Data analysis, machine learning, LLM apps, and prompt design (9.1K skills)
Fetch Airbnb income estimate (ADR, occupancy, monthly revenue) for any area using the official Airbnb GraphQL API — the same data the Airbnb host simulator shows. Input: station/area name. Output: per-night rate, avg nights, monthly estimate for entire_home and private_room.
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ScalarDB Analytics設計エージェント - ScalarDB Analyticsを使用した分析基盤の設計。Apache Sparkベースの分析クエリ、マルチDB横断分析を策定。/design-scalardb-analytics [対象パス] で呼び出し。
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データモデル分析エージェント - 既存のデータモデルを分析し、エンティティ・リレーションシップ・ドメインルールを抽出。/data-model-analysis [対象パス] で呼び出し。
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Searches the web for facts, news, and data.
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Intelligent README.md generation prompt that analyzes project documentation structure and creates comprehensive repository documentation. Scans ./ directory files and creates a README.md file for the project. Only used when creating a new repository. or when the README.md file is missing.
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Creates an llms.txt file from scratch based on repository structure. Use when configuring LLM discovery files. For updating existing configurations, see update-llms.
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E-commerce product-management desk (Busabase App-in-Skill) for catalog master data, SKUs, pricing, inventory, channel status, content assets, compliance notes, lifecycle state, and approval-gated product operations. Use when the user invokes $kelly-products or /kelly-products, asks for 电商商品管理, 商品库, SKU 管理, inventory/reorder, product status across Amazon/Shopify/TikTok Shop/eBay, channel publishing approvals, price-change review, quality holds, product lifecycle/archive decisions, or a Busabase-backed product management desk.
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Busabase-backed App-in-Skill dashboard for a shared LLM gateway's cost and model governance — daily spend trend, cost breakdown by service/model, a canary-rollout status board, and a deterministic cost/error anomaly list. Use when the user invokes $kelly-llm-gateway or /kelly-llm-gateway, or wants to review LLM gateway spend, model routing, canary rollouts, rollback readiness, or cost/error anomalies for services routed through one shared gateway to multiple LLM providers/models. Human actions (promote/rollback/hold a rollout, acknowledge an anomaly) write directly onto the route's own Busabase record — this skill never changes a real routing config.
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Busabase-backed App-in-Skill control panel / kanban board for a BD or sourcing team triaging merchant and business financing leads for a lender or investment fund. Use when the user invokes $kelly-lead-funnel or /kelly-lead-funnel, wants to review the deal sourcing pipeline, funnel, lead board, or asks to move a lead's stage, reject a lead, add a note, score a lead, or see funnel conversion rates. Deterministic rule-based lead scoring only — never an LLM call — and never sends outreach, signs term sheets, or moves money.
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Insurance-industry App-in-Skill for read-only data governance, backed by an operator-provisioned Busabase workspace (one Drive node for the file drive plus four Bases for QA pairs, featured information, insurer notices, and user feedback) and trusted export/restore/PDF-text-backfill scripts. Use when the user invokes $kelly-insure-data or /kelly-insure-data, wants an insurance data workspace with UI, needs to review insurance files, metadata completeness, QA pairs, featured information, insurer notices, or user feedback, wants to back up or restore a Kelly Insure Data Busabase workspace from local PDFs, or wants Busabase Drive/Base data surfaced for data quality review and ongoing data governance.
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Busabase-backed App-in-Skill low-code agent configuration and governance console for a platform team. Use when the user invokes $kelly-agent-builder or /kelly-agent-builder, wants to review or edit a catalog of mock LLM agent configs, check quota usage, find configs that need attention, move a draft to live, pause a live agent, or archive an agent. Mock config/governance console only — it never provisions or calls any real agent.
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Busabase App-in-Skill dashboard over a fixed, deterministic mock user-behavior funnel dataset (browse → search → compare → booking attempt/abandon → complete) for a generic consumer booking product. Use when the user invokes $kelly-behavior-predict or /kelly-behavior-predict, wants to review funnel drop-off, per-segment predicted next actions, or backtest a rule-based "predicted next action" heuristic against a mock historical sample. Fully deterministic mock data and a hand-recomputable rule — never a real ML/LLM model, never a live system.
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Run a Busabase-backed sandbox desk for scoring and triaging course-instructor ("讲师") candidates found on a recruiting-style platform. Use whenever the user invokes $kelly-instructor-sourcing or /kelly-instructor-sourcing, wants a lightweight instructor candidate tracker, needs to score sourcing-platform leads against a three-axis rubric (background endorsement, expertise depth/breadth, teaching-service ability) before reaching out, or wants to log a WeChat add without building a live-connected outreach tool. Three subcommands - setup, criteria, review - plus the desk itself. v1 is sandbox-only — every dataset is deterministic mock data, it never connects to a real sourcing-platform or messaging account, and it never sends a message or automates a WeChat add - that stays entirely human-performed outside the app.
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Extract balance sheet, income statement, shares outstanding, organic growth, and GAAP reconciliation data from financial PDFs. Standardize via Tiger-Transformer and append structured output to the document markdown.
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Execute a single deterministic Python script to compute all derived financial metrics (EBITA, Invested Capital, Tax Rates, Summary Table) from extracted financial data.
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Use after changing prompts, skills, the compiler, or editorial policies — or when the user asks to measure edit quality, run regression evals, check agreement with approved edits, or says '評価して', '一致率を測って', 'eval を回して'. Compares agent output against human-approved golden projects.
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Tauri v2 (Rust + WebView のデスクトップ / モバイルアプリフレームワーク、Electron とは別) リファレンス。 tauri.conf.json, tauri CLI, command / invoke / Channel, AppHandle, Tauri capabilities / permissions (ACL), @tauri-apps/api, 公式プラグイン (fs, dialog, updater, store, sql), sidecar, 署名・配布, WebDriver。
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Kotlin (JetBrains 製プログラミング言語, kotlinlang.org) の言語仕様・標準ライブラリ・ツールチェーン。 null safety, data class, sealed class, 拡張関数, context parameters, スコープ関数 (let / run / apply / also / with), コレクション, Uuid, Duration (kotlin.time), kotlinx.coroutines (suspend, Flow), kotlinx.serialization (@Serializable, Json, ProtoBuf, CBOR), KGP, Maven, KSP, kapt, K2, KDoc。
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Expo (React Native フレームワーク, Expo SDK 58 / EAS) のリファレンス。 Expo Router (file-based routing, expo-server, data loaders, +api.ts), app.json / app.config, config plugins, Expo Modules API, expo-* SDK, Expo UI, EAS Build / Update / Submit / Workflows, eas.json, expo-updates (OTA), CNG / prebuild, Expo CLI (npx expo), development build (dev-client), expo-notifications push。
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Rules for the shared MatrxDataTable and its drill-down. Use when configuring, migrating or reviewing table columns, filters, toolbars, record links or pagination, adding group-by, 'by X' analytics or counts and sums by status, owner, model or day, or replacing hand-built totals or lists.
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Rust 製ローカルファースト vector 特化クエリ DB fandhe-db (PostgreSQL wire protocol v3 互換) の fandhe-db-engine / fandhe-db-wire-server リファレンス。 USING PLAN / USING OPERATION_ID 構文、DDL / JOIN / CTE / window 関数、 拡張クエリ・COPY・トランザクション、TLS 1.3 / SCRAM-SHA-256、 NoSQL HTTP 表層、precision・recall モード、HNSW / BM25 / RRF hybrid / rerank、 redb 永続化、tenant・RLS、SIMD / wgpu、wire_code エラー契約。
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Hand off a task with only the context needed to continue in a fresh session. Use for "handoff", "引き継ぎ", "別セッションへ渡す", or "別マシンで続ける". The orca subcommand launches an independent Orca workspace or terminal tab; without it, produce a paste-ready prompt backed by a verified remote branch or PR. Do not launch sessions for capability questions or design requests.
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Manual-only orchestrator for medium-to-large software development. Turns a broad goal into PR-sized and operational nodes with verification gates, then coordinates approved execution across follow-up prompts. Activate only when the user explicitly invokes my-epic; once activated, keep orchestrating that epic for the rest of the session. Do NOT use for an uninvoked planning or implementation request, a single small bug fix, one obvious PR, pure code review, ordinary SDD work that fits in one spec/PR, or implementing an epic during the same first call that created it.
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Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.
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