'cohere' 검색 결과

Use when reviewing or auditing a library of Claude Code skills, agents, slash commands, and workflows — frontmatter correctness, routing quality, tool allowlists, command arg-hints, workflow meta/phase coherence, cross-reference coherence, single-responsibility, file structure, and anti-pattern detection. Triggers on mentions of "review skills", "audit agents", "skill library", "agent definition review", "review this command", "review this workflow", "is this skill right", or when iterating on `.claude/skills/`, `.claude/agents/`, `.claude/commands/`, or `.claude/workflows/` directories. For code review of source code see code-review-and-quality.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Protocol for auditing API surface coherence and type safety. Trigger when: - Evaluating API designs, interface type safety, or design elegance. - Prompt contains: /api-audit, API surface, API coherence, type safety.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Goal-directed review of git history for change coherence. Trigger when: - Analyzing project history, reviewing diffs, or checking commit messages for alignment. - Prompt contains: /git-review, git history, commit log, change coherence.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

PR 작성 전이나 큰 수정 후에 자신의 변경을 목표에 필요한 최소 범위로 정리합니다. 중복 설계와 테스트를 검토하고 필요한 동작을 유지하면서 변경량을 줄입니다.

• PR 작성 전 변경 내용 정리
• 큰 수정 후 중복 설계 줄이기
• 구체적인 결함을 잡는 테스트 유지

음악 영상과 짧은 영상의 색·빛·움직임 및 박자에 맞춘 컷을 설계하고, angelcore와 hyperpop 방향에 따라 생성 소재와 편집을 정리합니다.

• 음악 영상의 표현 방향을 정합니다
• AI 생성 보조 영상의 분위기를 통일합니다
• 곡의 박자에 맞는 컷을 설계합니다

후보 탐색과 비교를 반복하며 근거와 판단을 추가 기록 방식의 장부에 남깁니다. 이전 결과와의 일관성과 재검증 결과를 확인하고 실거래나 운영 작업의 실행 조건을 명확히 합니다.

• 여러 차례 시도하며 후보를 비교할 때
• 판단의 근거를 기록할 때
• 새 정보로 이전 채택 후보를 재평가할 때

대량 데이터 수집, 과거 데이터 보충, 변환, 동기화의 지연을 단계별로 조사합니다. 처리 방식을 비교해 속도를 높이고 행 수, 파일 수, 시각의 일치 여부를 확인합니다.

• 대량 데이터 수집과 내보내기 가속
• 과거 데이터 보충 시간 단축
• 배치 크기와 병렬 작업 수 비교

정리되지 않은 스타트업 발표 자료를 의사 결정에 필요한 내용과 근거가 드러나는 HTML 슬라이드로 구성하고, 파스텔과 네온 색면 및 굵은 검은 테두리로 디자인을 통일합니다.

• 이사회 발표 자료 정리
• 제작사 프로젝트 실적 소개
• 브랜드 개편안 검토

Compare an implementation with its OpenSpec specifications, tasks, and design decisions before archiving the change. Get a report on completion, requirement coverage, and consistency, with prioritized issues, actionable recommendations, and explicit limits where evidence is missing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check for unfinished tasks before archiving a change
• Find gaps between specifications and implementation
• Review scenario tests and adherence to design decisions

Revise an existing OpenSpec change plan and reconcile related planning documents. Incorporate new decisions, identify contradictions or gaps, and apply proposed document edits after confirmation, while leaving implementation code untouched.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Incorporating new decisions into an existing change plan
• Checking planning documents for contradictions
• Reconciling related documents after an edit

Research a topic across multiple sources and turn the findings into a readable report. The skill coordinates separate research agents to compare options, examine markets or trends, and synthesize literature into a coherent narrative.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing products or services
• Researching markets and industry trends
• Reviewing studies on a topic

Design practice lessons around learners’ actual attempts, using the zone of proximal development: learning supported by a teacher or experienced peer. Plan targeted help, fresh independent tasks, and evidence-based next steps, or run a single practice cycle in chat.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing a lesson that connects assessment and practice
• Offering hints based on a learner’s actual answer
• Checking independent performance after removing hints

Create a consistent company story for employees, investors, customers, candidates, and partners. Shape the same facts for each audience, check messages for contradictions, and prepare company updates or crisis communications.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Aligning investor updates with employee communications
• Preparing a company-wide meeting
• Checking recruiting messages against company reality

Structure board presentations and investor updates using financial, sales, product, and people perspectives. Turn supplied metrics into a coherent account of progress, explain missed targets, and make decisions and requests explicit, with placeholders for missing figures.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing a quarterly board presentation
• Drafting a monthly investor update
• Structuring a fundraising narrative

Review an OpenSpec implementation against its specifications, tasks, and design decisions. The skill checks for missing work, uncovered scenarios, and inconsistencies, then produces a prioritized report with concrete recommendations and code references where available.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review an implementation before archiving
• Find incomplete tasks and missing requirement implementations
• Check whether scenarios have implementation and test coverage

Develop independent solutions to a defined problem, compare them against shared requirements, and combine useful contributions into a coherent recommendation. An independent assessment and evidence checks support the selection, while unresolved tradeoffs and verification needs remain explicit.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing concrete solutions to a defined problem
• Developing rough options before choosing an approach
• Comparing architectural or product proposals

Helps design semantic search and RAG, where an AI answers using retrieved documents. Covers embeddings, numerical representations of content, plus document splitting, search indexes, keyword search combinations, and evaluation of retrieval quality.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Design document retrieval for AI answers
• Compare embedding models and document splitting strategies
• Combine semantic search with keyword search

Turn ePub books into training examples for models that reproduce an author's writing style. Covers text extraction, coherent segmentation, varied instructions, model training, and checks for copied phrases and style transfer to new scenarios.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build training datasets from ePub books
• Train a model on an author's writing style
• Check for copied phrases in generated prose

Review Agent-Native Research Artifacts, structured research packages for agents, across six dimensions of research quality. Produce a JSON report with scores, strengths, severity-ranked findings, practical improvements, and an overall acceptance or rejection recommendation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing an ARA before publication
• Checking whether evidence supports research claims
• Assessing experimental methods and research records

Design and implement RAG systems, which retrieve documents to inform AI answers. Get document preparation strategies, vector database comparisons, combined keyword and meaning-based search, result reranking, and an evaluation plan for retrieval quality.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Design an AI application that answers using internal documents
• Compare vector databases and document splitting strategies
• Improve search through keyword matching and result reranking

Turn books, transcripts, courses, and interviews into reusable agent skills. Extract practical frameworks and procedures, verify their source support, test representative tasks, and compile the results into a single entry or a skill pack.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning a book's methods into reusable agent skills
• Extracting practical procedures from course or podcast transcripts
• Creating a single entry for studying and consulting source material

Create static technical drawings from object descriptions, photographs, or CAD models. Produce consistent views that explain shape or assembly, plus a viewer with zoom, editable colors, and downloads in SVG, PNG, and PDF formats.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating an exploded view to explain an assembly
• Drawing aligned views from supplied dimensions
• Illustrating an object's shape from photographs

Research an unfamiliar topic or turn a collection of sources into structured notes, a reference article, or a publish-ready draft. The workflow connects sections to evidence, makes conflicting claims visible, and guides revision before publication.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Research an unfamiliar field using primary sources
• Compile supplied materials into a coherent article
• Build reference notes without drafting an article