「dex」の検索結果

Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.

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Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

日本語の概要は準備中です。原文の説明を表示しています。

Interactive Archon integration for knowledge base and project management via REST API. On first use, asks for Archon host URL. Use when searching documentation, managing projects/tasks, or querying indexed knowledge. Provides RAG-powered semantic search, website crawling, document upload, hierarchical project/task management, and document versioning. Always try Archon first for external documentation and knowledge retrieval before using other sources.

日本語の概要は準備中です。原文の説明を表示しています。

Backend-neutral image generation: create new raster images and looping GIF/WebP animations through the local one-file image-use CLI (formerly chatgpt-imagegen), using the user's ChatGPT subscription by default, the Codex backend as fallback, or an optional Gemini subscription — no API key or daemon. Triggers: image generation, generate an image, draw a picture, 画图, 画一张, 生成图片, 生图, 配图. Use for photos, illustrations, icons, hero banners, mockups, sprites, concept art, animation loops, and figures for documents, proposals, blog posts, or READMEs; save outputs in the workspace. Auto mode uses the logged-in ChatGPT browser via chrome-use. Gemini users can pass --backend gemini or agy. Proactively propose useful figures while authoring long-form content. Do not use for editing existing images, SVG/vector work, code-native graphics, established icon systems, explicit high-quality or transparent API output, or end-user image-generation services.

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Summarize, organize, and normalize messy research materials into an IEEE-ready writing brief before manuscript drafting. Use when Codex needs to process a folder or collection of experiment logs, code files, AI chat exports, idea notes, literature summaries, related-work notes, copied introduction excerpts, Zotero-derived paper summaries, tables, figures, or scattered Markdown/text records and convert them into structured inputs for ieee-writing, ieee-experiment, ieee-citation, ieee-reviewer, or ieee-response.

日本語の概要は準備中です。原文の説明を表示しています。

Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).

日本語の概要は準備中です。原文の説明を表示しています。

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

日本語の概要は準備中です。原文の説明を表示しています。

PowerX CRUD 规范聚合入口，按任务类型分派到 http/grpc/migration/model/repository/service 等子技能。

日本語の概要は準備中です。原文の説明を表示しています。

Postgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pg_cron, pgmq), vector/semantic search (pgvector), and restoring dumps (pg_restore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.

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Coordinator-only native Codex issue-to-develop workflow. Specialists use only their assigned role and task.

日本語の概要は準備中です。原文の説明を表示しています。

Search, create, and manage notes in the Obsidian vault with wikilinks and index notes. Use when user wants to find, create, or organize notes in Obsidian.

日本語の概要は準備中です。原文の説明を表示しています。

Design engineering principles and patterns for building polished, accessible web interfaces. Use this skill when building UI components, reviewing frontend code, implementing forms, handling touch interactions, optimizing performance, or creating marketing pages. Triggers on: design engineering, UI polish, input fields, form validation, button states, touch devices, mobile UX, accessibility, a11y, keyboard navigation, aria labels, font rendering, typography, layout shift, z-index, animations, transitions, easing, hover effects, tap targets, iOS Safari, prefers-reduced-motion, marketing pages, landing pages, dark mode, theme switching, scrollbars, gradients, shadows, virtualization, preloading.

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Guided, hands-on course teaching architects how to use Codex or Claude Code — six short modules, each built around an exercise on a bundled sandbox project (a fictional Brooklyn art museum expansion). Resumable across sessions via PROGRESS.md. Use when the user runs $learn or /as:learn, says they're new to AI-assisted project work, or asks how to learn it.

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Create or update an Arch Studio skill for Codex or Claude Code using the host's native skill maker when available, with Arch Studio governance and validation. Use when asked to create, package, adapt or revise a reusable skill.

日本語の概要は準備中です。原文の説明を表示しています。

Learn daily from this machine's Claude Code, Codex, Hermes, OpenClaw and Cursor sessions. Review skill changes and lessons with accept/reject/tbd; recall lessons at session start.

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Carry out a released charter to a proven result: plan only as much as the work needs, do the work through the project's own workers, prove every success check with a recorded real run, get one independent review, and close honestly. Invoke explicitly as `$deliver <charter>` (Codex) or `/deliver <charter>` (Claude, Cursor), or the way your agent invokes a skill, or when a dispatch names you the executor of a charter.

日本語の概要は準備中です。原文の説明を表示しています。

Read remaining Claude Code and Codex subscription quota without spending it. Use when the user asks or after a vendor rejects work for quota; a caller such as rotate-agent may also arm a scheduled read on purpose. Never poll on your own; after a `wait` verdict, pass the reset wait to `sno heartbeat` and re-read once when it ends.

日本語の概要は準備中です。原文の説明を表示しています。

Quota-triggered failover from Claude Code, Codex, Cursor, Hermes or OpenClaw. When armed, it reads the sender quota and tries other-vendor models in place, then receiving agents in the configured order. Use when a long run must finish even if one vendor's quota runs out. Not a monitor for anything else.

日本語の概要は準備中です。原文の説明を表示しています。

Ultra-fast RNA-seq transcript/gene quantification via quasi-mapping (no BAM). Builds a k-mer index from transcriptome FASTA, quantifies in minutes. Outputs TPM/count tables (quant.sf) with optional GC- and sequence-bias correction. Integrates with tximeta/tximport for DESeq2/edgeR. Use STAR when a genome-aligned BAM is needed.

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Python library for genomic interval ML. Train/apply region2vec embeddings turning BED regions into vectors, index interval datasets for ML, search embedding space with BEDSpace, and evaluate embedding quality. Use for chromatin accessibility clustering, regulatory element classification, and cross-sample region comparison.

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Genomic interval ops on BED/BAM/GFF/VCF. Find overlaps, merge intervals, compute coverage, extract FASTA, find nearest features. Core for ChIP-seq peak annotation, region filtering, genome arithmetic. Use tabix for indexed single-region queries; use deeptools for normalized bigWig coverage.

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Splice-aware RNA-seq aligner producing sorted BAM and splice junction tables. Builds genome index, runs two-pass alignment for better junctions. Outputs sorted BAM, junctions (SJ.out.tab), stats (Log.final.out), optional gene counts. Use Salmon for fast pseudoalignment; STAR when a BAM is needed for variant calling, IGV, or ENCODE pipelines.

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Chunked N-D arrays with compression and cloud storage. NumPy-style indexing. Backends: local, S3, GCS, ZIP, memory. Dask/Xarray integration for parallel and labeled computation. For lineage use lamindb; for labeled arrays use xarray.

日本語の概要は準備中です。原文の説明を表示しています。

Time-to-event modeling with scikit-survival: Cox PH (elastic net), Random Survival Forests, Boosting, SVMs for censored data. C-index, Brier, time-dependent AUC; Kaplan-Meier, Nelson-Aalen, competing risks. Pipeline/GridSearchCV compatible. Use statsmodels for frequentist, pymc for Bayesian, lifelines for parametric.

日本語の概要は準備中です。原文の説明を表示しています。