「embed」の検索結果

Recover data from archived REST APIs using Wayback Machine. Use when: (1) Recovering data from defunct services like Vine, Twitter, or other platforms, (2) Need to find which API endpoints were archived vs which require authentication, (3) Building data recovery pipelines from web.archive.org. Covers CDX API queries to discover archived endpoints, understanding what gets archived (public) vs what doesn't (authenticated), and extracting embedded JSON from archived web pages as a fallback.

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Translate natural-language requirements or structured specification documents into formal temporal logic properties (LTL, CTL, safety/liveness properties). Use when users need to formalize requirements for model checking, formal verification, or property specification. Handles embedded/real-time systems, hardware verification, concurrent systems, and reactive systems. Resolves ambiguities, asks clarifying questions when needed, and outputs machine-checkable formulas with explanations. Supports multiple output formats (SPIN, NuSMV, Uppaal, TLA+, Maude).

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Cloudflare Vectorize vector database for semantic search and RAG. Use for vector indexes, embeddings, similarity search, or encountering dimension mismatches, filter errors.

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Cloudflare Workers AI for serverless GPU inference. Use for LLMs, text/image generation, embeddings, or encountering AI_ERROR, rate limits, token exceeded errors.

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Evaluate JavaScript at bundle time and inline results. Use when optimizing compile-time code generation, embedding files, inlining environment variables, or executing code during the bundling process.

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Think and work like an expert Information Retrieval Scientist. Use when a task calls for Information Retrieval Scientist judgment. Reasons from the Probability Ranking Principle, Saracevic's relevance layers, and Cranfield pooling through tuned BM25, SPLADE/ColBERT/dense and LLM reranking, trec_eval/ir_measures with paired topic-level tests, interleaving, and nugget-based RAG evaluation while treating unjudged-as-nonrelevant pools, position-biased clicks, LLM-judge circularity, single-vector embedding limits, and benchmark contamination as first-class failure modes.

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Think and work like an expert Histologist. Use when a task calls for Histologist judgment. Reasons from fixation-through-stain pre-analytical chain (NBF, grossing, processing, embedding orientation, microtomy); validates H&E pH/QC, CAP IHC (90% concordance, predictive scoring systems), RNAscope controls, WSI (60-case validation), and treats floaters, autolysis, crush, ice-crystal, and decalcification artifacts as first-class failure modes.

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Think and work like an expert Electromagnetics Engineer. Use when a task calls for Electromagnetics Engineer judgment. Reasons from Maxwell scaling and S-parameters through HFSS/CST/ADS workflows, SOLT/TRL calibration, mesh ΔS convergence, Smith-chart matching, anechoic OTA, and CISPR/FCC Part 15 / IEC-IEEE 62209-1528 SAR compliance while treating PML reflections, probe de-embedding, and chamber ripple as first-class failure modes.

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Think and work like an expert Dynamical Systems Theorist. Use when a task calls for Dynamical Systems Theorist judgment. Reasons from state spaces, invariant sets, bifurcations, and multiple time scales through normal-form classification, center-manifold reduction, Floquet/Poincaré maps, and continuation tools like AUTO, MatCont, and DynamicalSystems.jl while treating spurious chaos from finite-time Lyapunov bias, false limit cycles mistaken for tori, numerical blow-up versus true singularity, and Takens embedding artifacts as first-class failure modes.

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Think and work like an expert Computational Chemist. Use when a task calls for Computational Chemist judgment. Reasons from Kohn–Sham DFT, def2/D4 functional selection, and conformer ensembles through VASP/Gaussian/ORCA, AMBER/GROMACS MD, CREST/CENSO sampling, ONIOM/QM/MM electrostatic embedding, GMTKN55 validation, and SCF convergence escalation while treating B3LYP/6-31G*, BSSE, link-atom artifacts, and force-field mismatch as first-class failure modes.

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Select, run, and govern NVIDIA Cosmos world-video generation across Cosmos 3 Generator, Predict2.5, Transfer2.5, downloadable checkpoints, self-hosted NIMs, and hosted preview surfaces. Use for text/image/video-to-world, controlled world transfer, multiview or action-conditioned physical-AI video, local checkpoint pinning, hardware planning, inference approval, and output validation; do not use for Cosmos Reason/Embed-only tasks.

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Build, configure, and ship production voice agents on the ElevenLabs Agents platform (branded "ElevenAgents," formerly "Conversational AI"). Use when an agent must design a spoken-conversation system prompt, pick an LLM and TTS voice/model for a real-time voice bot, wire client/server/system tools and knowledge-base RAG, connect a channel (WebRTC/WebSocket SDK, embeddable widget, or telephony via Twilio/SIP), tune turn-taking and latency, set up simulation testing and evaluation, or reason about pricing, concurrency, and the consent/disclosure obligations of a synthetic voice talking to real people. Not for plain non-conversational text-to-speech, dubbing, or music generation.

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Dimensionality reduction and clustering for single-cell RNA-seq using Seurat (R) and Scanpy (Python). Use for running PCA, computing neighbors, clustering with Leiden/Louvain algorithms, generating UMAP/tSNE embeddings, and visualizing clusters. Use when performing dimensionality reduction and clustering on single-cell data.

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Facilitate a structured conversation to define requirement standards for a project — epic and feature definitions, scenario structure, AC format, priority notation, status workflow, and naming conventions. Produces a formal requirement-standards.md that the requirement-quality atom reads via config resolution, customising its embedded defaults for the team's product process. Use when setting up a new project, defining product standards, or when the user says 'set up requirement standards', 'define feature standards', 'configure requirement forge', 'define how features should be structured', or 'requirement forge refiner'.

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Use when the user wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.

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Implements document chunking, embedding generation, vector storage, and retrieval pipelines for Retrieval-Augmented Generation systems. Use when building RAG applications, creating document Q&A systems, or integrating AI with knowledge bases.

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Installs and configures ktx, the open-source context layer for data agents — runs ktx setup non-interactively with hidden CLI flags, configures database connections and embeddings, installs agent integration, and verifies readiness. Use when the user asks an agent to add ktx to a project, connect data sources, install agent rules, ingest schema, or troubleshoot a local ktx install.

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Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface (18 tools) available with --full flag. Two-verb model: inhale (session_start) and exhale (session_end). Correction-first memory with decision trail tracking, watch_for warnings, palace rooms with salience scoring, cross-project insight matching, same-day journal merging, ambient recall hooks. Local markdown only. Zero cloud, zero telemetry, Obsidian-compatible. Optional Supabase backend: when configured via `ar setup supabase`, recall() uses pgvector cosine similarity on OpenAI/Voyage embeddings instead of keyword search — same API, semantic understanding. Gracefully degrades to local search if not configured.

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AI SDK for Python (the `ai` package). Use for Python model calls (LLMs, image, video, speech, embedding, transcription, reranking, or evaluation), agents, model interaction tests, tool calling, subagents, approvals, durable execution, telemetry, AI SDK UI backends, and custom providers.

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Use when the user wants a short, design-led motion graphic where motion is the message: kinetic typography, stat or number count-up, chart/data-viz hit, logo sting, brand lockup, lower-third, callout, social overlay, animated headline/tweet/news item, motion poster, or quick captured-page highlight. Usually under 10s and up to ~30s, with no live-action subject. Can render to MP4 or transparent overlay. Not for longer, multi-scene, or brand-reel pieces (use general-video), topic explainers (faceless-explainer), PR videos (pr-to-video), or captions on existing footage (embedded-captions). When unsure whether it's a quick motion-first piece or a longer treatment, see /hyperframes.

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Expert guidance for Excalidraw, the open-source virtual whiteboard library for creating hand-drawn style diagrams and sketches. Helps developers embed Excalidraw in React applications, build custom integrations, and leverage the API for programmatic diagram creation.

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Cube is an open-source semantic layer that sits between a data warehouse and analytics applications and serves governed metrics over REST, GraphQL and SQL APIs. Use when a user asks to define cubes, measures and dimensions, add pre-aggregations, build a metrics API or embedded analytics, set up multi-tenant row-level security, or query Cube from React or the REST API.

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Serverless vector database at the edge with Cloudflare Vectorize. Use when: building semantic search on Cloudflare Workers, RAG pipelines at the edge, low-latency vector similarity search, or storing and querying embeddings without managing a separate vector database.

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Expert guidance for Cal.com, the open-source scheduling platform for building booking and appointment systems. Helps developers integrate Cal.com's embed widgets, REST API, and webhooks to add scheduling capabilities to their applications.

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