「budgets」の検索結果

Direct a claim-driven research experiment project from post-Idea intake through method realization, prioritized evidence collection, Human Gates, and Evidence Freeze. Use for scientific planning, state transitions, queues, budgets, or recovery; not for running code or independently auditing results.

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。

Implement and execute approved research Experiment, Tuning, or Design Cards with reproducible logs, metrics, environment, and artifacts. Use for bounded coding, debugging, and runs; not for changing claims, priorities, budgets, or the Research Spine.

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。

Establish Service Level Objectives (SLO), Service Level Indicators (SLI), and Service Level Agreements (SLA) with error budget tracking, burn rate alerts, and automated reporting using Prometheus and tools like Sloth or Pyrra. Use when defining reliability targets for customer-facing services, balancing feature velocity against system reliability through error budgets, migrating from arbitrary uptime goals to data-driven metrics, or implementing Site Reliability Engineering practices.

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。

Implement circuit breaker logic for agentic tool calls — tracking tool health, transitioning between closed/open/half-open states, reducing task scope when tools fail, routing to alternatives via capability maps, and enforcing failure budgets to prevent error accumulation. Separates orchestration (deciding what to attempt) from execution (calling tools), following the expeditor pattern. Use when building agents that depend on multiple tools with varying reliability, designing fault-tolerant agentic workflows, recovering gracefully from tool outages mid-task, or hardening existing agents against cascading tool failures.

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 asked to implement under non-negotiable constraints: performance budgets, platform limits, legal or API rules. Not for remote, credential, publish, deploy, or irreversible changes.

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 visually validate implementation-agnostic website pages or modules from an approved Design System and confirmed content. Use for Module Design Solutions, Page UI Architecture Maps, media, evidence, page motion budgets, section motion intent, visual-direction images, and direction review before HTML. Do not use to write or review HTML/CSS/JS, run browser implementation QA, plan platform fields, or implement CMS components.

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。

Built by DynG AI for PlatformPilot.ai-style multi-agent systems. Use when designing or reasoning about message-passing agent coordination in ANY language: actor-style mailboxes, select, point-to-point routing, pub/sub, fan-in joins/quorums, ownership handoff, budgets, dead letters, and traces. Trigger words include PlatformPilot, DynG AI, actor model agents, message-passing agents, CSP agents, coordinate agents, multi-agent orchestration, agent runtime, fan-out workers, pub/sub agents, agent barrier, or join.

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。

Run the Upstash CLI (`upstash`) from a terminal, shell script, or CI job when no Upstash MCP tools are in the session. Do not load this skill when Upstash MCP tools are available (the Upstash plugin registers mcp.upstash.com) - they already cover creating, listing, renaming, and deleting Redis databases, running Redis commands, usage stats, backups, Vector and Search indexes, QStash schedules and messages, Blob buckets, and Box, so call them directly. Use this skill for shell work the MCP does not do - a CI step or provisioning script that needs `upstash` commands with JSON output, piping results into other commands, `upstash auth login` and API-key setup, team and member management, changing plans, regions, TLS, eviction, auto-upgrade, or budgets, minting temporary S3 credentials for a Blob bucket, connecting a coding agent to Upstash with `upstash setup` (the Upstash plugin, or the remote MCP server plus skills), or when the user explicitly asks for the CLI or for managing Upstash without the console.

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。

Creates demand generation campaigns, optimizes paid ad spend across LinkedIn, Google, and Meta, develops SEO strategies, and structures partnership programs for Series A+ startups scaling internationally. Use when planning marketing strategy, growth marketing, advertising campaigns, PPC optimization, lead generation, pipeline generation, or startup marketing budgets. Covers multi-channel acquisition (Google Ads, LinkedIn Ads, Meta Ads), CAC analysis, MQL/SQL workflows, attribution modeling, technical SEO, and co-marketing partnerships for hybrid PLG/Sales-Led motions in EU/US/Canada markets.

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。

Manage LLM context budgets—prioritization, summarization, compaction, and what to load vs reference. Use for long sessions, large repos, or multi-doc tasks.

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。

Assess organizational training needs using ADDIE methodology and Kirkpatrick's 4-Level evaluation framework. Maps performance gaps to learning objectives using Bloom's taxonomy. Use when planning L&D budgets, designing training programs, or evaluating training effectiveness.

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Build and maintain a rolling financial forecast using a 12–18 month horizon. Lock actuals, reforecast remaining periods, extend the planning window, and generate a waterfall bridge showing prior-to-new variance. Use monthly or quarterly when the organization follows a continuous planning cadence instead of annual budgets.

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Section-by-section media planning and generation. Image generation (GPT Image 2 primary, built-in fallback), logo/icon generation (Ideogram v3 → favicon set), video generation (Veo 3.1), social preview images (OG 1200x630 + AI search optimization), stock photo curation (Pexels, Pixabay), critique/remix loops (max 3 rounds), asset compression pipeline, and media performance budgets.

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。

AI integration review patterns. Use when reviewing model API calls, prompt construction, LLM output handling, RAG pipelines, and tool-calling code. Covers prompt-injection call-chain tracing, output validation, token budgets, retry/timeout handling, streaming, and key/PII exposure.

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。

AI specification planning frameworks. Use when a spec touches model calls, prompts, retrieval, tool calling, agentic loops, or evals. Covers approach selection, model and provider choice, structured output contracts, loop guards, budgets, failure modes, and eval design.

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。

Record, compose, publish, serve, and review short desktop validation video proofs for Pulp UX/test-harness work. Use when the user asks to "show me it working", record a validation video, prove a click/interaction, share a local proof link, attach a video to a review issue, or compare an implemented UI against source material. Covers macOS desktop capture, Remotion proof composition, attachment budgets, local/Tailscale serving, and review closure.

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。

Audits game assets for compliance with naming conventions, file size budgets, format standards, and pipeline requirements. Identifies orphaned assets, missing references, and standard violations.

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。

Structured performance profiling workflow. Identifies bottlenecks, measures against budgets, and generates optimization recommendations with priority rankings.

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 profiling patterns including ProfilerMarkers, FrameTimingManager, memory profiling, and performance budgets.

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 diagnosing or improving frontend performance, Core Web Vitals, bundle size, runtime rendering cost, network waterfalls, memory leaks, long tasks, Lighthouse findings, or performance budgets; Chinese triggers include performance optimization, page freeze, slow first screen, bundle volume, Web Vitals.

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 DevOps/Site Reliability Engineer — designing deployment pipelines, setting SLOs/error budgets, responding to or reviewing an incident, or making infrastructure/reliability tradeoffs. Distinct from a backend software engineer role — this one owns the system's operational health across all services, not one service's feature 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。

Defines service level objectives, creates error budget policies, designs incident response procedures, develops capacity models, and produces monitoring configurations and automation scripts for production systems. Use when defining SLIs/SLOs, managing error budgets, building reliable systems at scale, incident management, chaos engineering, toil reduction, or capacity planning.

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。

Building defensible grant budgets — personnel, equipment, indirect costs, and justifications reviewers believe.

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。

Create 3D web experiences: scene setup, models, materials, lighting, animation, scroll-driven scenes, and performance budgets. Use when adding 3D to websites beyond basic demos.

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。