'debug' 검색 결과

Investigate errors and unexpected behavior through reproduction, isolation, diagnosis, and a proposed fix. Receive a structured report covering the root cause, necessary code or configuration changes, and suggested tests to prevent the issue from returning.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate an error message or stack trace
• Diagnose behavior that differs between staging and production
• Trace a failure that appeared after deployment

Investigate difficult bugs by adding temporary logs to the actual execution path and reproducing the reported behavior. Analyze JSONL logs, which store one structured event per line, then fix the cause, verify regression tests, and remove debugging artifacts.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating bugs that occur only during manual use
• Tracing event order in streaming or concurrent operations
• Checking whether passing tests cover the reported bug

Extract fields, filter records, and reshape JSON from API responses, configuration files, or logs using Crush’s built-in jq. Get help writing and debugging transformations, constructing new JSON, and formatting output for other commands.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Extract selected fields from API responses
• Filter JSON arrays by conditions
• Reshape configuration data or construct JSON

Investigate difficult bugs through explicit hypotheses, targeted logs, and repeated checks against actual data. Keep an investigation journal to track findings, examine environment differences and leftover state, and confirm the root cause before applying a fix.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate a bug that survived an initial fix
• Trace tests that fail intermittently
• Compare local behavior with a user's report

Turns recurring workflows and proven debugging solutions into reusable skill packages. It creates SKILL.md, a readable overview, and optional supporting examples from a user description or saved project memory, with checks for completeness and portability.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Saving a debugging solution as a reusable skill
• Packaging recurring workflows for other projects
• Turning saved project knowledge into documented procedures

Build, run, and debug the Kilo JetBrains plugin using its Gradle workflows. It covers isolated development storage, chat logs, sandbox recovery, and switching between a pinned CLI release and locally built CLI code.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a versioned plugin ZIP for testing
• Run the plugin in a sandbox or split mode
• Inspect chat logs and session events

Implement and debug Google OAuth 2.0 refresh tokens bound to a client key. Covers key generation, signed DPoP proofs that demonstrate key possession, and nonce challenge retries in WebCrypto and JavaScript environments.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Bind Google OAuth refresh tokens to a client key
• Debug DPoP proof signatures and nonce retries
• Plan a backend for a browser application using DPoP

Write and debug code for further training large language models with TRL. Match training methods to dataset formats, configure supervised or preference-based training, and set up reward functions through Python or the command line.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Training a language model on example responses
• Training with preferred and rejected response pairs
• Debugging GRPO reward functions and batch settings

Debug json-render interfaces with an inspector panel that shows screen specifications, editable runtime state, action history, and streamed updates. Select a rendered page element to locate its definition and investigate display or interaction problems.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate missing or incorrectly displayed elements
• Inspect and edit application state at runtime
• Review action results and errors

Develop and debug LangBot's backend and web frontend. The skill guides environment setup, API additions, authentication, database migrations, and testing, including updates to matching MCP tools so agents can use changed API features.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Set up the LangBot backend and frontend for development
• Add an API endpoint and its matching MCP tool
• Update the database schema with Alembic

Build and debug LangBot plugins that handle messages, commands, and AI tool calls. The skill covers SDK usage, common errors, test environment setup, WebSocket message testing, and preparation for publishing to LangBot Space.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create a plugin that reacts to incoming messages
• Fix plugin SDK errors and missing responses
• Test group and private chats through WebSocket

Test and debug REST and GraphQL APIs using curl, httpie, Postman collections, or scripted tests. Check authentication, invalid inputs, pagination, and response details to identify failures that a successful status code alone may miss.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking authentication and access permissions
• Testing invalid inputs and boundary conditions
• Debugging failed HTTP requests

Analyze records of an AI agent’s decisions and tool use to find repeated failures, lost goals, and misunderstood instructions. Use the findings to refine prompts, rerun tasks, and turn debugging lessons into reusable skills.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigating repeated agent failures
• Reviewing incorrect tool choices
• Refining prompts through repeated evaluation

Investigate software errors, version conflicts, and API questions across official documentation, GitHub, technical Q&A, and Chinese developer communities. Results distinguish matching errors, source authority, and reported environments, giving you documented leads and next checks for debugging.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find existing reports of the same error
• Investigate package and runtime version conflicts
• Look up API usage in documentation and Q&A

Diagnose failed model requests from OpenShell sandboxes to hosted APIs or local servers such as Ollama and vLLM. Check provider attachment, access rules, credentials, network layout, and client settings to identify the narrowest configuration change needed.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Diagnose failed requests to hosted model APIs
• Troubleshoot connections to Ollama or LM Studio
• Investigate credential and endpoint mismatch errors

Diagnose unreachable or unhealthy OpenShell gateways and sandbox startup failures. Identify the underlying execution platform, then examine logs, authentication, certificates, and configuration with the matching tools to narrow down the cause.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Investigate gateway connection and health check failures
• Find why a sandbox remains pending or fails to start
• Check Docker or Podman runtime and image problems

Find, add, and combine shadcn/ui components to build forms, dashboards, and other interfaces. Use project settings and component documentation to guide styling, debugging, preset changes, and updates that preserve local modifications.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build forms and dashboards from existing components
• Find and add components from registries
• Debug component structure and styling

Create, migrate, refine, or debug CARLA vehicle assets with Blender and Unreal. Use real vehicle references to guide geometry and materials, configure wheels, lights, and physics, and deliver editable sources with evidence from runtime validation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a CARLA vehicle from real vehicle references
• Refining tires, materials, or body geometry
• Migrating vehicles and debugging Unreal integration

Validate CARLA pedestrian navigation by sampling walkable locations and reporting their coverage. Draw the samples as debug points to inspect the walkable area after a map import or investigate pedestrians that will not move.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking pedestrian navigation after importing a map
• Investigating pedestrians that stand still
• Visualizing the area pedestrians can walk through

Guides PyTorch model training and fine-tuning, from choosing architectures to configuring optimizers and learning rates. Provides troubleshooting steps for unstable loss and memory shortages, plus methods for improving GPU throughput and comparing experiments.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choose model architectures for the available data type and scale
• Configure optimizers and learning-rate schedules
• Investigate loss spikes, NaNs, and GPU memory shortages

Build React components, forms, and custom hooks with TypeScript. Organize state and data fetching, debug rendering problems, migrate class components, and improve performance, with type checks and component tests to validate the implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build React components and forms
• Design state management and data fetching
• Debug rendering issues and improve performance

Build and debug Java applications with Spring Boot 3.x. This skill guides application design, API implementation, database query tuning, authentication, and testing, including WebFlux applications that process requests without blocking.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build APIs with Spring Boot
• Improve slow JPA queries
• Configure OAuth2/JWT authentication

Inspect recent merges for leftover debug code, TODO comments, lint warnings, and technical debt, meaning deferred maintenance work. Create a prioritized cleanup list that separates small fix candidates from issues requiring human judgment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding debug code left after merging
• Organizing TODO and FIXME follow-up work
• Prioritizing newly introduced lint warnings

Write and debug code for further training large language models with TRL. Match training methods to dataset formats, configure supervised or preference-based training, and set up reward functions through Python or the command line.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Training a language model on example responses
• Training with preferred and rejected response pairs
• Debugging GRPO reward functions and batch settings