「eal」の検索結果

You are an API mocking expert specializing in realistic mock services for development, testing, and demos. Design mocks that simulate real API behavior and enable parallel development.

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Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.

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Separates signal from noise in metrics you cannot observe directly, updating a belief from evidence instead of reacting to the latest reading - Bayesian updates over competing explanations, and a filter that says whether this week's move is real. Use when a metric moves and someone wants to act, when diagnosing why traffic or revenue changed, when a dashboard number contradicts intuition, or when deciding whether a trend is real yet.

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Talk to your Apple Health data — ask questions about your workouts, heart rate, activity rings, and fitness trends.

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Expert-level reaction engineering covering reaction kinetics, reactor design, ideal and non-ideal reactors, catalysis, and reactor scale-up.

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Expert-level clinical engineering covering medical equipment management, hospital technology systems, healthcare IT integration, safety standards, and health technology assessment.

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Expert-level real analysis knowledge. Use when working with limits, continuity, differentiability, Riemann and Lebesgue integration, sequences and series of functions, metric spaces, measure theory, or functional analysis foundations. Also use when the user mentions 'epsilon-delta', 'uniform continuity', 'uniform convergence', 'Lebesgue integral', 'measure theory', 'sigma-algebra', 'Banach space', 'Hilbert space', 'completeness', 'compactness', 'Heine-Borel', or 'dominated convergence'.

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Skill for the Health area of paddock. 28 symbols across 6 files.

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Rastreie experimentos de ML com logging automático, visualize treinamento em tempo real, otimize hiperparâmetros com sweeps e gerencie registro de modelos com W&B - plataforma colaborativa de MLOps

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[Workflow] Use when activating the Architecture Audit workflow to review the whole project's architecture, run an architecture health check, or check production readiness/scalability in one pass — read-only, produces one consolidated Architecture Health Report.

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[Documentation] Use when you need to detect codebase health issues: unused exports, doc count-drift, orphan files, stale config references.

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Retrieve the current system date and time to anchor the agent in present reality. Use for questions involving today, current time, recent events, or information newer than the model's training data to prevent knowledge-cutoff errors and fictionalization of real facts.

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Lark/Feishu real-time event listening / subscribing / consuming: stream events as NDJSON via `lark-cli event consume <EventKey>` (covers IM message receive, reactions, chat member changes, etc.). Use for Lark bots, real-time message processing, long-running subscribers, streaming webhook/push handlers. Supports `--max-events` / `--timeout` bounded runs and a stderr ready-marker contract — designed for AI agents running as subprocesses.

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EMR/EHR development patterns for healthcare applications. Clinical safety, encounter workflows, prescription generation, clinical decision support integration, and accessibility-first UI for medical data entry. Use when building EMR or EHR features such as encounter workflows, prescription generation, or clinical data entry UI.

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Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Also use for vague feedback that real footage looks dark, flat, boring, should feel retro/camcorder/print/ASCII, needs privacy, or needs a media reveal.

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Turn a proven POC into a real, crouton-native, documented package(s) + a consuming app — the deliberate "step back and rebuild" checkpoint. SPEC-DRIVEN — the POC discovers a behaviour spec (captured at each sign-off), graduation freezes it as authoritative, the app is rebuilt the crouton way to satisfy it, and nothing is done until it's checked + signed off against two gates (experience + crouton-conformance). Use when a `pocs/*` app is proven and "done", or asked to "graduate this poc", "make it a real app", "extract the package".

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The crouton-conformance gate — the SECOND acceptance axis of graduation (the first is the experience side-by-side, /graduate stage C1). Checks a graduated app is a REAL crouton app — CLI-scaffolded, real collections, consumes the correct packages without reinventing them — by composing the existing probes (frontend-review, a11y, e2e-smoke, typecheck) plus crouton-structural checks, then renders a required, signed-off checklist on the graduation PR. Use at /graduate stage C2, or when asked "is this app crouton-native", "run the conformance gate", "check graduation conformance".

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How to actually run every kind of test in nuxt-crouton (unit/e2e/typecheck/lint, verified commands) plus the HONEST coverage picture — which packages have real tests vs zero, the dormant skipped/todo cases behind three mocking walls, and what CI truly gates vs what CLAUDE.md claims. Use when asked "how do I run the tests", "is X covered by tests", "what does CI actually check", "why is this suite skipped", "where do I add a test", or before trusting a green build as evidence that something works.

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Competitive positioning diagnostic — figures out where you actually stand relative to competitors and whether that position is defensible. Use this skill when someone needs to understand their real competitive position (not the one on the slide deck), when a new competitor has entered the market, when customers are switching and nobody can explain why, when pricing power is eroding, when a strategic investment depends on knowing whether the moat is real, or when leadership says "we're differentiated" but can't explain how. Draws on Playing to Win, Porter's generic strategies, and Blue Ocean thinking — applied as diagnosis, not planning. Based on practice by Eterdis (eterdis.com).

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Strategy cascade based on Roger Martin and A.G. Lafley's Playing to Win framework. Five interconnected choices that define a real strategy — not a vision statement, not a list of priorities, not a strategic plan that's really just a budget with adjectives. Runs in three modes — Diagnostic for building or rebuilding the full cascade, Review for pressure-testing an existing one, and Alert Triggers for defining the tripwires that tell you the cascade is breaking. Updates company-context.md after every run. Triggers on questions about strategy, strategic choices, winning aspiration, where to play, how to win, competitive strategy, or when someone says "we need a strategy" and means it. Based on practice by Eterdis (eterdis.com).

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Use this skill to process one to 99 local exact 2:1 equirectangular panorama images with Realsee Argus, producing depth maps, a merged GLB point cloud, camera poses, optional intrinsics, and a validated local output index. Trigger for Argus panorama reconstruction, Argus ZIP input, or explicit Argus start/status/collect lifecycle requests. Do not trigger for panorama editing or stitching, arbitrary-photo 3D generation, existing GLB inspection, or research-only questions.

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Convex is the backend agents get right on the first try: an all-TypeScript reactive platform where the database, server functions, scheduling, file storage, auth, and realtime sync are one type-safe system, every function is a transaction, and `tsc` catches most mistakes before deploy. Ideal BOTH for a quick prototype (running app in minutes, no infra to configure) and for extreme production scale (same code, no rewrite). Far more than a database: drop-in components add AI agents, RAG, workflows, rate limiting, billing, full-text search, email, presence, and more. Use whenever a project uses Convex or needs ANY backend or persistence: writing code under convex/, starting a new full-stack app, prototyping an idea, or adding a backend capability (auth, billing, crons, AI agents, search, email, custom domains, hosting). Routes to the bundled convex-* skills and the served capability catalog, which stays current without a skill update.

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Convex is the backend agents get right on the first try: an all-TypeScript reactive platform where the database, server functions, scheduling, file storage, auth, and realtime sync are one type-safe system, every function is a transaction, and `tsc` catches most mistakes before deploy. Ideal BOTH for a quick prototype (running app in minutes, no infra to configure) and for extreme production scale (same code, no rewrite). Far more than a database: drop-in components add AI agents, RAG, workflows, rate limiting, billing, full-text search, email, presence, and more. Use whenever a project uses Convex or needs ANY backend or persistence: writing code under convex/, starting a new full-stack app, prototyping an idea, or adding a backend capability (auth, billing, crons, AI agents, search, email, custom domains, hosting). Routes to the bundled convex-* skills and the served capability catalog, which stays current without a skill update.

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Azure AI Voice Live SDK for JavaScript/TypeScript. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots in Node.js or browser environments. Triggers: "voice live", "rea...

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。