1,175 件 ・ 関連度順
概要と使いどころ
Analyze survey and feedback data with statistical distributions, cross-tabulations, significance testing, and open-ended theme extraction. Produces executive-ready survey reports with segment comparisons and action recommendations. Use when processing NPS, CSAT, employee engagement, or market research surveys.
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 lighting or rendering a PlayCanvas scene, covering lights, ambient and environment lighting, sky, shadows, tone mapping, exposure, fog, and post-processing.
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 adding visual effects to a PlayCanvas app, to choose between particle systems, shader chunks, runtime meshes, and post-processing.
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。
Execute Indirect Prompt Injection attacks against Large Language Models (LLMs) by subtly embedding malicious instructions within external data sources (e.g., websites, documents, databases) that the LLM autonomously ingests. This forces the model to execute attacker-controlled commands under the guise of processing legitimate user requests.
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 integrating Celery with Django - task definition and calling, django-celery-beat scheduling, worker deployment, Flower monitoring, testing tasks, batch processing, or choosing between cron and beat
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。
Full instrumentation from day one. PostHog consolidates product analytics + feature flags + error tracking (one platform, one bill). GA4 via GTM (14-step automation, custom dimensions over events, server-side tagging). Sentry (deep error tracking + performance). Stripe (webhook-first with idempotent processing). Listmonk on Coolify (newsletters via Amazon SES SMTP relay). PLG 7-layer framework. Programmatic SEO (5 page types). Incident auto-remediation via Sentry→Inngest pipeline. AI search (GEO) awareness. Local business conversions (phone_click, direction_click, form_submit, booking_click) with CRO patterns for both SaaS and local.
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。
Supreme policy layer governing all agent behavior. Autonomy, one-line prompt interpretation, speed standards, emphasis signal processing, cross-skill coordination, done definitions, conflict resolution. Loaded every prompt.
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。
React Three Fiber (R3F) 3D rendering — Canvas, meshes, materials, lights, cameras, animations, events, physics, post-processing, performance
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。
Background fetch, processing tasks, background location, headless JS, battery optimization - Expo and bare React Native
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。
Job queues, background processing, and task scheduling with BullMQ v5
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。
Image understanding and document analysis with Claude's multimodal capabilities -- image input formats, PDF processing, multi-image patterns, structured extraction, and token cost estimation
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。
Stripe payment processing — Checkout Sessions, Payment Intents, subscriptions, webhooks, Connect, customer management, error handling
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。
Implementation guide for common DSP algorithms. Use when the user asks "implement a lowpass filter", "how do I write a compressor", "reverb algorithm", "FFT convolution", "pitch shifter", or "oscillator with no aliasing". Trigger on phrases like "biquad filter", "state variable filter", "feedback delay network", "phase vocoder", "overlap-add", "PolyBLEP", or any request to implement a specific DSP processing block.
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。
Step-by-step guide for building Web Audio processing pipelines — AudioWorklet processors, custom nodes, parameter automation, and WebMIDI integration. Use when the user asks how to build or wire up Web Audio code from scratch. Trigger on phrases like "build an AudioWorklet", "create a custom Web Audio effect", "how do I use WebMIDI", "how do I write an AudioWorkletProcessor", or "how do I connect AudioNodes".
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。
Explains DSP math concepts to developers who need the theory behind an algorithm. Use whenever the user asks how a signal-processing concept works, wants intuition behind a formula, or hits a math-shaped bug. Trigger on phrases like "how does a Fourier transform work", "explain z-transforms", "what is convolution", "why does my biquad ring", "what is windowing for", "what causes aliasing", or "how do I convert gain to dB". Also trigger when the user pastes DSP code and asks why it behaves a certain way.
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。
Apply a formal state machine to issues — assign category (bug/enhancement/question/spike) and state (needs-triage → needs-info → ready-for-agent → ready-for-human → wontfix). Issues marked ready-for-agent become inputs to supergraph:plan. Use when processing a backlog, reviewing new issues, or preparing work for automation.
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。
Unity 6 graphics and rendering guide. Use when working with render pipelines (URP, HDRP, Built-in), shaders, Shader Graph, materials, textures, cameras, post-processing, or rendering optimization. Covers Render Graph, batching, draw call optimization, and GPU instancing. Based on Unity 6.3 LTS documentation.
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。
Unity 6 lighting and visual effects guide. Use when working with lights, baked/realtime/mixed lighting, light probes, reflection probes, Adaptive Probe Volumes (APV), global illumination, Particle System, VFX Graph, or post-processing effects. Based on Unity 6.3 LTS documentation.
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。
Python engineering skill for implementing, debugging, testing, packaging, typing, reviewing, and refactoring Python applications, scripts, APIs, automation, data processing, CLIs, and libraries. Use for .py files, pyproject.toml, requirements files, pytest, async Python, type hints, packaging, dependency management, and Python performance or reliability work.
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 and analyze engineering experiments or simulations using baseline cases, hypothesis-driven DOE, traceable data processing, defensible plots, uncertainty, and validation. Use for CFD, laboratory data, ML workflows, parameter studies, or research code.
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 a task needs the judgment of an Endoscopy Technician — deciding whether to release or quarantine a scope after a failed leak test or minimum-effective-concentration (MEC) reading, handling a point-of-use treatment delay against the manufacturer's reprocessing window, triaging a borescope finding on a working channel, or troubleshooting equipment and passing accessories during a live GI procedure.
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 a task needs the judgment of a Data Engineer — designing an idempotent pipeline operation so retries and backfills don't corrupt data, choosing event-time over processing-time partitioning for time-series aggregation, enforcing schema compatibility rules before an upstream change propagates downstream, adding automated data quality checks to a pipeline, or deciding between batch and streaming architecture for a specific freshness requirement.
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 a task needs the judgment of a Crematory Operator — running a cremation cycle safely, verifying chain-of-custody and identification before charging a retort, handling implanted-device or oversized-decedent hazards, or documenting and troubleshooting an incident during processing.
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 a task needs the judgment of a court, municipal, or license clerk — checking a pro se filing for procedural completeness, calculating a court filing fee or fee-waiver eligibility, processing a license or permit application against an eligibility checklist, determining whether a case record is public or sealed, or making a docket entry.
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。