2.6K skills · sorted by relevance
Check whether Apache Hudi table maintenance is keeping pace with incoming data. Runs a read-only utility, interprets its JSON report, and explains unhealthy or skipped checks with concrete next steps.
Crawl linked pages within a chosen website scope and collect clean text, Markdown, or HTML with page metadata. Use the resulting records as source material for AI search systems or chatbot knowledge bases.
Remove a specific Git worktree, a separate working directory for a branch, after checking uncommitted work and merge status. Clean up branches and stale references, protect important branches, and provide reminders for related database cleanup.
Clean Excel columns by removing unwanted prefixes from numeric values and extracting Chinese characters from text. Add the cleaned results as new columns, then save an Excel file and provide a download link.
Clean Excel data, summarize groups, and examine relationships between numeric columns. Produce charts such as scatter plots with trend lines, calculate measures of fit and statistical significance, and export cleaned data and statistical summaries.
Correct and improve existing MSTest tests using APIs supported by the installed version. Refine assertions and failure messages, update data-driven tests, fix setup and cleanup, and address MSTest diagnostics while preserving the project's established conventions.
Set up Claude Code hooks that block specified Git commands before they run, including push and destructive cleanup operations. Choose project or global installation, adjust the blocked commands, and test that the hook rejects a sample command.
Create and edit spreadsheet files, clean messy tables, and convert tabular formats. Add formulas, formatting, and charts while following existing template styles, then recalculate formulas and check for errors before delivering the spreadsheet.
Prepare survey and administrative datasets for analysis with Python, R, or Stata. Generate cleaning code to handle missing values, duplicates, outliers, and derived variables, with documented transformations and integrity checks that support reproducible research.
Use LeanCTX Context Gateway tools to select task-relevant code context, apply supported controls, reuse local knowledge and inspect recorded evidence. Use when lean-ctx MCP tools (ctx_*) are available or file, search or command output needs a focused view.
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[omh] Messy or AI-generated code to clean up: delete AI-generated slop, dead code, and duplication while observable behavior stays identical. Use when the user says: ai-slop-cleaner, cleanup, deslop, refactor, risky, behavior-preserving refactor, risk analysis, refactor workflow.
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Apply lean thinking to UX: hypothesis-driven design, collaborative sketching, and rapid experiments instead of heavy deliverables. Use when the user mentions "Lean UX", "design hypothesis", "outcome over output", "design studio method", "assumption mapping", "lightweight research", "too much design documentation", or "get the team designing together". Also trigger when reducing design-documentation overhead, getting cross-functional teams to co-design, or running fast usability experiments. Covers hypothesis statements, MVPs for UX, and cross-functional collaboration. For Build-Measure-Learn, see lean-startup. For usability audits, see ux-heuristics.
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Write readable, maintainable code through disciplined naming, small functions, and clean error handling. Use when the user mentions "clean up this code", "this function is too long", "code smells", "naming conventions", "boy scout rule", "single responsibility", or "unit test quality". Also trigger when reviewing a pull request for readability, untangling a messy function, debating comment styles, or improving error-handling patterns. Covers SRP, comment discipline, formatting, and unit testing. For refactoring techniques, see refactoring-patterns. For architecture and dependency rules, see clean-architecture.
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Guided journey from a raw app idea to a validated, cleanly architected first version that ships on a sustainable cadence. Orchestrates ten skills phase by phase - lean-startup, design-sprint, clean-architecture, domain-driven-design, clean-code, pragmatic-programmer, system-design, ios-hig-design, 37signals-way, software-design-philosophy - asking the user questions at every decision point and recording results in the project docs/ folder (PRODUCT.md, ARCHITECTURE.md, EXPERIMENTS.md, CREATE-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to build a new app, validate an idea before writing code, architect an MVP that will not need a rewrite, or says 'help me build my app the right way'. App already exists: use improve-app or grow-app. Business idea not yet validated: run create-business first. Marketing site only: use create-website. Architecture-only question: design-code-architecture. For one framework in isolation, invoke that skill directly.
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Build boolean and X-ray search strings to source candidates. Use when asked to build a boolean search, source candidates on LinkedIn/Google, write an X-ray search, or find people with specific skills. Produces ready-to-paste boolean strings (with synonyms, must-haves, and exclusions), X-ray variants for LinkedIn/GitHub, and a refinement plan to widen or narrow the result set.
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Use when targeting the Journal of Cleaner Production or deciding whether a cleaner-production/sustainability manuscript fits this venue. Encodes the journal's fit, the cleaner-production contribution and methodological-transparency bar, LCA/system-boundary expectations, house style, official-submission re-check, and desk-reject heuristics.
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Identify stale and empty Claude Code sessions in the Agent Monitor and explain the cleanup endpoint (POST /api/settings/cleanup), always showing the exact list of what WOULD be removed before anything is deleted. Cleanup permanently deletes data, so this skill previews first and requires explicit user confirmation. Use when tidying the monitoring database.
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Clean and normalize A-share financial data for modeling. Adapts the original clean-data-xls skill for Chinese financial statements, CAS conventions, and A-share data formats. Triggers on "A股数据清洗", "财务数据清洗", "clean financial data China", "数据清洗", or "normalize financial statements".
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Clean-code engineering standards for writing, refactoring, and reviewing code in any programming language. Use this whenever the user asks to write clean code, follow clean-code principles, refactor for clarity, improve naming, reduce complexity or duplication, separate concerns, tighten error handling, work test-first or do TDD, or otherwise raise code quality, readability, and maintainability. Also use when writing or reviewing Operately APIs or Ecto queries. Apply these rules by default when producing or changing code for a quality-conscious user.
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Integrate ManagedCode.Orleans.SignalR for grain-driven SignalR delivery, connection and group routing, offline user queues, and restart-safe state. USE FOR: Orleans backplane setup, grain-to-hub publishing, reconnect, heartbeat, and client-invocation failures. DO NOT USE FOR: ordinary SignalR without Orleans or unrelated persistence. INVOKES: inspect configuration, implement the integration, and validate connected-client delivery.
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Use when a clinical CSV/Excel dataset needs profiling and cleaning before analysis (missing values, outliers, duplicates, type mismatches). Profiles, flags and generates cleaning code in three stages, each gated on the researcher's approval. Never auto-cleans.
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Dead code and dependency cleanup, repo-wide: unused deps, unreferenced exports, unreachable code, orphaned files — removed only with tool evidence, in reversible waves. Runs on green main. For diff-scoped cleanup use absolute-simplify. Triggers on "absolute prune", "remove dead code", "find unused deps/exports", "what can we delete", "clean up orphaned files".
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Review or improve code — one skill, four modes: bug/security review (default), performance, clean-code audit, slop cleanup. Pass mode:review|perf|clean|cleanup or infer. Don't use for writing features or generating tests (use test-coverage).
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Evaluate and simplify Boolean expressions using truth tables, algebraic laws (De Morgan, distributive, absorption, idempotent, consensus), and Karnaugh maps for up to six variables. Use when you need to reduce a Boolean expression to its minimal sum-of-products or product-of-sums form, verify logical equivalence between two expressions, or prepare a minimized function for gate-level implementation.
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