Results for “quaderno”

Guides optimization of Qdrant query latency by tuning segments, memory, quantization, and search parameters.

Guides scaling Qdrant query throughput (QPS) through performance tuning, horizontal scaling with read replicas, and disk I/O optimization.

Prose quality checker for Quarto (.qmd) files, grounded in William Zinsser's *On Writing Well* (30th Anniversary Edition). Checks for clutter, weak verbs, hollow qualifiers, clichés, inflated academic voice, poor leads and endings, pronoun and tense inconsistency, and unclear explanation. Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to improve prose quality, tighten writing, reduce clutter, or apply Zinsser's writing principles to a draft. For grammar and punctuation, use the proofread skill. For APSA style rules, use the apsa-style skill. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.

Guides selection of Qdrant search strategies including hybrid search, reranking, relevance feedback, MMR, and discovery APIs to improve retrieval quality.

Guides embedding model migration in Qdrant without downtime, covering alias swap, side-by-side, and hybrid search strategies.

Optimize Qdrant vector search performance through indexing strategies, query tuning, memory management, and hardware considerations.

Diagnoses and reduces Qdrant memory usage by analyzing resident memory, page cache, and providing optimization techniques like quantization, on-disk storage, and async_scorer.

Optimizes Qdrant query performance for large limits across multiple shards by using Poisson-distributed subsampling to reduce inter-shard data transfer.

Diagnoses and resolves slow Qdrant indexing and data ingestion by optimizing batching, sharding, HNSW parameters, and payload indexing strategies.

Use when planning a USENIX FAST project timeline from venue fit through choosing a Spring or Fall deadline, double-blind submission, the author-response period, shepherding or a one-shot revision, artifact evaluation, and the open-access camera-ready, with backward-planning offsets tuned to storage evaluation and honest handling of the two-deadline cycle.

Drafts a Motion for Judgment Notwithstanding the Verdict (JNOV) under FRCP 50(b) or state equivalents, with alternative new-trial request. Builds element-by-element evidentiary insufficiency arguments using transcript citations and preserves the appellate record. Use when drafting JNOV motions, post-trial motions, renewed judgment as a matter of law, or challenging jury verdicts for insufficient evidence.

APSA style checker for Quarto (.qmd) files. Checks numbers, capitalization, abbreviations, italics, in-text citations, titles of works, neutral and unbiased language, and APSA-specific terminology against the APSA Style Manual for Political Science (2018, updated 2023). Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to check APSA style, fix citations, review capitalization, check number formatting, or flag biased language in a .qmd document. For grammar, spelling, and punctuation, use the proofread skill instead. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.

经济金融顶刊文献速递与选题建议生成器。通过RSS和网页抓取获取经济学、金融学、会计学顶级期刊的最新论文， 筛选公司金融相关文献，生成中文综述摘要和研究选题建议。 当用户提到"期刊速递"、"文献周报"、"论文速递"、"最新文献"、"journal digest"、"paper digest"、 "选题建议"、"研究选题"、"顶刊追踪"、"文献追踪"、"周报"时触发此技能。 即使用户只是说"帮我看看最近有什么新论文"或"最近顶刊发了什么"，也应该触发。

Quarkus 3.x LTS 测试驱动开发——JUnit 5、Mockito、REST Assured、Camel 测试及覆盖率

Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system

Test-driven development for Quarkus 3.x LTS using JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo. Use when adding features, fixing bugs, or refactoring event-driven services.

Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications.

Drafts Qualified Domestic Relations Orders (QDROs) compliant with ERISA §206(d)(3) and IRC §414(p) to divide retirement benefits in divorce. Covers defined benefit pensions, 401(k)s, and defined contribution plans with plan-specific division formulas and alternate payee protections. Use when drafting QDROs, dividing retirement assets post-judgment, or preparing domestic relations orders for plan administrator review.

提供奉俊昊导演风格的创意建议，涵盖视觉方案、叙事建议、场景设计和执行要点，适用于剧本创作和影像设计。

Index local folders and search documents with BM25, vector, or hybrid queries, plus AI answers with citations and a web UI.

Search local documents, files, notes, and knowledge bases. Index directories, search with BM25/vector/hybrid, get AI answers with citations. Use when user wants to search files, find documents, query notes, look up information in local folders, index a directory, set up document search, build a knowledge base, needs RAG/semantic search, or wants to start a local web UI for their docs.

Guides test-driven development for Quarkus 3.x services with JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo, targeting 80%+ coverage for event-driven architectures.

Qdrant vector database — collections, upsert, search, filtering, payloads, sparse vectors, BM25

Turn account data into a QBR that earns the renewal. It builds the value-delivered story, adoption against the goals they signed up for, the open risks stated plainly, the forward roadmap, and the expansion ask, then hands you a deck outline. Built for B2B customer success teams, customizable to your CRM and product analytics. Trigger on "build a QBR", "prep the business review", "quarterly review for this account", "what do I show the customer", "value story for the renewal", or any account-review prep.

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.

Import Gerber, ODB++, Allegro .brd, .mcm files for PCB boards and IC packages. Inspect nets, layers, shapes, and stackups. TRIGGER: user asks to import, read, or open a PCB layout file. Gerber files use gerberRead or PCBReader; ODB++, Allegro .brd, .mcm, and native formats use pcbFileRead. Also when inspecting nets, layers, components, or stackups from an imported board. Invoke BEFORE writing import code — the query API (cadnet, cadnetList, componentList) is specialized. SKIP: EM analysis or S-parameter extraction (use matlab-analyze-em), PDN/IR-drop analysis (use matlab-analyze-pcb-pdn), building custom geometry (use matlab-assemble-pcb-layout), material/stackup definition only (use matlab-manage-pcb-material).

Use when working with *.excalidraw or *.excalidraw.json files, user mentions diagrams/flowcharts, or requests architecture visualization - delegates all Excalidraw operations to subagents to prevent context exhaustion from verbose JSON (single files: 4k-22k tokens, can exceed read limits)

Search local documents, files, notes, and knowledge bases. Index directories, search with BM25/vector/hybrid, get AI answers with citations. Use when user wants to search files, find documents, query notes, look up information in local folders, index a directory, set up document search, build a knowledge base, needs RAG/semantic search, or wants to start a local web UI for their docs.

Test-driven development for Quarkus 3.x LTS using JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo. Use when adding features, fixing bugs, or refactoring event-driven services.

Test-driven development for Quarkus 3.x LTS using JUnit 5, Mockito, REST Assured, Camel testing, and JaCoCo. Use when adding features, fixing bugs, or refactoring event-driven services.

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Runs an evidence-first, read-only workflow over large codebases via an external JSONL REPL server, retrieving only minimal file slices and greps to produce cited architecture and audit reports.

Prevent Kubernetes hallucinations by diagnosing and fixing failure modes: insecure workload defaults, resource starvation, network exposure, privilege sprawl, fragile rollouts, and API drift. Use when generating, reviewing, refactoring, or migrating manifests, Helm charts, Kustomize overlays, cluster policies, and platform-specific Kubernetes work for EKS, GKE, AKS, OpenShift, GitOps controllers, or observability stacks.

Sistema multiagente de IA para assistência em pesquisa científica que automatiza fluxos de trabalho de pesquisa desde análise de dados até publicação. Esta skill deve ser usada ao gerar ideias de pesquisa a partir de conjuntos de dados, desenvolver metodologias de pesquisa, executar experimentos computacionais, realizar buscas de literatura ou gerar papers prontos para publicação em formato LaTeX. Suporta pipelines de pesquisa end-to-end com orquestração de agentes personalizável.

Create exercise directory structures with sections, problems, solutions, and explainers that pass linting, then commit with git.