'clean' 검색 결과

Programmatically clear WP Rocket cache from a third-party plugin / theme when data changes — the public rocket_clean_* function family (rocket_clean_post, rocket_clean_files, rocket_clean_term, rocket_clean_user, rocket_clean_home, rocket_clean_minify, rocket_clean_cache_busting, rocket_clean_domain, rocket_clean_cache_dir). Critical detection rule — WP Rocket is a PAID plugin not on Packagist; always feature-detect via function_exists('rocket_clean_post') OR defined('WP_ROCKET_VERSION') before calling, since not every site has it. Never raw-unlink the cache directory or call wp_cache_flush() expecting it to clear WP Rocket — wp_cache_flush is WP object cache, WP Rocket is FILE cache. The before_*_clean_* / after_*_clean_* action lifecycle hooks fire around every clean — useful for audit logging, monitoring, custom invalidation chains. Use when integrating cache invalidation in a companion plugin, WC integration, custom data plugin. Triggers on rocket_clean_, before_rocket_clean, af...

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Clean spoken recordings by transcribing words, identifying filler and false starts, and joining cuts with short audio fades. Preview proposed edits, reduce breaths, repair noise-gate clicks, and optionally use Cleanvoice for additional cloud processing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Removing filler words and long silences from a podcast
• Reviewing proposed edits before applying them
• Repairing clicks caused by a noise gate

Automate Campaign Cleaner operations through Rube MCP and Composio. The skill discovers available tools, checks the service connection, and uses current input requirements to carry out the requested workflow.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding tools for a Campaign Cleaner task
• Checking the service connection before execution
• Automating a workflow with multiple operations

Automate Campaign Cleaner operations through Rube MCP and Composio. The skill discovers available tools, checks the service connection, and uses current input requirements to carry out the requested workflow.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding tools for a Campaign Cleaner task
• Checking the service connection before execution
• Automating a workflow with multiple operations

Find and identify the CCSGameRules_PostCleanUp function in CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the post-round entity-cleanup routine. It is non-virtual and has no unique string of its own, so it is found via the CCSGameRules_ResetRound predecessor: PostCleanUp is the entity-cleanup call ResetRound makes. Emits a unique IDA-style byte signature and a func YAML. Mirrors the find-CCSGameRules_PostCleanUp.py preprocessor (LLM_DECOMPILE CCSGameRules_ResetRound). Trigger: CCSGameRules_PostCleanUp, PostCleanUp, CGameRules::PostCleanUp

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Remove AI-generated code smells (slop) from branch changes or an explicit file list. Locks behavior with regression tests FIRST, then runs categorized cleanup via parallel `deep` agents in batches of 5, then verifies with quality gates. Covers 10 slop categories including performance equivalences, excessive complexity (object annotations, if/elif variant chains), and oversized modules (250+ pure LOC with mandatory modular refactoring). MUST USE when the user asks to "remove slop", "clean AI code", "deslop", "clean up AI-generated code", "remove AI slop", or wants to clean up AI-generated patterns from recent changes. Triggers - "remove ai slops", "clean ai code", "deslop", "cleanup AI generated", "remove AI slop", "clean up AI-generated code", "strip slop", "ai-slop cleanup".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Prepare spreadsheet data for analysis by finding extra spaces, inconsistent capitalization, numbers stored as text, mixed date formats, and duplicates. Review proposed fixes, apply traceable formula-based changes, and compare results before and after cleanup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Cleaning spreadsheet data before analysis
• Standardizing dates and text capitalization
• Finding duplicate rows and mixed data types

Identify unused AWS resources, estimate potential savings, and prepare cleanup scripts with preview steps. Covers storage retention policies and scheduled cleanup so teams can review dependencies before removing resources and track the resulting savings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Inventory unused resources and estimate savings
• Prepare cleanup scripts for EBS volumes and Elastic IPs
• Review S3 versions and storage retention rules

Clean up local Git branches and remote connections left after pull request reviews. The workflow checks unfinished work, preserves main and the current branch, and requests confirmation before force-deleting branches that have not been merged.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clean up branches after pull request reviews
• Remove contributor remotes other than origin
• Review unmerged branches before deletion

Analyze disk usage on macOS or Windows, identify large folders, and classify cleanup candidates by the care they need. Generate an interactive HTML report with estimated space savings, cleanup guidance, and optional browser controls for deleting selected files.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding large folders when disk space runs low
• Reviewing caches and downloads before cleanup
• Identifying which app owns an unfamiliar large folder

Maintain data retention in ClawHub's Convex tables by classifying each table, defining expiration fields, and bounding cleanup jobs. Guide changes to temporary data and expired authentication records, with focused tests and runtime verification.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Classify retention policies for new tables
• Add expiration fields and indexed cleanup
• Update scheduled jobs with bounded deletion batches

Use when the user wants to simplify, clean up, refactor, tidy, or refine code — their staged/unstaged git changes or a target file/path. Reduces complexity, flattens nesting, removes redundancy and dead code, scores each change by value (holding low-value churn), then runs tests to prove nothing broke. Invoke on: "simplify", "simplify this", "simplify my code/changes", "clean up", "clean this up", "clean up my changes", "refactor this", "make this cleaner", "tidy this up", "reduce complexity", "flatten this", "remove dead code", "make it more readable", "polish before commit", or "absolute simplify". Acts on your working diff; for repo-wide dead code use absolute-prune; for lint/type debt use absolute-debt.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

AWS Cost Cleanup workflow skill. Use this skill when the user needs Automated cleanup of unused AWS resources to reduce costs and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when asked to run /clean-clean-cut to cut accumulated records and residue. Not for untracked or non-VCS changes, or branch/worktree cleanup: use git-cleanup.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Review recent code changes from four angles: reuse, quality, efficiency, and whether fixes address underlying mechanisms. Combine findings, apply suitable cleanup with tests, and leave changes that could affect behavior for human review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Cleaning up recent code changes
• Finding duplicated logic and reusable helpers
• Reviewing efficiency in the last commit

Clean messy tabular data through OpenRefine using command-line operations. Import files, inspect rows, apply reusable JSON transformation histories, and export cleaned CSV or TSV data, with session support for undoing and redoing changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Remove extra spaces from names in a CSV file
• Reuse the same cleaning steps on another dataset
• Inspect sample rows before and after transformation

Structure Python code to release files and database connections reliably, including when errors occur. Covers context managers, which handle setup and cleanup, asynchronous resources, nested cleanup, and streaming responses that retain accumulated state.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Releasing database connections when errors occur
• Cleaning up files and temporary files
• Creating asynchronous context managers

Design or refactor backend services with clear layers and dependency rules. Using Clean Architecture, Hexagonal Architecture, and Domain-Driven Design, it separates business logic from databases and frameworks and defines interfaces that support testing without external services.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing the structure of a new backend service
• Separating business logic from database and HTTP code
• Resolving circular dependencies between layers

Prepare raw credit data for pre-loan modeling by checking data quality and screening variables. Review missing values, predictive usefulness, stability, noise, and correlation, then export an Excel report with organization-level statistics and cleaning results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Prepare credit data before building a model
• Compare missing values and bad-sample rates across organizations
• Screen variables for usefulness, stability, and redundancy

Simplify bloated AI-generated code by removing dead code, duplicated logic, and unnecessary layers while checking that existing behavior stays intact. Use a limited cleanup scope, verify changes with relevant checks, or request a review without edits.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Removing duplicate logic and unused code
• Simplifying unnecessary wrappers without changing behavior
• Cleaning up only a specified set of changed files

Prepare readable Markdown from HTTPS article pages using an optional external Defuddle cleaner. The workflow checks URLs, requires network consent and executable review, previews extracted content, and can retain the cleaned source separately from wiki ingestion.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Extract readable Markdown from a web article
• Prepare a web source for later wiki ingestion
• Save cleaned content with source metadata

Add burned-in captions to a finished video using Whisper timings from its own audio. Choose paper, bold, or clean styling, and optionally use narration text to preserve intended spelling. Outputs include the captioned video and an SRT file.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding captions to a finished video
• Restyling captions for social media shorts
• Preserving brand names and numbers from a narration script

Clean up unwanted Dropbox files and folders through a review process. Identify candidates, check metadata and sharing status, optionally preserve copies, and delete only explicitly confirmed items, with a report of each outcome.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review and delete duplicate PDFs in a Dropbox folder
• Remove obsolete draft files after confirmation
• Clean up temporary exports stored in Dropbox

Facilitate a structured conversation to define clean code principles for a repository. Produces a formal clean-code.md document that the clean-code atom will use as its override. Use when setting up coding standards, defining code quality rules, or when the user says 'setup clean code', 'define coding standards', 'code quality principles', 'coding guidelines', or 'help me define my code standards'.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.