「ai platform」の検索結果

Reference when designing autonomous agent systems or deciding agent freedom/safety/context management/collaboration infrastructure. 10 design principles distilled from Karpathy autoresearch (autonomous ML experiment loop) + AgentHub (agent-native Git DAG). Triggered by "autoresearch", "agenthub", "ratchet" ("래칫"), "context budget", "dumb platform", "program.md", "overnight", "autonomous experiment" ("자율 실험"), "branchless", "single-file constraint" ("단일 파일 제약"), "fixed time budget" ("고정 시간 예산") keywords.

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Drafts privilege-protective, board-ready executive summary memoranda of internal antitrust investigation findings for US federal law. Covers monopolization, vertical restraints, acquisitions, FTC Act Section 5, tech-platform conduct, risk assessment, and remediation. Use when drafting antitrust investigation summaries, board memos on competition risk, or internal compliance investigation reports.

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Designs and orchestrates a realistic interview simulation platform with voice AI, whiteboard evaluation, gaze-tracking proctoring, and mobile spaced repetition. Use for building mock interview infrastructure, configuring sessions, and adaptive difficulty. Activate on "interview simulator", "mock interview", "practice session", "voice mock". NOT for individual round-type coaching, resume writing, or prep timeline coordination.

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Designs adaptive clinical trials including group-sequential (O'Brien-Fleming, Pocock, Lan-DeMets spending), sample-size re-estimation (blinded Friede-Kieser, unblinded Cui-Hung-Wang, Mehta-Pocock promising zone), seamless Phase 2/3 with treatment-arm selection, population enrichment, and response-adaptive randomisation. Covers FDA 2019 Final Adaptive Designs Guidance, FDA 2022 Master Protocols, and ICH E20 Step 2b/3 draft (June 2025, NOT final). Use when planning interim analyses, sample-size re-estimation, or master/platform-trial designs.

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Guidance for SPR and BLI binding characterization experiments. Use when: (1) Planning binding kinetics experiments, (2) Troubleshooting poor/no binding signal, (3) Interpreting kinetic data artifacts, (4) Choosing between SPR vs BLI platforms.

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Expert security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).

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Extract product data, prices, reviews, and seller information from any e-commerce platform using Apify's E-commerce Scraping Tool.

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xAI Grok Imagine API integration for image generation, text-to-video, image-to-video, and editing via natural language. Use when you need to generate images or videos from text prompts, edit existing images, animate static images into videos, or edit existing videos with natural language instructions. Supports conversational generation across messaging platforms with async polling, progress updates, and automatic delivery.

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Plataforma autônoma de agentes de IA para construir e implantar agentes contínuos. Use ao criar agentes de workflow visual, implantar agentes autônomos persistentes ou construir sistemas complexos de automação de IA com múltiplas etapas.

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[Workflow] Use when activating the Idea-to-Spec workflow — turn a raw idea/vision/problem into ONE canonical (provisional) Feature Spec. STOPS at the reviewed spec; chain workflow-spec-to-pbi for a backlog. For code→spec use workflow-code-to-spec.

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[Workflow] Use when activating the Integration Test Green workflow — drive an integration-test suite to fully green with a bounded convergence loop: verify the whole system (or the named target), adjudicate every failure with /debug-investigate + /integration-test-review before any edit, fix at the owning layer, /changes-review each round's fix diff, re-verify from scratch, then sync spec TCs, the integration-test reference doc, and feature docs.

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[Code Quality] Use when you need to combine /why-review + /fix in a recursive loop — each round runs /why-review to find validated findings then /fix to resolve them, then loops again over the CHANGED target until a fresh full /why-review produces zero findings (nothing left to fix).

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[AI & Tools] Use when you need to apply structured, reflective problem-solving for complex tasks requiring multi-step analysis, revision capability, and hypothesis verification.

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[Content] Use when you need to build marketing strategy: positioning, channels, messaging, campaigns, budget, KPIs.

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[Project Management] Use when you need to enforce quality gates, verify compliance with standards, track quality metrics, and generate audit trails.

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[Code Quality] Use when you need to prove fix correctness with adversarial code proof traces — a skeptic tries to DISPROVE the fix and trace all related paths first, with confidence scoring and stack-trace-style evidence chains, so confidence is earned by surviving attack, not by confirming it works.

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[Debugging] Use when analyzing or optimizing performance bottlenecks: database queries, N+1 fan-out, indexing, API latency, memory/GC, concurrency and pool saturation, algorithmic complexity (O(n²)), network/protocol round trips, frontend rendering and Core Web Vitals, caching, and distributed/resilience paths. Calibration constants and domain laws (latency ladder, Little's Law, utilization knee, CWV thresholds, symptom→cause triage) live in references/performance-knowledge.md.

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[Utilities] Use when applying structured problem-solving frameworks to complex, blocked, recurring, or uncertain decisions.

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[Skill Management] Use when enhancing, compressing, or expanding prompts, docs, or skills with attention anchoring [INTELLIGENT ROUTING]. Flag: --op={compress|expand|enhance} (default enhance); --op=compress strips token bloat, --op=expand reconstructs compressed text.

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[Utilities] Use when a project needs to add, change, list, or remove its OWN protocol rules layered on top of a framework skill — a named overlay of extra project rules that applies whenever the targeted skill runs, stored with the project rather than in the portable framework. `/project-skill-protocol list` prints every overlay with its target and description; `add` drafts a new overlay and confirms it before writing; `update` applies a surgical change; `delete` removes it. Overlays are ADDITIVE ONLY — they never replace, override, or waive anything the skill already does. Triggers: skill protocol, project protocol, custom protocol for skill, extend a skill, overlay rules, add rules to a skill, project rules for skills, skill protocol overlay.

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[Code Quality] Use when you need an AI-assisted Dev BA PIC review of PBI drafts.

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[Planning] Use when you need intelligent plan creation with prompt enhancement. Flag: --mode={ci|cro} (default none — standard planning); --mode=ci plans a fix from a GitHub Actions CI run/log, --mode=cro plans conversion-rate optimization (25-item CRO framework).

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[Planning] Use when you need to start a new project from scratch with full waterfall inception — idea, research, domain modeling, tech stack, and implementation plan.

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[Code Quality] Use when you need to combine /changes-review + /fix in a recursive loop — each round runs /changes-review (report-only) to surface validated findings over a fixed diff scope, then /fix to resolve them, then loops again with a FRESH full /changes-review over the CHANGED diff until one complete pass produces zero validated findings (nothing left to fix).

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。