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模型评估全流程。覆盖分类/回归/排序/生成/RAG/LLM 评估、A/B 测试、 在线监控、数据漂移检测、评估集构建、基准测试。 触发关键词：评估、指标、Precision、Recall、F1、AUC、BLEU、ROUGE、 A/B 测试、基准测试、数据漂移、模型监控、RAGAS、LLM-as-Judge。

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Audit websites and landing pages for conversion issues and design evidence-based A/B tests. Use when the user mentions "landing page isn't converting", "conversion rate", "A/B test", "why visitors leave", or "objection handling". Covers funnel mapping, persuasion assets, and objection/counter-objection frameworks. For overall marketing strategy, see one-page-marketing. For usability issues, see ux-heuristics.

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Self-learning SEO content pipeline: dashboard, multi-agent queue, token budgets, research → write → audit → publish. StoryBrand/Cialdini/JTBD-style frameworks; config-driven. Use for content factory, batch articles, or scaled publishing.

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。

Ultimate UI/UX design intelligence: an Anti-Slop layer that kills AI tells (em-dash, AI purple glow, generic names, template layouts), tunable Design Dials (variance/motion/density) and Style Modes (functional, minimalist, brutalist, soft-premium, marketing), 161 industry color palettes in a shadcn-aligned semantic token schema, 48 UX Laws, 37 Design Tests, UX Heuristics (Nielsen + Krug), Harvester extraction, Figma & Google Stitch integration, MCP server, Component Generator, and BM25 search across 17 domains + 19 framework stacks. One command = complete design system. Use when designing or reviewing UI/UX, choosing colors/typography, fixing generic AI-looking designs, or building Web App / SaaS / Mobile screens.

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。

Google App Script form-to-sheet integration with auto-retry, toast notifications, and Zalo/contact fallback. Reusable across any static website.

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。

Extract reusable templates from PowerPoint presentations into the template library

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Inspect repository session replay and verify configured MetaHarness field memory boundaries before reusing outcomes.

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Use Agent Media when an agent needs to create captioned vertical UGC videos, narrated b-roll overlays, reusable characters, images, and voice through a hosted MCP server and companion skills.

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。

Give Claude Code, Codex, Cursor, ChatGPT and other MCP clients 1,000+ apps and 400+ expert-built Skills through one reusable Aident Loadout setup, with credentials kept in Aident Vault and every action recorded in Audit.

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Turn an existing coding agent into a supervised local work assistant that connects to workplace tools, reusable skills, workflows, and scheduled loops.

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。

Convert a book or long document into a reusable AI mentor with source-grounded lessons, guided practice, citations, and persistent learning records.

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。

Orchestrates AWS data pipelines using @aws-sdk/client-s3 and @aws-sdk/client-sqs. Manages S3 object lifecycle with PutObjectCommand/GetObjectCommand, processes SQS message queues via ReceiveMessageCommand with long polling, and configures S3 event notifications to SQS for event-driven 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 REUSE when an agent needs file-level licensing clarity instead of guessing from a single top-level LICENSE file. The agent checks compliance, adds or verifies SPDX headers, pulls missing license texts into LICENSES/, and produces a concrete remediation list or SPDX export.

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Separates audio tracks into individual stems (vocals, drums, bass, other) using Meta's Demucs neural network model via the demucs Python package. Supports batch processing of WAV and MP3 files, outputs isolated stems in FLAC or WAV format, and integrates with FFmpeg for format conversion and loudness matching post-separation.

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Deploys custom Apify Actors via the Apify API v2 for large-scale web crawling using CrawleeJS. Leverages Apify dataset storage, RequestQueue, and proxy configuration for distributed scraping at scale.

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。

Deploys intelligent web scraping actors on the Apify platform using the Apify SDK with RequestQueue and Dataset APIs. Handles dynamic content via Apify CheerioCrawler and PlaywrightCrawler with automatic scaling.

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。

Download a supported video URL with yt-dlp and upload the preserved file plus metadata to archive.org as a repeatable preservation job.

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。

Builds Apify Actors for scalable cloud scraping with automatic proxy management and storage. Uses the Apify SDK (Actor, Dataset, KeyValueStore, RequestQueue) and Crawlee library for robust crawling.

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Processes real-time event streams using KafkaJS consumer groups and transforms messages with configurable schemas. Handles partition rebalancing, offset commits, and dead-letter queue routing for failed transformations.

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Study a merged or shipped tdmcp implementation and extract reusable learnings: code improvements, runtime/UX lessons, test gaps, docs updates, roadmap items, and harness changes. Use when the user asks to learn from a completed feature/project/PR/build, analyze what can be improved from an implementation, or turn a real installation experience into actionable tdmcp improvements. This is a post-implementation learning harness; it does not replace tdmcp-pipeline for building or tdmcp-quality-audit for broad repo audits.

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。

Turn vulnerability notes, disclosure reports, PoCs, source code, or Codex Security findings into self-contained, sceptically validated, natural-sounding vulnerability reports. Use for one vulnerability or a disclosure campaign; a Codex Security scan is optional.

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 the user wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.

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 the user says 'save this as a template', 'create a playbook from this page', 'capture this layout', or has hand-built the same page type three times. Captures canonical page patterns as reusable playbooks that later page generation can spawn from in seconds.

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。

Extracts reusable patterns from sessions. Use at session end to capture debugging insights and project-specific knowledge.

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。