「index」の検索結果

Neutral, framework-agnostic decision tree for project kickoff: "which agent / RAG / LLM framework should I reach for?" Synthesizes the ecosystem sections of 7 landmark-project SOPs (LangGraph, LlamaIndex, DSPy, CrewAI, vLLM, Aider, Dify) into one layered rubric. Core stance: frameworks are LAYERS, not competitors — a real project usually combines DSPy (compile) + LlamaIndex (retrieve) + LangGraph (orchestrate) + vLLM (serve), and you choose ONE per layer, not one to rule all. Use when starting any LLM/agent/RAG project, or whenever the "which framework?" question is asked. Deliberately neutral — unlike vendor docs and the LangChain-biased `framework-selection` on skill.sh, this skill has no horse in the race.

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Build or refresh the Operator Project Index.

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Build or refresh the Operator Project Index.

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Quick reference for common SQL patterns, CTEs, window functions, and indexing strategies. Triggers on: sql patterns, cte example, window functions, sql join, index strategy, pagination sql.

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Designs convex/schema.ts tables, validators, indexes, and relationships, and keeps the schema honest as data evolves. Use when creating tables, adding fields, choosing index fields, modeling relationships, or when a validator error appears at deploy time.

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Create and manage database migrations with reversible changes, proper naming conventions, and zero-downtime deployment strategies. Use this skill when creating database migration files, modifying schema, adding or removing tables/columns, managing indexes, or handling data migrations. Apply when working with migration files (e.g., db/migrate/, migrations/, alembic/, sequelize migrations), schema changes, database versioning, rollback implementations, or when you need to ensure backwards compatibility during deployments. Use for any task involving database structure changes, index creation, constraint modifications, or data transformation scripts.

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CLI toolkit for SAM/BAM/CRAM: sort, index, convert, filter, QC alignments. Core commands: view, sort, index, flagstat, stats, depth, markdup, merge. Required between alignment and variant/peak calling. Use pysam for Python-native BAM access; deeptools for normalized coverage tracks.

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Query and download NCI Imaging Data Commons (IDC) cancer radiology and pathology datasets via the idc-index Python client. No authentication required: the parquet index ships inside the pip wheel, SQL runs locally via DuckDB, and DICOM downloads stream from public S3/GCS buckets through s5cmd. Use sql_query() for DuckDB cohort selection, get_collections/get_patients/get_dicom_studies/get_dicom_series for hierarchical browsing, download_from_selection() for downloads, and get_viewer_URL() for OHIF/Slim links. Use pydicom-medical-imaging for local DICOM reading; histolab for whole-slide pathology preprocessing.

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Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns

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Designs relational and document database schemas from requirements or an existing app - tables and collections, keys, relationships, constraints, indexes driven by real query patterns, ERDs, and reversible migration scripts - with PostgreSQL (including Supabase) as the default and MySQL, SQLite, and MongoDB supported. Use when the user wants to model data for a new app or feature, review or fix an existing schema, choose keys or indexes, plan multi-tenancy, normalize or denormalize, or write CREATE TABLE statements or migrations, even if they just describe their app and ask "how should I store this". For moving data between database providers, use database-migrator.

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Index of Apple developer documentation for iOS, macOS, and related frameworks. Use when looking up what APIs exist in a framework, browsing available documentation, or deciding what docs to fetch. Covers SwiftUI, UIKit, Core Animation (QuartzCore), XCTest, HealthKit, Combine, SwiftData, and more.

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Use ColBERT/colbert-ai for late-interaction retrieval: prepare data, inspect configs, train/fine-tune, index collections, search rankings, update indexes, serve search, evaluate MS MARCO/LoTTE outputs, or reason about Baleen multi-hop retrieval.

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Implements the right to be forgotten in search engines under GDPR Article 17 and the CJEU Google Spain ruling (C-131/12). Covers delisting request procedures, criteria assessment balancing privacy against public interest, and geographic scope determination. Activate for right to be forgotten, search delisting, Google Spain, de-indexing queries.

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Code intelligence over repositories Guaardvark has indexed: semantic code search, exact-text search, file listing, PageRank repository map, import dependency graph, reading one class or function, analysis and generated rewrites, plus the System Mapper and self-improvement status. Use when the user asks where something is implemented, how modules depend on each other, or wants an architecture map of an indexed repo.

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Analyze Chinese notes, articles, manuscripts, and digital card-box material with FIRE 2.0: Full-D numbering, Index keyword webs, Route thinking paths, and Evolution over time. Use when Codex needs to prepare material for semantic search, turn temporary notes into permanent or project notes, build table-of-contents/index/search structures, create compact Chinese FIRE cards, or maintain this skill's original discussion thread provenance.

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Create iMandalArt 2.2 pure-text 3x3 Mandala index cards with a five-character center axis, eight orthogonal surrounding angles labeled Ⓐ-Ⓗ, compact title cells such as Ⓐ健康復節, hard-line CJK layout, optional の字型 ordering, and 井字號 compass ordering. Use when the user asks for iMandalArt, iMandalart, I MandalArt, の字型, ◊字型, 井字號, 中國城市方位, 64＋8＋1, 手機方形曼陀羅, 正方形九宮索引卡, 五字定格, ◎中心, Ⓐ-Ⓗ 九宮卡, TheBrain/Cerebro preview-safe hard-line cards, or a square 3x3 card that is not a Markdown table, visible-border PE2 card, or 81-cell Mandala.

Use BIRD Book Deconstructor 2.2 to apply the formal BIRD 2.1 Knowledge Address protocol to complex manuscript text and TheBrain Thoughts. Use when splitting books into chapter/section/item knowledge nodes, assigning Book Address, structured Knowledge Index (Weight, Type, Keyword, Alias), Routes, verified Deep Links, and Semantic Roles; producing BIRD Excel workbooks, TheBrain scaffolds, Roam JSON, monochrome printable double nine-grid cards, or a routed handoff from iMandalArt to A4 eight-page booklets; or auditing and migrating existing BIRD/TheBrain indexes.

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Search an index of public repositories, GitHub issues, merged pull requests, repository READMEs, and curated documentation sites. Use when a programming question needs external documentation or upstream evidence.

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Any live-web task via the Firecrawl CLI — including ordinary web research: searching the web, reading or extracting pages, gathering sources, discovering site URLs, bulk extraction, downloading a site, change alerts, or pages needing clicks/login — web only; local files route to firecrawl-parse. For US legal or regulatory questions use gov; for papers use firecrawl-research-index; for library, API, error, or bug questions use firecrawl-developer-index.

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Think and work like an expert Forestry Scientist. Use when a task calls for Forestry Scientist judgment. Reasons from silvicultural systems, site index, DGH and DBH increment, and FIA cruise design through FVS/ORGANON calibration, LiDAR area-based inventory with support matching, and IPCC carbon pools while treating site-index misassignment, plot edge effects, and change-of-spatial-support bias as first-class failure modes.

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Use when an agent must make TwelveLabs do real video-understanding work: indexing footage, semantic/visual search across an archive, generating descriptions, summaries, chapters, highlights, and tags from video, producing multimodal embeddings, or wiring TwelveLabs into a media-production pipeline (NLE panels, logging, compliance review, metadata). Covers the current model families (Marengo for search/embeddings, Pegasus for video-to-text analysis), the v1.3 Video Understanding API (indexes, assets, tasks, search, analyze, embed), prompt construction for analysis, capability and format limits, pricing/quota math, output quality review (hallucination and timestamp accuracy), and privacy/rights obligations when footage shows real people. Not for generating or editing video pixels — this is analysis and retrieval.

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Internal — for Boundless team members only. Cross-reference Boundless indexer API data, broker telemetry, and service logs to investigate production and staging operational issues. Use when the user wants to understand why slashings happened on prod/staging, diagnose prover or service failures in deployed environments, correlate market events with broker behavior, investigate fulfillment rate drops, look at prover/service logs, or perform any analysis that requires combining on-chain indexer data with off-chain broker telemetry and CloudWatch logs. Also use when the user asks to "investigate", "diagnose", or "find root cause" for prover, service, or market issues on live networks. Do NOT use for debugging local code changes, reviewing PRs, or investigating issues in the codebase itself.

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Configure and use Elasticsearch for full-text search, custom analyzers, aggregations, and index management. Use when a user needs to design search mappings, write complex queries, build aggregation pipelines, tune relevance scoring, or optimize index performance for search workloads.

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Designs database schemas with proper normalization, indexing, constraints, and tenant isolation patterns. Use when someone needs to create a new database schema, add multi-tenant support, design row-level security policies, or optimize table structures. Trigger words: database schema, table design, RLS, row-level security, foreign keys, indexes, migrations, ERD, data model, normalization.

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