'open source' 검색 결과

Python으로 재무 모델 Excel 파일을 만들고 입력값·수식·참조를 색으로 구분합니다. 출처 주석과 일관성 검사를 더해 다른 사람이 검증하기 쉽게 정리합니다.

• 출처를 추적할 수 있는 재무 모델 작성
• 가정별 기업 가치 비교
• 다른 사람이 검토할 Excel 파일 준비

browser-use 참고 자료를 바탕으로 Python 브라우저 자동화 구현을 돕습니다. 설치, 에이전트와 브라우저 설정, 도구 추가, 실행 모니터링과 비용 추적을 다룹니다.

• Python으로 브라우저 작업을 자동화합니다
• 에이전트와 브라우저 인증을 설정합니다
• 사용자 정의 도구와 실행 훅을 추가합니다

로컬 데이터나 연결된 서비스를 바탕으로 나중에 데이터를 갱신할 수 있는 HTML 대시보드와 보고서를 만듭니다. 출처, 수집 시각과 가공 내용도 기록해 수치의 근거를 확인할 수 있습니다.

• 데이터를 갱신할 수 있는 대시보드 제작
• 출처를 확인할 수 있는 보고서 작성
• 연결된 서비스의 상태 페이지 제작

Run protein structure prediction, molecular design, and docking tools on Tamarind Bio without a local GPU. Guides tool selection, input validation, job submission, batch processing, and result retrieval through its REST API or MCP server.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Predicting protein structures in the cloud
• Running binder or antibody design tools
• Submitting batches of sequences for analysis

Compare C# Web API source code with its TypeScript or JavaScript clients to find mismatched data fields, required inputs, and response handling. Receive an audit report showing client impact, severity, and confidence in each match.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check client impact before merging a DTO or controller change
• Audit API compatibility before a release
• Find stale request fields and missing response fields

Investigate domains, IP addresses, and certificates linked to suspected attackers using public sources. This skill guides passive research and relationship mapping to support phishing investigations, external exposure reviews, and threat intelligence reports.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating infrastructure linked to a phishing campaign
• Adding public evidence to threat actor profiles
• Reviewing an organization's external exposure

Plan and configure large language model training with OpenRLHF to better match human preferences. Covers training method selection, distributed GPU setup, inference acceleration with vLLM, and troubleshooting memory or training stability issues.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing a method for training models on human preferences
• Setting up PPO training with a reward model
• Configuring GRPO training without a critic model

Search the web, news, and financial information from several angles, then read relevant pages when more detail is needed. Use the findings to answer current questions, compare options, or check claims with source links.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking recent news and developments
• Finding evidence for or against a claim
• Comparing two options using multiple sources

Investigate a topic through multiple sources, including primary evidence and counterarguments. Save research materials and notes to files, compare conflicting findings, and produce a cited report that explains conclusions, uncertainty, and limits of the evidence.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check the evidence behind a claim
• Review research papers on a topic
• Compare conflicting sources and findings

Find projects, skills, agents, and tools in the Kortix catalog, then adapt their files to an existing project. The skill guides source inspection, configuration merging, and preparation of a change request for user review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find skills and tools in the Kortix catalog
• Import selected parts of a ready-made project
• Adapt an external agent to an existing project

Understand a public GitHub repository through GitDiagram's architecture overview. Get an explanation of its main components, source paths, and connections, plus Mermaid diagram source and an interactive diagram for exploring the code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Getting an overview of an unfamiliar public repository
• Finding source paths for major components
• Understanding connections and data flow

Guide large language model training with OpenRLHF using human preference feedback. Covers training method selection, distributed GPU setup, reward model training, and memory tuning, with examples for PPO, GRPO, and DPO.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing a training method for human preference alignment
• Setting up distributed training across multiple GPUs
• Training a reward model before PPO

Add documents, interview notes, or observations to an open investigation. Process batches against documented selection criteria, surface significant items, and log everything reviewed so the team can verify coverage and update its source checklist.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add interview notes to an open investigation
• Process a newly received batch of documents
• Add an email export to an investigation

Gather business context before analysis by checking connected or provided sources for metric definitions, recent changes, and decision background. Produce a focused context note that preserves source references, conflicting evidence, assumptions, and remaining gaps.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clarifying metric definitions before analysis
• Checking recent changes before investigating performance
• Reconciling conflicting sources before writing a report

Find GitHub projects using keywords, minimum stars, and update dates, then collect repository details and contributor profiles through BrowserAct. Results include project descriptions, contributor biographies, personal websites, and Twitter handles for research, recruiting, or collaboration scouting.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Discover open-source projects in a specific field
• Collect developer profiles for recruiting
• Find potential collaborators and sponsors

Guide a bug bounty investigation from scope checks and asset discovery to vulnerability testing, impact validation, and report writing. Covers web applications, source code, and AI features, with an emphasis on reproducible evidence of real harm.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning an investigation for a new bug bounty target
• Reviewing source code for risky implementation patterns
• Testing web and AI features for security flaws

Find scientific papers, check their citation details and retraction notices, and synthesize the evidence into a readable review. Identify landmark studies, compare findings or methods, and explain disagreements and research gaps with links to supporting papers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding the original paper behind a research topic
• Synthesizing evidence across multiple studies
• Comparing research methods and their trade-offs

WeCom (Enterprise WeChat) CLI - official open-source CLI tool from WeCom. Covers 7 business categories: Contacts, Todos, Meetings, Messages, Schedules, Documents, Smartsheets. Built in Rust for macOS/Linux/Windows. Use when user wants to operate WeCom resources.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Feishu/Lark CLI - official open-source CLI tool from Feishu for AI Agents. Provides 200+ commands across 12 business domains: IM, Docs, Sheets, Base (Bitable), Calendar, Video Meeting, Mail, Tasks, Wiki, Drive, Contacts, Search. Supports both user identity and bot identity authentication. Use when user wants to operate Feishu/Lark resources.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

DingTalk Workspace CLI (dws) - officially open-sourced cross-platform CLI tool from DingTalk. Provides 86 commands across 12 products: Contact, Chat, Bot, Calendar, Todo, Approval, Attendance, Ding, Report, AITable, Workbench, DevDoc. Built in Go with zero-trust security architecture. Use when user wants to operate DingTalk resources.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

End-to-end GitHub repository maintenance for open-source projects. Use when asked to triage issues, review PRs, analyze contributor activity, generate maintenance reports, or maintain a repository. Triggers include "triage", "maintain", "review PRs", "analyze issues", "repo maintenance", "what needs attention", "open source maintenance", or any request to understand and act on GitHub issues/PRs. Supports human-in-the-loop workflows with persistent memory across sessions.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

End-to-end open source contribution workflow: from scanning issues to submitting PRs. Use this skill whenever the user wants to contribute to an open source project, find issues to fix, submit a pull request, fork a repo to contribute, fix a GitHub issue, or mentions 'open source contribution'. Also trigger when they provide a GitHub repo URL and ask about contributing, say things like 'help me submit a PR', 'find good first issues', 'I want to contribute to X', or mention fixing bugs in someone else's project.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Structure prediction using Boltz-1/Boltz-2, an open biomolecular structure predictor. Use this skill when: (1) Predicting protein complex structures, (2) Validating designed binders, (3) Need open-source alternative to AF2, (4) Predicting protein-ligand complexes, (5) Using local GPU resources. For QC thresholds, use protein-qc. For AlphaFold2 prediction, use alphafold. For Chai prediction, use chai.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.