'ai-agent' 검색 결과

Review and rewrite Chinese product announcements, articles, emails, and README text using eleven style checks. Identify repetitive phrasing, overloaded sentences, vague openings, and decorative language, then revise them into clearer statements suited to each type of writing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Revising formulaic Chinese product announcements
• Reviewing repetitive phrasing in Chinese articles
• Shortening overloaded sentences in Chinese emails

Design recovery paths for AI agents that loop, lose streamed responses, or hit service limits. Classify failures, choose retries or backup models, and set stopping rules to keep recovery attempts from causing further failures.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating repeated tool calls with no progress
• Designing recovery for interrupted responses
• Setting retry limits and stopping rules

Design evaluation tasks that check whether agents actually complete work. Define requests, simulated user behavior, starting conditions, and verifiable success criteria, then plan difficulty levels, training-data leakage checks, and ongoing maintenance.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating evaluation tasks for real business workflows
• Reviewing success criteria and verification logic
• Designing checks for evaluation data leakage into training

Find animation, short-video, and motion-effect references on 1human, including items saved in a shared human-agent library. Review sources and licenses to guide creative work, and publish creations only within the owner's explicit permission.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find references for a loading animation
• Use shared favorites to guide motion design
• Check source tutorials and creation recipes

Create and manage persistent Azure AI agents from Java. Covers conversation threads that retain messages, agent execution, status checks, response retrieval, and cleanup, using preview SDK examples with guidance on authentication and cloud resource handling.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building a Java app with reusable AI agents
• Managing conversation threads and messages
• Checking execution states and handling timeouts

Helps build AI agents in .NET with persistent conversation threads. Covers messages, execution status, streaming responses, document search, and custom function calls using Azure.AI.Agents.Persistent, with examples for creating agents and cleaning up resources.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build an AI assistant that retains conversation threads
• Answer questions using uploaded documents
• Connect an agent to custom functions

Analyze a codebase to create project-specific AGENTS.md instructions and supporting rule files. Detect the package manager and relevant conventions, preview proposed changes, or update existing guidance when the project’s tools change.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create agent instructions tailored to an existing project
• Generate a minimal AGENTS.md file
• Refresh instructions after changing development tools

Plan and build AI agents through selected stages of design, implementation, tool integration, memory, and evaluation. The workflow points to specialized skills for single agents, coordinated agent teams, and stateful workflows using CrewAI or LangGraph.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing an autonomous AI agent
• Building a team of agents with distinct roles
• Creating stateful workflows with LangGraph

Design layered protections for AI agents against malicious instructions, tool misuse, and data leakage. Provides guidance and code examples for input checks, isolated tool execution, permission limits, and audit logging to help review and strengthen agent security.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review defenses against malicious instructions
• Isolate tool execution and restrict permissions
• Assess data leakage risks between tenants

Design AI agents that use tools, plan tasks, retain relevant context, and recover from failures. Choose execution patterns, permission boundaries, memory handling, and runtime limits, and assess whether coordinating multiple agents is justified for the task.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing an execution loop for a tool-using agent
• Designing memory and recovery for long-running tasks
• Setting tool permissions, runtime limits, and cost caps

Document the tools an AI agent may call, including input rules, caller permissions, execution limits, and retry conditions. Produce a tool register and verification plan for reviewing registrations or MCP routing designs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Defining which tools an agent may call
• Reviewing a proposed tool registration
• Documenting timeout and retry rules

Create consistent records for evaluating AI agents, including task success, invalid tool calls, token use, and actual costs. Produce CSV tables, database definitions, and JSON validation schemas to support reproducible comparisons and checks for performance declines.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Recording agent evaluation results in a shared format
• Comparing a candidate agent with a baseline
• Tracking actual cost per solved task

Organize CTF investigations by mapping the supplied targets, tracing one minimal path, and selecting the relevant specialist workflow. Findings are grounded in observed behavior and reproducible evidence, with a clean baseline used for verification.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing an analysis path for a CTF challenge
• Tracing a minimal path through challenge infrastructure
• Packaging reproducible evidence for a solution

Guides Python agent development with PydanticAI, covering tool calls and structured outputs checked against defined data types. Explains service injection, provider switching, streaming responses, and tests that run without calling a real language model.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building agents that return validated structured data
• Connecting customer support agents to order data
• Testing agent logic without real model calls

Design AI agents that plan tasks, call tools, and retain useful information. Covers coordination between agents, evaluation, and debugging, with practical patterns for execution limits, error handling, and tracing what an agent does.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing an agent that plans and executes tasks
• Organizing tool definitions and selection
• Deciding what an agent should remember

Compare a Python SDK release plan or candidate with the previous release to assess compatibility, versioning, and proven regressions. Produce a ship-or-block recommendation, documentation handoff, and key changes for minor releases.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan the next patch or minor SDK release
• Assess whether a release candidate can ship
• Check compatibility and migration paths

Assess GitHub issues and pull requests by checking demonstrated user needs, existing alternatives, compatibility, and maintenance costs. Produce an evidence-based maintainer recommendation through code and document inspection, without running tests or examples.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Deciding whether a pull request merits merging
• Checking whether existing features already solve an issue
• Comparing competing fixes for the same problem

Compare local case files with insurer policies to prepare a concise prior authorization packet, covering approval requirements, referrals, missing information, and a checklist for staff reviewing the case and communicating with the patient.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check prior authorization requirements for a case
• Review referral status and imaging policies
• List missing information for human review

Fix a small formatting bug in a credit note shell script while keeping the output label as credit and the amount positive. Run the specified targeted test and summarize the bug, fix, and verification command.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Fix a credit note output formatting bug
• Check the credit label and positive amount
• Run the specified test and report the fix

Plan SDK behavior changes by defining required outcomes, compatibility boundaries, and unsupported cases. Reuse existing implementation paths, assess review feedback, and reconsider designs when repeated fixes introduce complexity beyond the original requirement.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Define the scope of an SDK behavior change
• Assess compatibility with released APIs
• Reconsider a design after repeated review findings

Measure Python SDK test coverage, the code exercised by tests, and identify meaningful gaps in user-visible behavior. Report proposed scenarios or add authorized tests, then verify the changes and report remaining gaps alongside coverage results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Auditing Python SDK test coverage
• Investigating a decline in coverage metrics
• Finding untested error and cancellation paths

Find and retrieve official OpenAI documentation to answer API integration questions with source evidence. Check endpoint definitions, parameters, and documented limits, and receive setup guidance when the documentation connection is unavailable.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Verify specifications before integrating an OpenAI API
• Check endpoint parameters and schemas
• Support technical explanations with official documentation

Capture a local static HTML page from the terminal using Playwright and Chromium. The supplied commands install the browser, set a 2048 × 1152 viewport, and save screenshots without starting a web server.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Capturing a local static HTML page
• Saving screenshots at a specified viewport size
• Keeping first and second captures as separate files

Carry agreed implementation work through a separate Git worktree, an isolated working directory. After checks and review, it prepares one local commit, a clean branch, and a pull request draft for handoff without publishing them.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Starting agreed implementation in a separate worktree
• Preparing a reviewed local branch with one commit
• Taking over an existing pull request while preserving author credit