데이터·AI 스킬

Analytics Tracking & Measurement Strategy workflow skill. Use this skill when the user needs Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ai-engineer workflow skill. Use this skill when the user needs Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

AI/ML Workflow Bundle workflow skill. Use this skill when the user needs AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Agent Performance Optimization Workflow workflow skill. Use this skill when the user needs Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Agent Performance Optimization Workflow workflow skill. Use this skill when the user needs Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ai-engineer workflow skill. Use this skill when the user needs Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

AI/ML Workflow Bundle workflow skill. Use this skill when the user needs AI and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Advanced Evaluation workflow skill. Use this skill when the user needs This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Advanced Evaluation workflow skill. Use this skill when the user needs This skill should be used when the user asks to "implement LLM-as-judge", "compare model outputs", "create evaluation rubrics", "mitigate evaluation bias", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ADHX - X/Twitter Post Reader workflow skill. Use this skill when the user needs Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser required and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Improve and rewrite user prompts to reduce ambiguity and improve LLM output quality. Use when a user asks to optimize, refine, clarify, or rewrite a prompt for better results, or when the request is about prompt optimization or prompt rewriting.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Recommend basic data structures for a task. Use when a junior developer needs help choosing lists, maps, or sets.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Review database migrations for safety and rollback. Use when a mid-level developer needs validation of schema changes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Draft a basic SQL query from a simple requirement. Use when a junior developer needs help forming SELECT queries.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Review data handling for privacy and retention. Use when a senior developer needs governance validation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Dùng khi cần prompt ảnh thiết kế nhân vật (3 góc toàn thân + cận mặt trong 1 ảnh) cho Midjourney/SD/Flux để giữ nhân vật nhất quán khi làm video AI. Bản Lite.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Dùng khi viết hoặc sửa prompt tạo video/ảnh AI (Veo 3, Google Flow, Kling, Runway, Sora, Midjourney, Hailuo, Luma): từ vựng chuẩn về góc máy, chuyển động camera, ánh sáng, bố cục, phong cách, màu, cảm xúc công thức ghép prompt, và bài học thực chiến về lỗi model AI hay gặp. Use when writing or fixing AI video/image prompts — cinematic camera angles, camera movement, lighting, composition, style, color grading, mood, a prompt formula, and real-world lessons on common AI video model failures.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Dùng khi viết prompt ảnh/video cảnh tiên hiệp, cổ phong, mỹ học phương Đông (thiên cung, biển mây, cung điện, kiếm khách) cho Midjourney/SD/Flux/Veo. Bản Lite.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate navigable semantic maps from PDF documents. Extracts section structure via font analysis, then runs LLM extraction per section for claims, symbols, and dependencies — all page-anchored. Produces _MAP.md (progressive disclosure), .symbols.json (definition index), .anchors.json (claim references), and a _USAGE.md snippet for CLAUDE.md. Use when analyzing papers, specs, or legal docs; when asked to "map this document", "index this PDF", "what does this paper say"; or when a coding agent needs grounded reference material from a PDF source. Analogous to tree-sitting but for prose documents.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Query, filter, and transform Markdown structurally with mq — a jq-like CLI for Markdown. Use to extract headings/sections/code-blocks/links from .md files, build a table of contents, pull code blocks of a given language, slice or reshape LLM prompt/output Markdown, or batch-transform docs. Triggers on "extract sections from this markdown", "get all the code blocks", "jq for markdown", "mq", or any structural query over Markdown that grep/Read can't do cleanly.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

In-process semantic search over text files or in-memory strings, using Gemini embeddings via the CF AI Gateway. Use when user wants fuzzy/conceptual search where exact-keyword grep would miss — "sessions discussing regulatory constraints", "code about retry logic", "notes mentioning burnout even if the word isn't there". Complements searching-codebases (regex/AST) and extracting-keywords (YAKE). Do NOT use when an exact string/regex match is what's wanted — grep/rg wins on speed and precision there.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Execute programs on a compiled transformer stack machine where every instruction fetch and memory read is a parabolic attention head. Demonstrates that transformer attention + FF layers can implement a working computer. Use when user mentions "llm-as-computer", "lac", "stack machine", "compiled transformer", "percepta", "parabolic attention", "execute program", or asks to run/trace programs on the transformer executor.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Assign items to a CLOSED label vocabulary that is too large to put in a prompt — product taxonomies, category hierarchies, tag vocabularies, routing tables, ICD/SIC-style code lists. A cheap model writes the label it thinks the vocabulary would use, and an embedder snaps that writing onto the nearest legal value, so the schema is never transmitted and the output is always in-vocabulary. Use for "classify these into our taxonomy", "tag these against the existing tag list", "map these queries to categories", "the enum is too big to send", or a Literal/enum that hits a provider cap. NOT for a vocabulary that fits in a prompt — structured output measured 0.701 acc@1 there against this pattern's 0.564. NOT for open-ended labelling with no fixed vocabulary, and not for ranked retrieval over documents (bm25).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Distill Opus-level reasoning into optimized instructions for Haiku 5.5 (and Sonnet). Generates explicit, procedural prompts with n-shot examples that maximize smaller model performance on a given task. Use when user says "down-skill", "distill for Haiku", "optimize for Haiku", "make this work on Haiku", "generate Haiku instructions", or needs to delegate a task to a smaller model with high reliability.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.