「schema」の検索結果

Comprehensive SEO analysis for any website or business type. Full site audits, single-page analysis, technical SEO (crawlability, indexability, Core Web Vitals with INP), schema markup, content quality (E-E-A-T), image optimization, sitemap analysis, and GEO for AI Overviews/ChatGPT/Perplexity. Industry detection for SaaS, e-commerce, local, publishers, agencies. Triggers on: SEO, audit, schema, Core Web Vitals, sitemap, E-E-A-T, AI Overviews, GEO, technical SEO, content quality, page speed.

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。

Bringing an existing table onto the platform base standard. Use when asked to canonicalize, retrofit, or 'Wave 3' a table, run apply_rls or an org backfill, retire a bespoke *_versions table, or move it onto platform comments/associations/permissions. NOT for a schema move (use db-move-table-schema).

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。

Retiring a dead table by moving it to the deprecated schema and clearing every reference in both repos. Use when asked to deprecate or retire a table, when a table is no longer used, or to take a table offline without dropping it. NOT for relocating a still-used table (use db-move-table-schema).

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。

Locate CCSPlayerInventory::m_pSOCache in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the WeaponPaints gamedata entry "CCSPlayerInventory::m_pSOCache" (symbol CCSPlayerInventory_m_pSOCache). This is a STRUCT MEMBER OFFSET (schema netvar). Resolve the CCSPlayerInventory class layout via the schema system; m_pSOCache is the CGCClientSharedObjectCache pointer member. Cross-check: CCSPlayerInventory methods load this pointer and pass it to CGCClientSharedObjectCache methods (the GetItemInLoadout shortlist is a strong caller-side witness). Trigger: CCSPlayerInventory_m_pSOCache, CCSPlayerInventory::m_pSOCache

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。

Locate CCSPlayerController_InventoryServices::m_pInventory in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the WeaponPaints gamedata entry "CCSPlayerController_InventoryServices::m_pInventory" (symbol CCSPlayerController_InventoryServices_m_pInventory). This is a STRUCT MEMBER OFFSET (schema netvar), not a function. Resolve the CCSPlayerController_InventoryServices class layout via the schema/network system; m_pInventory is an 8-byte pointer member early in the class (must stay 8-aligned). Cross-check: functions of the class dereference this->m_pInventory shortly after entry. Trigger: CCSPlayerController_InventoryServices_m_pInventory, CCSPlayerController_InventoryServices::m_pInventory

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。

Locate CBaseEntity::m_iTeamNum in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the local gamedata entry "CBaseEntity::m_iTeamNum" (symbol CBaseEntity_m_iTeamNum). This is a STRUCT MEMBER OFFSET (schema netvar), not a function. Resolve the CBaseEntity class layout via the schema/network system; the member must satisfy natural alignment. Cross-check with functions that dereference the member. Trigger: CBaseEntity_m_iTeamNum, CBaseEntity::m_iTeamNum

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。

Codex Plan Mode 専用。docs/PLAN/{YYMMDD}_{slug}/ に schema v3 仕様書を作成する。 Gate 契約 (Goal / Constraints / Acceptance Criteria)、Mermaid 図、Cursor Agent 委任ヒントを含む。 Trigger: spec-codex

docs/PLAN/{YYMMDD}_{slug}/ の schema v3 仕様書を Codex で Gate 単位に実行する。 tasks.json を正とし、Gate 契約 (Goal/Constraints/AC) に基づいて実装・検証・レビューを行う。 Trigger: spec-codex-run, spec-run

Plans Convex schema and data migrations with widen-migrate-narrow and @convex-dev/migrations. Use for breaking schema changes, backfills, table reshaping, or zero-downtime rollouts.

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。

Plan and execute Convex schema migrations safely, including adding fields, creating tables, and data transformations. Use when schema changes affect existing data.

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 analytics dashboards with nuxt-ui-tools as a package consumer. Covers schema and view functions (defineDashboardSchema, defineDashboardView) that take their context as typed params, useDashboard with a getter that rebuilds on input change, typed injection (useDashboardView, injectDashboard, InferDashboard, InferDashboardView), filters declared inline with the f builder and synced with the URL, memory, or an external store (one value per key across views), headless filters, filter controls and the shipped UI (UiDashboardPage, UiDashboardFilters, UiDashboardFilter, UiDashboardViewTabs) with slot overrides, remote paginated pickers and remoteTableOptions, staged queries (essential / background / deferred) with select and dependent requires, lazy enabled conditions on views, queries, and filters (blocks of disabled queries hidden, grids closing up), derived values, views (tabs), query-scoped filters, number formats (presets, Intl options, useDashboardFormat), and the dashboard blocks (stats with trends, goals, and comparisons, stat groups, gauges, unovis charts with highlights, value labels, and totals, lists with progress rings, bars, funnel, alerts, activity feeds, sortable tables, custom widgets) with their automatic loading, error, empty, and refresh states, card menus, header and footer actions, row actions, drill-down and selected state, card tabs, split cards, comparison periods, auto-refresh, and data freshness.

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 wiring nuxt-ui-tools translations in an app. Covers UiToolsProvider, locale objects, lazy schema text, and how package-owned UI copy differs from schema-owned text.

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 or edit images using AI models (FLUX, Gemini). Use for general-purpose image generation including photos, illustrations, artwork, visual assets, concept art, and any image that isn't a technical diagram or schematic. For flowcharts, circuits, pathways, and technical diagrams, use the scientific-schematics skill instead.

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。

Complete SEO + GEO (Generative Engine Optimization) system for SaaS companies wanting to rank on both Google and AI search engines (ChatGPT, Perplexity, Gemini, Claude). Use this skill whenever the user asks about SEO strategy, keyword research, content planning, writing SEO-optimized articles, auditing their search performance, creating a content calendar, analyzing competitors, or optimizing for AI search visibility. Trigger on: "seo", "keyword research", "content calendar", "rank on google", "search traffic", "write an article", "blog post", "serp", "backlinks", "competitor analysis", "content cluster", "seo audit", "geo optimization", "ai search", "search console", "organic traffic", "content strategy", "publish article", "seo setup", "ranking", "impressions", "ctr", "meta description", "schema markup", "faq schema". Also trigger when a user wants to set up their SaaS blog SEO from scratch, analyze their current rankings, or create a publishing workflow.

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。

Skill for graphql-schema-design tasks.

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 when a new feature needs a table, column or capability — evolving the schema so the new thing joins the permission, audit and RLS contract instead of sitting outside it. Covers the DDL/DML split, the resource/capability wiring, and the self-verifying migration.

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 FIRST when someone asks for a new feature or a change to an existing one — before any schema, code or test. Works out what is actually being asked for, whether to build it or integrate a third party (Trustpilot, Stripe, Calendly and the like), where the data lives, who may do what, and what happens when the vendor is down. Produces a decision, then hands to feature-schema.

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。

Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementa

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。

AI-powered autonomous data extraction that navigates complex sites and returns structured JSON. Use this skill when the user wants structured data from websites, needs to extract pricing tiers, product listings, directory entries, or any data as JSON with a schema. Triggers on "extract structured data", "get all the products", "pull pricing info", "extract as JSON", or when the user provides a JSON schema for website data. More powerful than simple scraping for multi-page structured extraction.

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 validated JSON-LD structured data markup for any page type

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。

OpenClawの既存ドキュメントを、仕様や操作の説明をソースで確かめながら再構成し、詳細の移動先やリンク、書式まで検証するスキル。

• 仕様説明を保ちながらページを短くしたいとき
• 詳細仕様を参照ページへ分けたいとき
• 説明を現在のCLIの動作に合わせたいとき

コードやデータ、APIの変更前に、実際の依存関係から影響範囲と必要な検証・復旧手順を整理し、実装後の差分と照合して見落としや範囲のずれを確認します。

• API変更の影響範囲の確認
• データベース移行と復旧計画の点検
• 認証変更のモジュール間影響の確認

検索に見つけてもらいやすいサイトを目指し、技術的な問題、ページの見出しや説明文、構造化データ、表示性能を点検し、ページごとの改善案と実装を進めるスキル。

• 検索に登録されない原因を調べたいとき
• タイトル・説明文・見出しの改善
• 記事や商品の構造化データ追加

医療アプリの患者・職員の機密情報を分類し、施設単位のアクセス制御や監査記録を設計するとともに、ログ・URL・ブラウザー保存からの情報漏えいを点検するスキル。

• 患者記録を扱うコードの点検
• 医療施設間のアクセス制御の設計
• 機密情報の閲覧・変更の監査記録