'implementation' 검색 결과

Review code that manages the conversation history and extra information sent to Codex models. Apply rules for incremental history, size limits, cache stability, manual review of large additions, and required implementation structures.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review changes to conversation history handling
• Check size limits on information sent to the model
• Identify large additions requiring manual review

Maintain visual snapshot tests, which compare rendered images, for Remotion’s web renderer. Update existing tests after implementation changes, or add explicitly requested tests with sample components, preview registration, and documentation updates for supported properties.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Updating existing tests after renderer changes
• Adding an explicitly requested rendering test
• Registering a test fixture for preview

Find current Remotion documentation for a feature or API, the interface used by code. Search for relevant pages and read their Markdown text so implementation follows the documentation available now.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check how to use a Remotion API
• Find documentation for a feature before implementation
• Read relevant documentation pages as Markdown

Add a new effect to @remotion/effects, including its implementation, package entry points, documentation, interactive demo, and preview images. Follow the package conventions and verify the changes with tests, formatting checks, and builds.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Implementing a new effect for @remotion/effects
• Registering effect imports and parameter types
• Creating documentation and an interactive effect demo

Consult Sally, a UX and UI specialist, to translate user needs into interaction designs and UX specifications. The role considers unusual situations as well as everyday use, helping communicate clear design intent to architecture and implementation work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Discuss interaction flows based on user needs
• Clarify UX specifications for implementation
• Consider unusual situations in interface design

Record durable Cherry Studio engineering decisions in Agent Notes. Determine which changes need a note, prepare specifications with verifiable acceptance criteria, and manage approval, implementation, rejection, and replacement while preserving the reasoning behind decisions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Deciding whether a change needs a lasting decision record
• Documenting bug fixes with significant tradeoffs
• Preparing specifications for approval before implementation

Delegate code analysis and implementation in a selected project to Claude Code without an interactive session. The skill reads structured results, reports failures, and supports comparing its findings with another coding agent.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Request a code review without changing files
• Delegate implementation to Claude Code
• Compare findings from different coding agents

Delegate code analysis and implementation to Codex CLI without an interactive session. The skill reads ordered output events, extracts the final agent response, and reports errors, with a read-only sandbox used by default.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review code in a read-only sandbox
• Delegate implementation to Codex
• Get a second coding agent's assessment

Delegate scoped repository analysis or implementation to DeepSeek Harness without opening its interactive interface. Collect its final text, check the exit status, and inspect repository changes when the task requires read-only work.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Diagnose a failing test without editing files
• Delegate a scoped repository investigation
• Request implementation in a specified project

Clarify ambiguous requests before implementation by asking a small set of essential questions. Use concise choices and suggested defaults to agree on goals, scope, constraints, and completion criteria before starting work that depends on those answers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clarify a request with several plausible interpretations
• Agree on completion criteria before implementation
• Confirm compatibility requirements and scope

Design REST or GraphQL APIs by defining who will use them, what data they expose, and how requests behave. Establish error formats, versioning, pagination, and authentication, then review examples for consistency before implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing a new REST or GraphQL API
• Reviewing API specifications before implementation
• Establishing shared API design standards

Guide AI coding work toward simple implementations, focused edits, and explicit assumptions. Use it when writing, reviewing, or refactoring code to keep changes tied to the request and define success through tests or other concrete checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Keeping bug fixes limited to the necessary code
• Simplifying code that has become overcomplicated
• Making implementation assumptions explicit

Plan AI application development by selecting relevant phases and companion skills. The workflow covers language model integration, retrieval from documents, agents, machine learning pipelines, monitoring, and security, with prompts and quality checklists.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan AI features and language model integration
• Organize RAG retrieval design and implementation
• Map agent roles, tools, and memory

Guide a scoped coding task through specification, implementation, and review. Set acceptance criteria, verification checks, iteration limits, and approval gates, then correct identified gaps until the requirements pass or a stopping condition is reached.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a small feature from specification through verification
• Modify a module against explicit acceptance criteria
• Repeat fixes and checks within an iteration limit

Provides persistent project memory for AI agents through a local MCP server, a tool interface for agents. Stores and searches architecture decisions and implementation patterns, syncs with project documentation, and includes a dashboard for viewing memory usage.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Save architecture decisions for later reference
• Search previously recorded implementation patterns
• Retrieve design notes by key

Assess a new or existing AI project by examining its code, goals, and constraints. Recommend skills confirmed to exist in the available registry, then outline tasks and implementation phases with dependencies, completion criteria, and checks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning the first steps of a new AI project
• Assessing technical issues in an existing project
• Selecting relevant skills from an available registry

Explore unfamiliar code with GitNexus to understand project structure and execution flows. Find related functions, inspect their callers and callees, and read implementation files to explain how a feature works, with repository and index freshness information.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Understand the structure of an unfamiliar project
• Trace authentication or payment flows
• Find a function's callers and callees

Coordinate GitHub pull request reviews by assigning comment triage and code changes to dedicated sub-agents. Repeat the process, track decisions and progress, and reply to and resolve threads as fixes are completed.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Work through outstanding pull request review comments
• Separate required fixes from items outside the pull request scope
• Repeat review and implementation until actionable items are cleared

Turn previously fetched pull request reviews into an ordered action plan. Separate distinct findings, track deferred work in Linear, validate that every triage decision is complete, and produce JSON and Markdown files for the implementation phase.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning responses to fetched PR review feedback
• Separating multiple findings within a single review
• Tracking deferred review work in Linear

Assess Airflow Improvement Proposals by comparing Confluence specifications with pull requests, commits, and codebase files. Produce evidence-backed progress reports showing delivered items, remaining work, and specification updates needed across one or more proposals.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Check implementation progress for an Airflow proposal
• Compare specification deliverables with shipped code
• Compile a progress report across multiple proposals

Review Python code for common mistakes in error handling, asynchronous operations, type annotations, and tests. Use a practical checklist and correction examples to guide code reviews, investigate bugs, and improve existing implementations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing Python code before a merge
• Investigating bugs caused by common coding mistakes
• Refactoring legacy Python code

Generate independent options for design, implementation, explanations, or debugging, then compare them using one shared rubric. Code candidates use separate working copies and undergo independent verification before a winner is presented for review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Comparing several plausible design approaches
• Evaluating independent implementations of the same task
• Comparing explanations or debugging approaches

Create a Kotlin MCP server, which connects AI agents to external tools, using the official SDK. Generate a Gradle project with tool implementations, input validation, configuration, basic tests, and setup documentation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Start a Kotlin MCP server project
• Expose custom tools to AI agents
• Set up stdio or SSE transport

Review C#/.NET code for design patterns, separation of responsibilities, and common implementation issues. Receive actionable recommendations covering maintainability, testing, performance, and security without changing the code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review design patterns in C#/.NET code
• Check separation of responsibilities before refactoring
• Identify dependencies that make testing difficult