「columns」の検索結果

Use when working with Mariadb — mariaDB Galera cluster status, MaxScale routing, ColumnStore engine analysis, performance schema tuning, and replication health.

日本語の概要は準備中です。原文の説明を表示しています。

Postgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pg_cron, pgmq), vector/semantic search (pgvector), and restoring dumps (pg_restore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used when the user asks to "automate SQL injection testing," "enumerate database structure," "extract database credentials using sqlmap," "dump tables and columns from a vulnerable database," or "perform automated database penetration testing." It provides comprehensive guidance for using SQLMap to detect and exploit SQL injection vulnerabilities.

日本語の概要は準備中です。原文の説明を表示しています。

Busabase-backed App-in-Skill money ledger for aggregating Mercury, Stripe, Airwallex, and Creem accounts into a read-only dashboard. Use when the user invokes $kelly-money or /kelly-money, wants a total cashflow ledger, account columns, Accounts sidebar, Account Detail views, finance onboarding, connector setup, transaction import/sync, reconciliation, balances, payouts, payments, fees, refunds, transfers, or a review of money movement across these providers.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

日本語の概要は準備中です。原文の説明を表示しています。

Change the sync configuration of an existing data warehouse schema — switch sync_type, pick a different incremental_field, set primary_key_columns, choose cdc_table_mode, or change sync_frequency. Use when the user asks "switch my orders table from full refresh to incremental", "this table is syncing too slowly / too frequently", "I need to pick a different incremental column", "set up CDC for this Postgres table", or when diagnosis of a failing sync pointed to an incremental-field or PK misconfiguration.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

日本語の概要は準備中です。原文の説明を表示しています。

Review and rank an entire SCF round end-to-end from a CSV export. Supports Open Track, Integration Track, and RFP Track with track-specific scoring dimensions. Reads submission data directly from an Airtable CSV, auto-detects columns, categorizes, runs parallel batch reviews, cross-batch calibration, and final ranking. All output is markdown. Use when you have a CSV export of an SCF Build Award round and need to review, score, and rank every submission.

日本語の概要は準備中です。原文の説明を表示しています。

Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues before phylogenetic inference, HMM building, or selection analysis.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

日本語の概要は準備中です。原文の説明を表示しています。

Pro-camera HUD mockup template — full-viewport black canvas wrapping a real video with monospace overlays (corner brackets, top status bar, side AF/exposure columns, bottom timecode + aperture/shutter/ISO row, vertical 8-filter wheel, animated reticle). For cinematographer portfolios, camera-app demos, LUT pack previews, filter-look auditions. NOT a TikTok/Reels mockup, NOT a storyboard, NOT a shot list, NOT a script document. The chrome wraps real footage — never a div placeholder.

日本語の概要は準備中です。原文の説明を表示しています。

Scrap and regenerate the in-flight EF migrations on the current branch as one consolidated migration. Use when migrations have accumulated mid-development cruft (added/removed columns, stacked add-column-to-existing-table fixes, hand-edited SQL that needs to come out, schema changes that should have been one migration but ended up as five), or when the branch has merged main and its migrations are now stuck mid-chain so `dotnet ef migrations remove` is unsafe. Triggers on phrases like 'regen the migrations', 'redo these migrations', 'scrap and regen migrations', 'consolidate the in-flight migrations', 'redo the migration stack', or any time an agent hits the mid-chain situation in `memory/architecture/migration-regen-after-rebase.md`.

日本語の概要は準備中です。原文の説明を表示しています。

Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues before phylogenetic inference, HMM building, or selection analysis.

日本語の概要は準備中です。原文の説明を表示しています。

Moves a person's whole Notion workspace into AI Matrx using only the AI Matrx and Notion connectors — every page and sub-page becomes an AI Matrx page (a Space) with its blocks, icons, covers, files and comments, and every database becomes a real table with typed columns, links, roll-ups, row pages, templates and views. Safe to run again; nothing duplicates. Use when the person says "move my Notion into AI Matrx", "copy my Notion", "import my Notion", or anything like it.

日本語の概要は準備中です。原文の説明を表示しています。

The one association system (platform.associations) and schema-qualified table refs. Use when touching an M2M junction table, an associate_*/attach_*/tag_* RPC, FK columns used as tags, a 'things attached to X' list or card, or a PGRST205 / 42703 table-not-found on a bare .from().

日本語の概要は準備中です。原文の説明を表示しています。

Approved table usage rules. Use when configuring, migrating, or reviewing MatrxDataTable columns, toolbars, or pagination.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill when building or debugging table usage with nuxt-ui-tools as a package consumer. Covers defineTableSchema, useTable, DataList, granular composition, columns, filters, sorting, offset or cursor loading, layouts, actions, selection, context, and URL state with concrete examples.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

日本語の概要は準備中です。原文の説明を表示しています。

Expert GNU awk (gawk) one-liner generation and transformation. Use this skill whenever the user asks to process text fields, extract columns, compute sums or aggregates, filter structured output, reformat CSV/TSV, parse logs, generate reports, or do any record/field processing task. Trigger on keywords like "awk", "extract column", "sum a field", "count occurrences", "print field N", "filter by column", "reformat output", "aggregate log data", "process CSV", "TSV", or any request that maps to a field-oriented text transformation. When in doubt, use this skill — awk is often the right tool when sed isn't enough.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

日本語の概要は準備中です。原文の説明を表示しています。

Generate formatted video scripts from transcripts, outlines, or topics with visual and audio columns

日本語の概要は準備中です。原文の説明を表示しています。

Manage database schema with Drizzle ORM and SQLite migrations. Use when adding tables, modifying columns, creating indexes, or running migrations. Activates for database schema changes, migration generation, and Drizzle query patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Supabase Postgres + Storage + Auth operations from FastAPI — service-role client, RLS-aware queries, additive SQL migrations under backend/db/migrations, the create_order RPC, and the product-images bucket. Use when adding tables/columns, writing queries, calling RPCs, or working with Storage.

日本語の概要は準備中です。原文の説明を表示しています。