment-options

qdrant/skills

Guides Qdrant deployment selection. Use when someone asks 'how to deploy Qdrant', 'Docker vs Cloud', 'local mode', 'embedded Qdrant', 'Qdrant EDGE', 'which deployment option', 'self-hosted vs cloud', or 'need lowest latency deployment'. Also use when choosing between deployment types for a new project.

qdrant-edge

qdrant/skills

Guides building on Qdrant Edge, the embedded in-process shard. Use when someone asks 'how to sync Edge with the server', 'keep a local shard in sync with Qdrant Cloud', 'BM25 or keyword search on Edge', 'hybrid search on Edge', 'embeddings on device', 'Edge snapshots', 'apply a partial snapshot', 'why is my Edge search empty after inserts', or is writing custom sync, BM25, or fusion code against qdrant-edge. Also use when deciding what Edge ships built-in versus what you must implement.

qdrant-horizontal-scaling

github/awesome-copilot

Diagnoses and guides Qdrant horizontal scaling decisions. Use when someone asks 'vertical or horizontal?', 'how many nodes?', 'how many shards?', 'how to add nodes', 'resharding', 'data doesn't fit', or 'need more capacity'. Also use when data growth outpaces current deployment.

qdrant-horizontal-scaling

qdrant/skills

Diagnoses and guides Qdrant horizontal scaling decisions. Use when someone asks 'vertical or horizontal?', 'how many nodes?', 'how many shards?', 'how to add nodes', 'resharding', 'data doesn't fit', or 'need more capacity'. Also use when data growth outpaces current deployment.

qdrant-hybrid-search

qdrant/skills

Explains hybrid search in Qdrant. Use when someone asks 'how do I setup hybrid search?', 'how to combine keyword and semantic search?', 'sparse plus dense vectors?', 'missing keyword matches', 'how to combine results from multiple searches?' and 'combining multiple representations'

qdrant-hybrid-search-combining

qdrant/skills

Fusing scores from multiple searches into a single ranked result (RRF, DBSF, custom fusion). Use when someone asks 'RRF or DBSF?', 'how to combine sparse and dense', 'how to combine scores from multiple searches?', 'custom fusion', or 'fusion is not producing good results'

qdrant-hybrid-search-prefetches

qdrant/skills

Constructing prefetch queries for hybrid retrieval, including sparse/dense and multi-field setups, and choosing a sparse embedding model. Use when someone asks 'dense and sparse in one search?', 'how to combine multiple fields for retrieval?', 'payloads or sparse vectors for lexical?', 'which sparse embedding model to use?', or 'BM25 vs SPLADE?'

qdrant-indexing-performance-optimization

github/awesome-copilot

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.

qdrant-indexing-performance-optimization

qdrant/skills

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.

qdrant-memory-usage-optimization

github/awesome-copilot

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.

qdrant-memory-usage-optimization

qdrant/skills

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.

qdrant-minimize-latency

github/awesome-copilot

Guides Qdrant query latency optimization. Use when someone asks 'search is slow', 'how to reduce latency', 'p99 is too high', 'tail latency', 'single query too slow', 'how to make search faster', or 'latency spikes'.

qdrant-minimize-latency

qdrant/skills

Guides Qdrant query latency optimization. Use when someone asks 'search is slow', 'how to reduce latency', 'p99 is too high', 'tail latency', 'single query too slow', 'how to make search faster', or 'latency spikes'.

qdrant-model-migration

github/awesome-copilot

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-model-migration

qdrant/skills

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-monitoring

github/awesome-copilot

Guides Qdrant monitoring and observability setup. Use when someone asks 'how to monitor Qdrant', 'what metrics to track', 'is Qdrant healthy', 'optimizer stuck', 'why is memory growing', 'requests are slow', or needs to set up Prometheus, Grafana, or health checks. Also use when debugging production issues that require metric analysis.

qdrant-monitoring

qdrant/skills

Guides Qdrant monitoring and observability setup. Use when someone asks 'how to monitor Qdrant', 'what metrics to track', 'is Qdrant healthy', 'optimizer stuck', 'why is memory growing', 'requests are slow', or needs to set up Prometheus, Grafana, or health checks. Also use when debugging production issues that require metric analysis.

qdrant-monitoring-debugging

github/awesome-copilot

Diagnoses Qdrant production issues using metrics and observability tools. Use when someone reports 'optimizer stuck', 'indexing too slow', 'memory too high', 'OOM crash', 'queries are slow', 'latency spike', or 'search was fast now it's slow'. Also use when performance degrades without obvious config changes.

qdrant-monitoring-debugging

qdrant/skills

Diagnoses Qdrant production issues using metrics and observability tools. Use when someone reports 'optimizer stuck', 'indexing too slow', 'memory too high', 'OOM crash', 'queries are slow', 'latency spike', or 'search was fast now it's slow'. Also use when performance degrades without obvious config changes.

qdrant-monitoring-setup

github/awesome-copilot

Guides Qdrant monitoring setup including Prometheus scraping, health probes, Hybrid Cloud metrics, alerting, and log centralization. Use when someone asks 'how to set up monitoring', 'Prometheus config', 'Grafana dashboard', 'health check endpoints', 'how to scrape Hybrid Cloud', 'what alerts to set', 'how to centralize logs', or 'audit logging'.

qdrant-monitoring-setup

qdrant/skills

Guides Qdrant monitoring setup including Prometheus scraping, health probes, Hybrid Cloud metrics, alerting, and log centralization. Use when someone asks 'how to set up monitoring', 'Prometheus config', 'Grafana dashboard', 'health check endpoints', 'how to scrape Hybrid Cloud', 'what alerts to set', 'how to centralize logs', or 'audit logging'.

qdrant-multitenancy

qdrant/skills

Guides tenant isolation architecture in Qdrant for multi-tenant or multi-user applications. Use when someone asks 'how to isolate customer data', 'how to build multi-tenant search/RAG', 'how many collections should I create', 'how to partition tenants by payload', 'a customer's data legally has to stay in a certain country or region'. Also use when they describe a symptom: one customer's data is way bigger than the rest and slowing everyone down, or one tenant is hogging resources.

qdrant-performance-optimization

github/awesome-copilot

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.

qdrant-performance-optimization

qdrant/skills

Navigation hub linking sub-skills for proactive Qdrant tuning: search speed, indexing performance, and memory usage optimization. Use when planning configuration or capacity changes to improve speed and efficiency. For diagnosing an active production slowdown or analyzing live metrics, use qdrant-monitoring instead.

qdrant-relevance-feedback

qdrant/skills

Expanding the candidate pool via relevance feedback, as an alternative to reranking when a dense retriever is too weak. Use when someone asks about 'Qdrant's Relevance Feedback API', 'improving dense search relevance/recall', 'how to discover/get more relevant results from vector search', 'cheaper/better alternative to reranking', 'using a more heavy/big embedding model for dense search but can't afford it', 'finding more relevant documents beyond the initial search pool', or 'feedback loops'. Also trigger when the user has a search quality problem due to a dense retriever being weak and is considering reranking as a solution — this API may be a better fit

qdrant-scaling

github/awesome-copilot

Guides Qdrant scaling decisions. Use when someone asks 'how many nodes do I need', 'data doesn't fit on one node', 'need more throughput', 'cluster is slow', 'too many tenants', 'vertical or horizontal', 'how to shard', or 'need to add capacity'.

qdrant-scaling

qdrant/skills

Guides Qdrant scaling decisions. Use when someone asks 'how many nodes do I need', 'data doesn't fit on one node', 'need more throughput', 'cluster is slow', 'too many tenants', 'vertical or horizontal', 'how to shard', or 'need to add capacity'.

qdrant-scaling-data-volume

github/awesome-copilot

Guides Qdrant data volume scaling decisions. Use when someone asks 'data doesn't fit on one node', 'too much data', 'need more storage', 'vertical or horizontal scaling', 'tenant scaling', 'time window rotation', or 'data growth exceeds capacity'.

qdrant-scaling-data-volume

qdrant/skills

Guides Qdrant data volume scaling decisions. Use when someone asks 'data doesn't fit on one node', 'too much data', 'need more storage', 'vertical or horizontal scaling', 'tenant scaling', 'time window rotation', or 'data growth exceeds capacity'.

qdrant-scaling-qps

github/awesome-copilot

Guides Qdrant query throughput (QPS) scaling. Use when someone asks 'how to increase QPS', 'need more throughput', 'queries per second too low', 'batch search', 'read replicas', or 'how to handle more concurrent queries'.

qdrant-scaling-qps

qdrant/skills

Guides Qdrant query throughput (QPS) scaling. Use when someone asks 'how to increase QPS', 'need more throughput', 'queries per second too low', 'batch search', 'read replicas', or 'how to handle more concurrent queries'.

qdrant-scaling-query-volume

github/awesome-copilot

Guides Qdrant query volume scaling. Use when someone asks 'query returns too many results', 'scroll performance', 'large limit values', 'paginating search results', 'fetching many vectors', or 'high cardinality results'.

qdrant-scaling-query-volume

qdrant/skills

Guides Qdrant query volume scaling. Use when someone asks 'query returns too many results', 'scroll performance', 'large limit values', 'paginating search results', 'fetching many vectors', or 'high cardinality results'.

qdrant-search-quality

github/awesome-copilot

Diagnoses and improves Qdrant search relevance. Use when someone reports 'search results are bad', 'wrong results', 'low precision', 'low recall', 'irrelevant matches', 'missing expected results', or asks 'how to improve search quality?', 'which embedding model?', 'should I use hybrid search?', 'should I use reranking?'. Also use when search quality degrades after quantization, model change, or data growth.

qdrant-search-quality

qdrant/skills

Diagnoses and improves Qdrant search relevance. Use when someone reports 'search results are bad', 'wrong results', 'low precision', 'low recall', 'irrelevant matches', 'missing expected results', or asks 'how to improve search quality?', 'which embedding model?', 'should I use hybrid search?', 'should I use reranking?', 'how to measure retrieval quality?', 'build a golden set', 'ground truth dataset', or 'how to score recall@k?'. Also use when search quality degrades after quantization, model change, or data growth.

qdrant-search-quality-diagnosis

github/awesome-copilot

Diagnoses Qdrant search quality issues. Use when someone reports 'results are bad', 'wrong results', 'not relevant results', 'missing matches', 'recall is low', 'approximate search worse than exact', 'which embedding model', or 'quality dropped after quantization'. Also use when search quality degrades without obvious changes.

qdrant-search-quality-diagnosis

qdrant/skills

Diagnoses Qdrant search quality issues. Use when someone reports 'results are bad', 'wrong results', 'not relevant results', 'missing matches', 'recall is low', 'approximate search worse than exact', 'which embedding model', 'quality dropped after quantization', 'how to measure retrieval quality', 'build a golden set', 'ground truth dataset', or 'how to score recall@k'. Also use when search quality degrades without obvious changes.

qdrant-search-speed-optimization

github/awesome-copilot

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.

qdrant-search-speed-optimization

qdrant/skills

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.

qdrant-search-strategies

github/awesome-copilot

Guides Qdrant search strategy selection. Use when someone asks 'should I use hybrid search?', 'BM25 or sparse vectors?', 'how to rerank?', 'results are not relevant', 'I don't get needed results from my dataset but they're there', 'retrieval quality is not good enough', 'results too similar', 'need diversity', 'MMR', 'relevance feedback', 'recommendation API', 'discovery API', 'ColBERT reranking', or 'missing keyword matches'

qdrant-search-strategies

qdrant/skills

Guides Qdrant search strategy selection. Use when someone asks 'should I use hybrid search?', 'how to rerank?', 'results are not relevant', 'I don't get needed results from my dataset but they're there', 'retrieval quality is not good enough', 'results too similar', 'need diversity', 'MMR', 'relevance feedback', 'recommendation API', 'discovery API', or 'missing keyword matches'

qdrant-sliding-time-window

github/awesome-copilot

Guides sliding time window scaling in Qdrant. Use when someone asks 'only recent data matters', 'how to expire old vectors', 'time-based data rotation', 'delete old data efficiently', 'social media feed search', 'news search', 'log search with retention', or 'how to keep only last N months of data'.

qdrant-sliding-time-window

qdrant/skills

Guides sliding time window scaling in Qdrant. Use when someone asks 'only recent data matters', 'how to expire old vectors', 'time-based data rotation', 'delete old data efficiently', 'social media feed search', 'news search', 'log search with retention', or 'how to keep only last N months of data'.

qdrant-tenant-scaling

github/awesome-copilot

Guides Qdrant multi-tenant scaling. Use when someone asks 'how to scale tenants', 'one collection per tenant?', 'tenant isolation', 'dedicated shards', or reports tenant performance issues. Also use when multi-tenant workloads outgrow shared infrastructure.

qdrant-tenant-scaling

qdrant/skills

Guides Qdrant multi-tenant scaling. Use when someone asks 'how to scale tenants', 'one collection per tenant?', 'tenant isolation', 'dedicated shards', or reports tenant performance issues. Also use when multi-tenant workloads outgrow shared infrastructure.

qdrant-vector-search

NousResearch/hermes-agent

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

qdrant-version-upgrade

github/awesome-copilot

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

qdrant-version-upgrade

qdrant/skills

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

qdrant-vertical-scaling

github/awesome-copilot

Guides Qdrant vertical scaling decisions. Use when someone asks 'how to scale up a node', 'need more RAM', 'upgrade node size', 'vertical scaling', 'resize cluster', 'scale up vs scale out', or when memory/CPU is insufficient on current nodes. Also use when someone wants to avoid the complexity of horizontal scaling.

qdrant-vertical-scaling

qdrant/skills

Guides Qdrant vertical scaling decisions. Use when someone asks 'how to scale up a node', 'need more RAM', 'upgrade node size', 'vertical scaling', 'resize cluster', 'scale up vs scale out', or when memory/CPU is insufficient on current nodes. Also use when someone wants to avoid the complexity of horizontal scaling.

qiita

vm0-ai/vm0-skills

Qiita API for Japanese tech articles. Use when user mentions "Qiita",

qinglong

uvwt/agentdock

Operate a QingLong panel through its official open API. Use for QingLong health checks, env variables, cron tasks, task logs, and controlled panel API calls from AgentDock Skill.

qiskit

K-Dense-AI/scientific-agent-skills

IBM quantum computing framework. Use when targeting IBM Quantum hardware, working with Qiskit Runtime for production workloads, or needing IBM optimization tools. Best for IBM hardware execution, quantum error mitigation, and enterprise quantum computing. For Google hardware use cirq; for gradient-based quantum ML use pennylane; for open quantum system simulations use qutip.

qiskit-v2

diegosouzapw/awesome-omni-skills

Qiskit workflow skill. Use this skill when the user needs Qiskit is the world's most popular open-source quantum computing framework with 13M+ downloads. Build quantum circuits, optimize for hardware, execute on simulators or real quantum computers, and analyze results. Supports IBM Quantum (100+ qubit systems), IonQ, Amazon Braket, and other providers and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

qmd

NousResearch/hermes-agent

Search personal knowledge bases, notes, docs, and meeting transcripts locally using qmd — a hybrid retrieval engine with BM25, vector search, and LLM reranking. Supports CLI and MCP integration.

qmd-extended

aAAaqwq/AGI-Super-Team

Extended QMD knowledge base with multi-backend embedding (Google AI Studio / Ollama / local). Use when managing QMD embeddings, switching backends, testing embedding quality, re-indexing, or troubleshooting QMD vector search. Triggers on "qmd embed", "embedding backend", "切换embedding", "embedding测试", "re-embed", "知识库embedding", "qmd扩展". For general QMD queries and knowledge retrieval, use memory-router skill instead.

qmd-knowledge

jellydn/my-ai-tools

Project-specific knowledge management system using qmd MCP server. Captures learnings, issue notes, and conventions in a searchable knowledge base.

qms-audit-expert

alirezarezvani/claude-skills

Use for ISO 13485 internal audits: planning the program, running an audit, classifying findings or preparing for an external audit. Optimizes the schedule with audit_schedule_optimizer.py.

qmt-docs

lzwme/finance-quant-skills

QMT（迅投极速策略交易系统）Python 策略开发完整指南。涵盖策略编写、回测、实盘交易、API参考和代码示例。当用户需要开发 QMT 量化策略、查询 QMT API、从聚宽迁移至 QMT、编写实盘交易程序，或提及 QMT、迅投策略、QMT 回测时使用。