949 件 ・ 関連度順
概要と使いどころ
Optimize construction site logistics including material delivery scheduling, crane positioning, storage area allocation, and traffic flow using operations research and simulation.
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Push records from apps, services, devices, or scripts directly into Unity Catalog Delta tables with Zerobus Ingest: SDKs (Python, TypeScript, Go, Java, Rust, C++, .NET), REST, OTLP, MQTT, Arrow Flight, or Apache Kafka-compatible producer APIs, with no message bus to run. Use to stream events, telemetry, logs, IoT data, CDC, or columnar batches into Databricks in near real time; connect existing collectors and log shippers (OpenTelemetry, Debezium, Vector, Telegraf, Cribl); replace a message bus that only feeds the lakehouse; or debug Zerobus auth, schema, throughput, or delivery issues.
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Audit Value Delivery compliance after PR push
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Coach workers, employees, and individual contributors to turn meetings, transcripts, minutes, and work notes into better execution: infer leader expectations, diagnose previous work, identify next actions, judge delivery readiness, and prepare a high-bandwidth update. Use after meetings, during work, before reviews, or across repeated low-value discussions. Perform semantic review from source evidence.
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Use when implementing Kafka, RabbitMQ, Pulsar, or JMS producers and consumers in Spring Boot 3. Covers event contracts, idempotency, retries, dead-letter handling, ordering, and outbox delivery.
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Use when implementing Kafka, RabbitMQ, Pulsar, or JMS producers and consumers in Spring Boot 4. Covers modular starters, event contracts, idempotency, retries, dead letters, and outbox delivery.
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Architectural visualization in Blender for interiors/exteriors with real-world scale, camera composition, PBR materials, and still/animation delivery via MCP.
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Blender compositor workflows for beauty stacks, render passes, color grade, glare, and delivery outputs via MCP.
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。
Review whether a repository's coding-agent harness can reliably carry work from intent through controlled execution, verification, delivery, and learning. Use when asked to assess agent readiness, repeated agent failures, Rules/Skills/Hooks/Memory effectiveness, missing validation or recovery loops, or whether a harness repair improved later outcomes. Do not use for code-only audits, AGENTS-only audits, individual skill reliability reviews, or executing the task itself.
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Turn a narration line, knowledge point, opinion, story beat, or abstract concept into a Seedance 2.0 editorial paper-collage clip with a clear visual metaphor, approved final composition, tactile stop-motion assembly, controlled paper texture, purposeful depth, and synchronized collage sound effects. Use for 4–15 second explainer or B-roll clips; not for realistic presenter ads or editable-layer delivery.
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Break a trusted implementation plan (or other provided context) into independently-grabbable, atomic work items, written to a single work-items.md file. Use when the user wants to convert a plan into work items, create implementation tickets or tasks, divide a plan into work units, or break the plan down into grabbable pieces. Do not use when there is no implementation plan yet or the plan is not yet trusted — use plan-implementation to produce the plan or iterative-plan-review to harden it first. Does not sequence work into demoable delivery phases — use plan-a-phased-build for that. Does not write code — use tdd to implement a work item.
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Designs the contract for an API change inside one codebase — a component's props, a function surface, URL or query parameters, an event payload, or a module boundary — through a discovery pass, an options document with one recommendation, a question round, and an adversarial validation round, with every element of the contract justified from one stated goal. Use when you want to design, shape, decide, or nail down an interface, contract, signature, or API change for a capability you can already describe, sized for roughly one pull request. Produces a design document and changes no code. Does not specify what a feature should do — use plan-a-feature. Does not plan delivery or sequencing — use plan-implementation. Does not assess the architecture of existing code — use architectural-analysis. Does not write the code — use tdd. Does not restructure existing code — use refactor. Runs its rounds without pausing for review; to review each round as it lands, use pairing.
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Apply the bioengineering, mechanobiology, and lymphatic transport reasoning of J. Brandon Dixon, professor of mechanical and biomedical engineering at Georgia Institute of Technology. Reach for this skill whenever analyzing lymphatic biomechanics, active vessel contractility versus passive drainage, peristaltic fluid transport, microfluidic organ-on-a-chip design, preclinical lymphedema models, non-invasive functional imaging, targeted nanomedicine delivery, or automated disease staging. Use this skill to critique bioengineering assumptions, guide quantitative protocol design, evaluate biomechanical pump failure, and formulate interdisciplinary biomedical solutions.
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Build supplier performance scorecards with KPIs, quality metrics, delivery performance, cost management, and improvement plans
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Use when the user asks to take a feature or bug fix from prompt to implementation, especially prompts like "/create a new feature", "build this feature end-to-end", "take this from plan to PR", or "own this change through validation and handoff". This skill is for repo-local delivery workflows that must create and maintain implementation plans, choose appropriate tests, run deterministic validation, open a draft PR against main, and return the preview deployment URL when one is available.
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Use when operating, debugging, deploying, or monitoring a Telegram bot or Telegram-to-agent gateway. Triggers on "telegram bot down", "bot not responding", "debug bot", "check webhook", "polling vs webhook", "restart bot", "deploy bot", "bot logs", "agent gateway", "Telegram Bot API error", "send test message", "бот не отвечает", "проверь бота", "логи бота", "перезапусти бота". Covers health checks, logs, webhook/polling diagnostics, environment validation, safe restart/deploy checklists, Bot API smoke tests, forum topic delivery, privacy mode, gateway routing, and incident notes.
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Set up a continuous integration and continuous delivery (CI/CD) pipeline for a software project, automating builds, tests, and deployments across environments. Use when the user requests ci cd or provides relevant inputs for this workflow.
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Think and work like an expert Anesthesiologist. Use when a task calls for Anesthesiologist judgment. Reasons from control of consciousness, analgesia, autonomic response, and oxygen delivery through the ASA Difficult Airway Algorithm, capnography and arterial-waveform trends, quantitative TOF monitoring, and ASRA/ERAS protocols while treating cannot-ventilate airways, local anesthetic systemic toxicity, malignant hyperthermia, and residual neuromuscular blockade as first-class failure modes.
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Produce speech and clone voices with Fish Audio — its hosted TTS API (S2.1-Pro / S2-Pro / S1 model lineup, REST + WebSocket streaming, instant and persistent voice cloning) and its open-weight OpenAudio S1-mini / Fish-Speech models for self-hosting. Use this skill when an agent must generate narration or dialogue through Fish Audio, choose between Fish Audio's hosted models and open weights, clone a voice from reference audio, author emotion/tone/special markers for expressive delivery, estimate cost from UTF-8 bytes, wire real-time streaming for a voice agent, decide whether self-hosting beats the API, or review Fish Audio TTS output for production. Do not use it to pick a different provider — it covers Fish Audio specifically.
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 Resemble AI Chatterbox for text-to-speech and voice-cloning workflows, including local open-weight Chatterbox, Chatterbox Multilingual, Chatterbox Turbo, and Resemble-hosted Chatterbox API routes. Apply when an agent must choose a Chatterbox variant, prepare reference-voice inputs, control emotion/paralinguistic delivery, plan multilingual TTS, handle PerTh watermarking, or make production decisions about consent, privacy, licensing, latency, and audio QA.
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Use when enhancing, upscaling, restoring, denoising, sharpening, deinterlacing, stabilizing, motion-deblurring, colorizing, SDR-to-HDR converting, or frame-rate/slow-motion converting video (and secondarily images) with Topaz Labs — whether cleaning up AI-generated video, compressed UGC, or old archival footage, or building a generate-low-res-then-upscale delivery pipeline. Covers choosing the right named Topaz model for a specific footage problem, setting parameters, driving the Topaz Platform (Video/Image) REST API's async job lifecycle, judging when enhancement helps versus when it introduces artifacts (over-smoothing, temporal shimmer, face hallucination), and QA of enhanced output. Do not use for originating new video content, non-Topaz upscalers, or purely editorial cuts.
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Produce and operate Amazon Nova Reel video-generation jobs through Amazon Bedrock. Use for Nova Reel text-to-video, image-conditioned animation, automated or manual multi-shot storyboards, async S3 delivery, cost and approval gates, production continuity, output custody, and AWS-specific safety, privacy, IAM, and provenance decisions.
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Direct and operate Luma Ray video generation through the current Luma Agents API and distinguish it from the consumer Luma App and legacy Dream Machine API. Use for Ray 3.2 text/image/multi-keyframe video, edits, extends, reframes, HDR/EXR, pricing and approvals, async delivery, migration, rights, privacy, and production QA.
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Plan and direct Midjourney Video V1 image-to-video work through the official website or Discord, with human operator handoff, motion prompts, start/end frames, loops, extensions, resolution and batch budgeting, privacy, rights, safety, and delivery QA. Use when creating Midjourney videos or when determining whether a requested API, automation, plan, or production workflow is supported.
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。