「serving」の検索結果

Use when a task needs the judgment of a Business Teacher, Postsecondary — grading case analysis on the rigor of business reasoning rather than matching a single "correct" answer, updating stale textbook examples against current market conditions rather than teaching them as still-current, distinguishing taught analytical frameworks from personal business opinion presented as universal fact, and preserving the incomplete-information trade-offs of real business decisions rather than simplifying problems into false certainty.

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Audit an existing Lamport-style hierarchical mathematical proof forward for validity and whether its hierarchy, scope, dependencies, side conditions, and proof constructs discharge the stated theorem. Use when the central question concerns a top-down proof with numbered levels, subproofs, ASSUME/PROVE, SUFFICES, PICK, CASE, DEFINE, Q.E.D., or prose equivalents. For an ordinary proof that first needs source-preserving hierarchy, use convert-lamport; for conclusion-first AND/OR obligation reconstruction, use reverse-lamport. Do not use to generate or replace a proof, or to audit Lean, Coq, Isabelle, or other proof-assistant source.

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Rebases a feature branch onto its latest base, resolving conflicts while preserving the intent of local changes, optionally force-pushing and watching CI afterward. TRIGGER when: the user wants to rebase a feature branch, update a branch against its base, or replay local work on top of the latest upstream. DO NOT TRIGGER when: merging a release branch into dev → merging-branches; only watching CI on an already-open PR → monitoring-pull-requests.

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High-throughput inference on FriendliAI — optimized serving engine for low-latency, cost-efficient LLMs.

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Translating documents while preserving layout, tables, and formatting — use for multilingual document workflows.

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Audit manufacturing predictive maintenance systems for OPC-UA/MQTT sensor data pipelines, time-series storage retention, ML model lifecycle (training-serving skew, drift detection, retraining triggers), MTBF/MTTF/MTTR reliability calculations, Weibull survival analysis.

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Audits and implements mandatory image resizing and compression for all uploaded user images to reduce storage costs while preserving visual quality.

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Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..

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Transform reference photographs and visually dense images into sparse, recognizable, high-saturation flat-vector-style illustrations through semantic compression rather than literal tracing. Use when the user asks for photo-to-flat illustration, photo-to-vector-style redraw, 照片转扁平插画, 无渐变高饱和插画, iconification, visual simplification, composition-preserving abstraction, a consistent minimal illustration set, or revisions that remove gradients, glow, texture, blur, clutter, text, logos, numbers, or UI. Default to human-perceived semantic complexity 6 out of 10 or lower, fixed-HSB solid fills, crisp boundaries, and no gradients or light-halo effects.

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Judges whether a user's input suits the Vibe Creating style of video-prompt writing, and when it does, distills single-scene prompts, multi-shot descriptions, emotional imagery, or mixed input into prompts that are easier for a video model to generate from — while preserving any user-specified dialogue, voiceover, music, sound effects, and other hard constraints. Use when a user wants to turn an idea, story, feeling, or rough/over-specified prompt into a strong text-to-video prompt (Seedance, Sora, Kling, Veo, Runway, etc.), or asks to "rewrite", "improve", "clean up", or "vibe-ify" a video prompt. Do NOT use for long narrative films that need precise word-for-word dialogue sync, industrial shot lists meant to be executed verbatim, or functional/UI demos and step-by-step tutorials.

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Validate Claude Ads contracts, scoring inputs, run bundles, capabilities, source freshness, safety, installation, uninstall, or release readiness. Use for ads validate, ads status, ads next, stale claims with missing tool access, maturity checks, ownership-manifest uninstall, preserving unrelated ads-* skills, checksum verification, preflight, QA, or release audits. Missing access must demote stale evidence for the run and block dependent release-current claims before recovery guidance.

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Edit academic prose in LaTeX manuscripts or supplied text at light, moderate, or strict intensity. Improve grammar and clarity while preserving scientific claims, uncertainty, numbers, citations, and LaTeX structure.

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Reformat LaTeX papers for a specified venue, year, track, and submission stage. Apply official templates and check layout, bibliography, page limits, and anonymization while preserving scientific content.

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Restructure code while preserving behavior. Use for extraction, consolidation, ownership moves, or cleanup where verification must bracket structural edits.

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Discovers requirements and designs a borderless open data lakehouse using Lakehouse for Apache Iceberg and BigQuery data agents. Use when architecting multi-cloud storage infrastructure (Cloud Storage, AWS S3, Azure Blob), establishing ingestion and AI serving subsystems, configuring Cross-Cloud Interconnect, or deploying Gemini Enterprise Agent Platform and BigQuery data agents. Don't use for single-cloud data warehouses, or when the focus is on Knowledge Catalog metadata governance and Spark-driven IDE analytics workflows (use google-cloud-solution-agentic-analytics-spark-knowledge-catalog instead).

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Provides guidance and instructions on managing remote devices on Developer Device Platform (DDP). Use when reserving remote Android devices, establishing connection tunnels, checking session status, or extending/cancelling leases. Don't use for iOS or local device/hardware inquiries.

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Agent Platform Model Tuning. Use when you need to fine-tune open models or Gemini models using Agent Platform infrastructure. Don't use for model training outside Agent Platform, model deployment to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).

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Manages GenAI tuning jobs in Agent Platform. Use this to list, get, or cancel ongoing model tuning jobs. Don't use for fine-tuning models (use `agent-platform-tuning`), deploying models to endpoints (use `agent-platform-deploy`), or managing serving endpoints (use `agent-platform-endpoint-management`).

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Ultra-compressed code review comments. Cuts noise from PR feedback while preserving the actionable signal. Each comment is one line: location, problem, fix. Use when user says "review this PR", "code review", "review the diff", "/review", or invokes /caveman-review. Auto-triggers when reviewing pull requests.

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Ultra-compressed commit message generator. Cuts noise from commit messages while preserving intent and reasoning. Conventional Commits format. Subject ≤50 chars, body only when "why" isn't obvious. Use when user says "write a commit", "commit message", "generate commit", "/commit", or invokes /caveman-commit. Auto-triggers when staging changes.

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Rename Pharo methods safely through Genie's `rename_method` MCP refactoring tool. Use when a selector should be renamed while preserving behavior, updating senders and symbol references across the live image, including as one step in larger refactorings such as clarify API names, split responsibilities, or move behavior behind better messages.

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Detects over-broad permission requests where a narrower permission or privacy-preserving alternative API is sufficient, violating Guideline 5.1.1(iii) data minimization requirements.

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Integrate PocketBase as a Go library using the github.com/castle-x/goutils/pocketbase (gopb) package to build single-binary full-stack applications. Use when building Go applications that need user authentication, embedding PocketBase into Go binary, registering custom API routes, managing default users, serving embedded SPA frontend, or deploying single-binary applications. NOT for using PocketBase as a standalone separate process.

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This skill provides guidance for implementing Go Embedded SPA architecture - embedding React/Vue/TSX frontend static resources into Go binary using go:embed directive. Use this skill when building self-contained single-binary applications, implementing SPA with Go backend, setting up cross-platform deployable full-stack projects, or configuring static file serving with Go standard library net/http.

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