'code generation' 검색 결과

Set up LLM serving with structured responses, including JSON and outputs restricted to specified patterns. Covers reusing shared prompt calculations, tool calling, and multi-turn conversations through SGLang, with examples for server setup and application integration.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Extract information into JSON with a defined schema
• Build agents that call tools
• Reuse shared prompts across chat requests

Combine capabilities from multiple fine-tuned LLMs without retraining using mergekit. Choose a merging method, configure how models are blended, and evaluate the resulting model on tasks such as math, code generation, and conversation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Combining math, coding, and conversation capabilities
• Blending two models at different ratios
• Comparing variants made with different merging methods

Turns research reports and experimental results into a paper through outline planning, figure creation, LaTeX drafting, PDF compilation, and review. Produces editable source files and a compiled PDF, with checks connecting claims to evidence.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turning a research report into a paper draft
• Creating paper figures and tables from experiment data
• Preparing a manuscript for a target venue

Develop robotics research ideas through literature review, feasibility filtering, novelty checks, and external critique. Get ranked proposals with specific benchmarks, comparison methods, failure metrics, and simulation-first pilot plans matched to available infrastructure.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Exploring research topics in manipulation or navigation
• Choosing robotics ideas that fit available infrastructure
• Planning pilot studies with simulation or existing logs

Create academic architecture diagrams and method illustrations with Gemini image generation. The workflow refines layout and visual style, then uses Claude to inspect arrows, labels, and readability and guide further revisions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Illustrating a model architecture for a paper
• Turning a method description into a workflow diagram
• Reviewing diagram arrows and labels

Explore a broad research direction through literature searches, idea generation, novelty checks, small pilot experiments, and critical review. Receive ranked ideas plus a refined proposal and experiment plan for the leading candidate, with evidence recorded across stages.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding concrete ideas within a broad research topic
• Exploring improvements to a reference paper
• Comparing promising ideas through small pilot experiments

Choose and configure AI tools for Web3 security work across web applications, APIs, and Solidity contracts. Follow setup examples for reconnaissance, vulnerability validation, and proof-of-concept generation, then combine automated findings with manual review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing AI tools for a security testing target
• Automating web application and API reconnaissance
• Preparing Solidity checks and proof-of-concept code

Turn Git commits, records of code changes, into clear release notes for users. The skill groups updates by type, rewrites technical descriptions in plain language, and filters out internal work such as refactoring and tests.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Preparing release notes for a new version
• Summarizing weekly or monthly product updates
• Writing app store update descriptions

Assess a website’s readiness for AI search alongside traditional SEO. Review content citation readiness, crawler access, brand mentions, technical foundations, and structured data, then generate scores, prioritized recommendations, and client reports.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Audit a website’s readiness for AI search
• Assess a page’s suitability for AI citation
• Check AI crawler access and generate llms.txt

Continue Python tasks when the sandbox cannot start by switching to run_shell. The workflow covers short scripts, saved script files, library checks, longer timeouts, and output verification for tasks such as PDF generation and data processing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Continue Python work after sandbox startup failures
• Generate PDFs through shell execution
• Run data processing with required libraries

Hand complex document generation or data processing to shell_agent when direct tools repeatedly fail. Define the required output, let the tool choose libraries and recover from errors, then verify the resulting files and content.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Resuming work after repeated tool failures
• Delegating PDF or DOCX document generation
• Handing off multi-step data processing

Generate PDF checklists, reports, and assessments with sections, tables, and scoring criteria using Python. Choose a suitable library, save the document for download, and check the output, with shell execution as an alternative when the sandbox fails.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turn a checklist into a PDF with sections and tables
• Create an assessment report with criteria and scores
• Produce PDF reports containing charts

Investigate Python failures in a sandbox, an isolated execution environment, by capturing partial logs, testing functions separately, and checking output files one at a time. Use the findings to identify failing steps and rebuild a working script.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate failures with missing or incomplete output
• Isolate a failing function in a large script
• Verify multiple generated files one at a time

Create multi-page PDFs with headings, tables, and consistent styling using reportlab, a Python library for building PDF documents. Run code directly through run_shell to control margins and page breaks when shell_agent document creation is unreliable.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating multi-page reports with tables
• Adjusting document margins and page breaks
• Generating PDFs when shell_agent creation fails

Generate Word, PDF, and HTML documents from one Markdown source. The workflow checks available tools, replaces problematic characters for PDF conversion, tries alternative conversion engines when needed, and checks that output files were created.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Exporting one report as Word, PDF, and HTML
• Handling PDF conversion errors caused by special characters
• Generating PDFs without pandoc or LaTeX

Produce Word, PDF, and HTML documents when retrieval or conversion tools fail. The workflow switches to available knowledge with stated limitations, prepares characters for PDF conversion, tries alternative tools, and checks the resulting files.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Drafting a report when search or file reading fails
• Producing Word, PDF, and HTML from one source
• Trying alternative tools after PDF conversion failures

Generates cryptographic test vectors, inputs with expected outcomes, by deliberately changing implementation code and finding changes existing tests miss. Verifies new vectors across independent implementations and compares detection rates before and after adding them.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding coverage gaps in cryptographic test vectors
• Creating invalid inputs that exercise validation checks
• Building test vectors shared across independent implementations

Investigate insecure deserialization, where restoring objects from stored or transmitted data can execute unwanted code. Covers multiple languages, input format recognition, vulnerable processing points, verification methods, and documentation of affected libraries and entry points.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing code that restores objects from external data
• Identifying serialized data in cookies and request bodies
• Assessing message consumers and admission webhooks

Organize authorized phishing exercises from sending infrastructure and email scenarios to landing pages and reporting. Uses GoPhish campaign tracking to review opens, clicks, and submissions while assessing employee awareness and email security controls.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning an authorized phishing exercise
• Preparing sending infrastructure and landing pages
• Reviewing email, QR code, and callback scenarios

Run builds, tests, code checks, and development servers in an Nx workspace. Choose one project, several projects, or projects affected by changes, with options for parallel execution, cached results, and failure handling.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Run tests for selected projects
• Build and check projects affected by changes
• Run multiple tasks across the workspace

Write and edit READMEs, guides, and other documentation using the code as evidence. Improve structure, wording, and terminology while checking related pages and links against the project's contribution process and documentation style guide.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Writing a guide for an existing feature
• Improving a README's structure and wording
• Updating documentation to match the implementation

Estimate how model architecture, precision, and context length affect weight storage, generation state, computation, and memory traffic. Compare models and attention designs with separate resource estimates for input processing and token generation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare memory needs across model architectures
• Estimate resource costs of longer contexts
• Compare attention designs and expert-based models

Collect Trustpilot reviews for a company domain, with filters for ratings, language, dates, and reply status. Get structured review text, reviewer details, and company responses across pages to support reputation research and customer service analysis.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Collect low-rated reviews to study customer complaints
• Gather reviews for competitor reputation comparisons
• Collect company replies and their publication dates

Add AI chat, text generation, and agents to applications using AI SDK. The skill checks documentation and source code to guide streaming replies, external tool calls, structured results, React integration, and fixes for outdated API usage.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add AI chat to an application
• Build an agent that calls external tools
• Build answers using retrieved documents