「filtering」の検索結果

Audit, classify, and selectively forget stored memories. Covers memory enumeration and classification by type/age/access frequency, staleness detection for outdated references, fidelity checks using external anchors, a decision tree for selective withdrawal, tombstoned deaccession so removed content stays recoverable, counter-memory inoculation for failed strategies that would otherwise be re-derived, preemptive filtering rules for what should never become memories, and an audit trail so forgetting itself is reviewable. Use when memory has grown large and uncurated, when project state has shifted significantly since memories were written, when retrieval quality has degraded, or as periodic maintenance alongside manage-memory.

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。

Purify water from wild sources using boiling, filtration, and chemical methods. Covers source assessment and priority ranking, sediment pre-filtering, method selection (boiling, chemical, UV, filter), altitude-adjusted boiling procedure, chemical treatment dosages, and safe storage practices. Use when needing drinking water in a wilderness setting, when available water sources are of unknown quality, in an emergency survival situation where dehydration is a risk, or when making water safe for cooking or wound cleaning.

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。

Stock Screener — pre-built screens (growth, value, momentum, dividend, earnings beats) plus custom natural language criteria. Returns top 10-20 matches ranked by Screen Fit Score (0-100). Triggered by "trade screen growth/value/momentum/dividend/earnings" or "trade screen custom <criteria>".

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。

Work with the @upstash/search TypeScript/JavaScript SDK, a serverless full-text and semantic search database with built-in reranking. Use when adding search to an app or site, creating a search index, upserting documents with searchable content and filterable metadata, running keyword, semantic, or hybrid search queries, reranking results, filtering with SQL-like or structured filter syntax, paginating with range, fetching or deleting documents, resetting an index, or checking index info. Also use when the user asks for site search, product, document, or knowledge-base search, or a managed search service that needs no cluster to run.

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。

Work with the @upstash/vector TypeScript/JavaScript SDK, a serverless vector database for embeddings, similarity search, semantic search, and RAG (retrieval-augmented generation). Use when upserting, querying, fetching, ranging, or deleting vectors, upserting raw text against an index with a built-in embedding model, choosing dense, sparse, or hybrid indexes, filtering by metadata, organizing data with namespaces, running resumable queries, or connecting Upstash Vector to an AI or LLM application. Also use when the user asks for a vector store, vector search, nearest-neighbor or kNN search, embeddings storage, semantic cache, recommendations or similarity features, or a hosted vector index that needs no infrastructure.

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。

Build content filtering for AI outputs. TRIGGERS - Use when user needs help with ai-content-filter related tasks.

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。

Bulk extract content from an entire website or site section. Use this skill when the user wants to crawl a site, extract all pages from a docs section, bulk-scrape multiple pages following links, or says "crawl", "get all the pages", "extract everything under /docs", "bulk extract", or needs content from many pages on the same site. Handles depth limits, path filtering, and concurrent extraction.

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。

Discover and list all URLs on a website, with optional search filtering. Use this skill when the user wants to find a specific page on a large site, list all URLs, see the site structure, find where something is on a domain, or says "map the site", "find the URL for", "what pages are on", or "list all pages". Essential when the user knows which site but not which exact page.

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。

Use the hyalo CLI instead of read/edit/grep/write when working with markdown (.md) files that have YAML frontmatter. This skill MUST be consulted whenever pi is working with markdown documentation directories, knowledgebases, wikis, notes, Obsidian-compatible collections, Zettelkasten systems, iteration plans, or any collection of .md files with frontmatter. Trigger this skill when: searching or filtering markdown files by content, tags, or properties; reading or modifying YAML frontmatter; managing tags or metadata across documents; toggling task checkboxes in markdown; getting an overview of a documentation directory; querying document properties or status fields; bulk-updating metadata across many markdown files; or when you find yourself repeatedly using read/edit/grep/write on .md files. Even if the user does not mention "hyalo" by name, use this skill whenever the task involves structured markdown documents with frontmatter. For pi sessions, ALWAYS use `--format text` for compact, LLM-friendly output.

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。

Use when you need to classify an IP as internet scanner noise vs. targeted activity. Returns noise/riot flags, classification (benign/malicious/unknown), actor name if known. IP-only. Commonly invoked by /ip-investigation to filter out mass-scanning noise. Retrieval only.

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。

Process multimedia files with FFmpeg (video/audio encoding, conversion, streaming, filtering, hardware acceleration) and ImageMagick (image manipulation, format conversion, batch processing, effects, composition). Use when converting media formats, encoding videos with specific codecs (H.264, H.265, VP9), resizing/cropping images, extracting audio from video, applying filters and effects, optimizing file sizes, creating streaming manifests (HLS/DASH), generating thumbnails, batch processing images, creating composite images, or implementing media processing pipelines. Supports 100+ formats, hardware acceleration (NVENC, QSV), and complex filtergraphs.

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 hybrid recommendation systems combining multiple strategies for improved accuracy. Use this skill when the user needs to overcome single-method limitations, combine collaborative and content-based filtering, or build a production recommendation pipeline — even if they say 'combine recommendation approaches', 'best recommendation architecture', or 'cold start plus personalization'.".

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。

"Implement collaborative filtering for recommendations based on user behavior patterns. Use this skill when the user needs to build a recommendation engine from user-item interaction data, find similar users or items, or predict ratings — even if they say 'users who bought this also bought', 'similar users', or 'recommend based on behavior'.".

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。

"Implement matrix factorization to decompose user-item interaction matrices into latent factor representations. Use this skill when the user needs scalable collaborative filtering, latent feature discovery, or dimensionality reduction for recommendation — even if they say 'SVD recommendations', 'latent factors', or 'factorize the rating matrix'.".

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。

SQL injection playbook. Use when input reaches SQL queries, authentication logic, sorting, filtering, reporting, or DB-specific blind and out-of-band execution paths.

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。

TanStack Table v8 patterns - useReactTable, column definitions, sorting, filtering, pagination, row selection, virtual scrolling, server-side data

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。

pnpm workspace protocol, filtering, catalogs, shared dependencies, publishing, and CI/CD for monorepo management

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。

Chroma vector database -- collection management, automatic embedding, metadata filtering, document storage, query patterns

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。

Weaviate vector database patterns with weaviate-client v3 -- collection management, vectorizer modules, hybrid search, filtering, generative search (RAG), multi-tenancy, batch imports

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。

Meilisearch search engine patterns -- client setup, indexing, search, filtering, facets, geo search, multi-tenancy, task management

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。

Pinecone serverless vector database -- index management, vector operations, metadata filtering, namespaces, hybrid search, inference API

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。

Qdrant vector database -- collection management, point operations, payload filtering, named vectors, quantization, recommendations, snapshots

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。

Generate a weekly changelog entry from git history, filtering operational noise and producing editorial summary, field notes, statistics, and a bounded commit manifest. Stops for review unless commit was explicitly requested.

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。

Build comprehensive DNA methylation maps by aggregating WGBS (Whole Genome Bisulfite Sequencing) data across multiple ENCODE experiments, donors, and labs. Use when the user wants to answer "where is DNA methylated/unmethylated in my tissue?" by combining per-CpG methylation data into tissue-level methylation profiles. Handles coverage filtering, identifies hypomethylated regions (HMRs) and partially methylated domains (PMDs), and manages cross-lab variation.

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。