'debugging' 검색 결과

Create, debug, and maintain Windows batch scripts for file operations, backups, and scheduled tasks. Covers command arguments, variables, loops, and error handling, with starter templates for command-line tools and reusable functions.

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• Automating file copies and backups
• Creating scripts for Task Scheduler
• Debugging variable expansion and quoting

Helps build and maintain Ant Design interfaces by checking component options, examples, and theme settings. It also supports debugging, version migrations, and project scans to identify deprecated code and configuration issues.

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• Build interfaces using component APIs and working examples
• Investigate component bugs and configuration issues
• Check changes before upgrading Ant Design

Add or verify model support in SGLang's Rust processor so chat requests produce the same prompt text and token IDs as Python. Use reference-generated test cases to find differences in tools, reasoning settings, conversation history, and errors.

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• Adding model support to sglang-processor
• Porting model rendering from sgl-router
• Rechecking prompt behavior after a Dynamo update

Understand and modify SGLang's CI pipelines, including test stage order, start conditions, early stopping after failures, and workload splitting. Use the guide to add jobs and investigate failed, skipped, or cancelled checks.

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• Add a test job to an SGLang CI stage
• Investigate failed or skipped CI checks
• Update test partitions and waiting job counts

Connect an agent to an existing Chrome browser, find local CDP ports used for remote browser control, or start a browser on a specified port for sharing with other agents and tools.

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• Connecting to Chrome with existing logins and open tabs
• Finding available local browser debugging ports
• Starting a browser on a fixed debugging port

Configure how the browser starts, including window visibility, proxy settings, extra launch options, and a custom browser executable. It also explains opening a local debugging port so other local tools can connect.

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• Show the browser window during automation
• Start a browser with a proxy or incognito mode
• Choose a specific installed browser

Compose compact, structured prompts for coding, debugging, review, and research with Codex or GPT-5.4. This internal skill defines task scope, completion criteria, output format, verification steps, and evidence requirements using consistent XML tags.

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• Define implementation scope and completion criteria
• Include verification steps in debugging requests
• Specify evidence requirements for code reviews

Keep project decisions, debugging notes, and session discoveries in a lasting Markdown wiki. Organize pages with tags and categories, connect related notes with links, and retrieve information through keyword searches.

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• Recording architecture decisions and their context
• Finding notes from earlier debugging sessions
• Saving discoveries at the end of a session

Use LangSmith to record LLM application inputs, outputs, and timing, investigate failures, evaluate answers against test datasets, and monitor production usage. It also guides automated quality checks and analysis of token usage and costs.

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• Investigating failures in LLM applications
• Evaluating answers against test datasets
• Monitoring production latency and costs

Get guidance on adapting LLMs with Unsloth, including implementation, API usage, and debugging. Covers LoRA and QLoRA, methods for adjusting models with fewer trainable parameters, with a focus on training speed and memory use.

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• Learning how to fine-tune models with Unsloth
• Exploring LoRA and QLoRA for efficient training
• Implementing features using Unsloth APIs

Configure Claude Code and improve how you assign coding tasks. This guide provides a CLAUDE.md template, practical prompting examples, debugging approaches using logs, and a workflow for making and checking small changes.

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• Set up project guidelines in CLAUDE.md
• Write clearer requests for coding tasks
• Investigate unexpected agent behavior using logs

Build custom cognee processing by chaining Python tasks, defining data types, and saving results to graph and vector databases. Use it to enrich existing data, inspect run status, and troubleshoot how tasks pass data.

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• Building custom extraction and processing steps
• Saving custom data types to graph and vector databases
• Adding information to an existing graph

Turn a Zoom integration idea into a recommended architecture and implementation path. The skill identifies the task, selects the appropriate Zoom technology, and routes requests to focused skills for authentication, meetings, bots, AI workflows, or debugging.

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• Choosing Zoom technology for a new integration
• Planning how to embed a Zoom meeting
• Finding the implementation path for a meeting bot

Explicitly save debugging discoveries, project conventions, and working preferences to Claude's persistent project memory. The skill checks for duplicate notes, keeps entries concise, and suggests moving enforceable rules into CLAUDE.md when appropriate.

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• Preserving hard-won debugging discoveries
• Recording undocumented project conventions
• Remembering tool-specific commands and pitfalls

Plan, set up, audit, and debug analytics tracking with GA4 and Google Tag Manager. Define events and their parameters, configure conversion tracking, and investigate missing or duplicate data using structured checks and prioritized fixes.

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• Building an event tracking plan from scratch
• Auditing existing tracking for gaps and duplicate events
• Debugging events missing from GA4

Maintain cmux billing code with guidance on Stripe checkout, pricing, subscriptions, and access rights. It maps the relevant services and provides workflows for testing purchases, handling payment events, and rolling out billing changes.

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• Debugging checkout and subscription records
• Updating prices and plan switching
• Checking paid access and Cloud VM limits

Connect OpenCode browser tools to a locally running OpenWork Electron app to inspect its UI, enter a task, and check the response. This skill supports exploration and debugging through CDP, Chrome's remote control protocol.

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• Connecting browser tools to a local Electron development app
• Inspecting screen state during debugging
• Entering a task in the composer and running it

Build and maintain interfaces with shadcn/ui by finding, adding, and combining components. The skill uses project settings, component documentation, and change previews to guide styling, debugging, preset changes, and updates that preserve local edits.

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• Building settings pages and dashboards from existing components
• Fixing form and dialog composition issues
• Updating components while preserving local edits

Set up and troubleshoot Daytona sandbox environments, which provide isolated spaces for running applications. The skill covers CLI authentication, persistent desktop and server sandboxes, diagnostic logs, shared secrets storage, snapshot refreshes, and environment deletion.

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• Troubleshooting Daytona authentication and organization selection
• Keeping an Electron or server sandbox available for debugging
• Preparing shared secrets storage for sandboxes

Find the right specialist guidance for building, editing, testing, or debugging n8n workflows through n8n-mcp. This entry skill explains available tools, connection requirements, credential handling, and checks to perform before activating a workflow.

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• Finding the right skill for an n8n task
• Checking settings and connections before activation
• Investigating a workflow that behaves unexpectedly

Use CoinGecko API documentation to build cryptocurrency price trackers and market data integrations. The skill supports implementation and debugging for access to prices, market capitalization, trading volume, and historical data.

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• Building a cryptocurrency price tracker
• Integrating market capitalization and trading volume data
• Exploring how to retrieve historical prices

Turn plain-language requests into Cloud Logging queries for Google Cloud. Generate service-specific filters to find errors, investigate issues, or review audit logs using LQL, the language used to search these logs.

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• Finding recent error logs
• Filtering logs for a specific Google Cloud service
• Investigating who changed or accessed a resource

Helps AI agents recover from repeated failures by reviewing previous attempts, checking original sources, testing different hypotheses, and verifying results. It combines structured troubleshooting with performance review rhetoric modeled on large technology companies.

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• Breaking out of repeated failed attempts
• Investigating configuration or deployment failures
• Verifying an agent's claimed completion

Plan and troubleshoot large language and vision model training and inference. This guide uses hardware measurements to identify bottlenecks, address memory shortages and unstable training, and improve checkpointing, recovery, and performance across multiple GPUs and machines.

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• Diagnosing slow training and GPU memory shortages
• Investigating loss spikes and invalid numerical values
• Debugging communication hangs across GPUs and machines