Data & Analytics

yhy0 Bundle

Use when performing penetration testing targeting SQL injection vulnerabilities in web applications. Keywords: SQL injection, blind SQLi, union-based, error-based, time-based, second-order injection, ORM injection, parameterized queries bypass

yhy0 Bundle

Use when auditing Python code involving command execution (subprocess, os.system, os.popen), SQL queries (cursor.execute, sqlalchemy.text, ORM .extra/.raw), eval/exec calls, template rendering (Jinja2, Mako SSTI), or expression evaluation. Covers CWE-77/78/89/94/95/917. Keywords: command injection, SQL injection, code injection, eval, exec, template injection, expression language injection, Hydra instantiate, allow_dangerous_code

qusong0627 Bundle

股票市场深度数据分析与导出 — 全市场信号扫描、行业轮动、个股研报级深度分析（基本面/估值/技术/资金筹码/情绪/风险六维）、数据挖掘、CSV/Excel 导出。在 QuantBot / Claude Code 中分析股票市场、挖掘机会、导出分析数据、生成选股/投研报告时使用。触发词：分析市场、数据分析、数据挖掘、全市场扫描、行业轮动、导出数据、导出CSV、生成报告、投研分析、深度分析、挖掘机会、个股研报、个股分析

qusong0627 Skill

QuantDB 服务器数据结构与读取口径 — 数据目录组织（1_kline_data~6_ml_datasets）、Hive 分区规律（dt=YYYYMMDD 整数）、单文件 {symbol}.parquet、parquet 后缀式代码 600519.SH 与 PG 前缀式 SH600519 的转换口径、quantdb_hub.py 单一读取入口与 DuckDB 视图清单、服务器路径映射（/opt/quantmind/data/quantdb → 容器 /data/quantdb）。凡需要读写/探查/补数/验证 QuantDB 本地 parquet 数据、查目录结构、写 DuckDB 查询、排查查不到数据问题时使用。触发词：quantdb 结构、数据目录、dt 分区、hive 分区、parquet 路径、数据在哪里、600519.SH、代码格式、qdb_ 视图、quantdb_hub、增量同步、数据缺失排查

scoobydont-666 Skill

budi token/cost analytics for Claude Code — dashboard access, CLI queries, cost analysis patterns, session tracking. Trigger on: "budi", "token cost", "how much did that cost", "session cost", "spending", "token analytics", "cost dashboard", "usage stats", or any question about Claude Code token consumption or spending patterns.

scoobydont-666 Skill

Schema design, migration strategy, index planning, and data lifecycle for SQL databases (PostgreSQL, SQLite). Covers table design, normalization, foreign keys, migration tooling (Alembic, raw SQL), index optimization, retention policies, and schema review. Trigger on: "design schema", "database migration", "add table", "schema review", "index strategy", "data model", "retention policy", "normalize".

phoenixrr2113 Bundle

Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations. Use PROACTIVELY for business intelligence or strategic analysis.

srltas Skill

Look up CUBRID Migration Toolkit (CMT) behavior in the official online manual at www.cubrid.org/cmt_manual: source database support (Oracle, MySQL, MariaDB, MSSQL, Informix, Tibero, and more), data type mapping, migration wizard steps, console/CLI mode, reports, and configuration. Use when migrating a database to CUBRID and you need to verify what CMT supports, how a source type maps to CUBRID, or how a CMT option or console command works. For CUBRID engine SQL/JDBC questions, use the cubrid-manual skill instead. Triggers on phrases like 'CMT', 'CUBRID Migration Toolkit', 'migrate X to CUBRID', 'CMT type mapping', 'how does CMT handle', 'CMT console mode'.

srltas Skill

Look up CUBRID engine behavior in the official online manual: SQL syntax, built-in functions, data types, identifiers and reserved keywords, configuration parameters, and JDBC/driver APIs. Fetches the version-pinned manual at www.cubrid.org/manual. Use when you need to verify CUBRID SQL semantics, a function signature, a data type's range, whether a word is reserved, or a config parameter before writing dialect or JDBC code. For CUBRID Migration Toolkit (CMT) questions, use the cmt-manual skill instead. Triggers on phrases like 'how does X work in CUBRID', 'CUBRID syntax for', 'is X a reserved word in CUBRID', 'what functions does CUBRID have', 'check the CUBRID manual'.

srltas Skill

Turn a list of JIRA issue keys into one short Korean line per issue, ready to paste into a weekly-report spreadsheet (one line per cell). Give it several keys (e.g. APIS-1111, TOOLS-4324) and it fetches each issue with the jira-fetch skill, reads the description, and compresses it into a single 개조식 line ending in 명사형: 대상 + 무엇을 하는가, no procedures or checklists. Summarizes what the issue IS, not progress or status. Use when writing the weekly report and you need each issue boiled down to one line. Triggers on phrases like '주간보고 정리', '주간 보고용으로 요약', '이 이슈들 한 줄로 정리', '주간보고 한 줄씩 만들어줘', 'weekly report lines for these issues'.

carapace-sh Bundle

Use when working with the bun CLI — Bun's all-in-one JavaScript runtime and toolkit. Covers the CLI command reference (install, add, remove, run, build, test, x, create, init, pm, upgrade, link, unlink), bunfig.toml configuration, environment variables, the package manager and lockfile, the test runner, the bundler, the Bun runtime API (Bun.serve, Bun.file, Bun.spawn, Bun.write, hashing, transpiler), the Bun shell ($ template literal), module resolution and loaders, and globals. Triggers on: "bun", "bunx", "bun install", "bun add", "bun remove", "bun run", "bun build", "bun test", "bun x", "bun create", "bun init", "bun pm", "bun upgrade", "bun link", "bun unlink", "bunfig.toml", "bun.lock", "Bun.serve", "Bun.file", "Bun.write", "Bun.spawn", "Bun.hash", "Bun.password", "bun:test", "Bun.build", "Bun.Transpiler", "bun shell", "$ template", "import.meta", "JavaScriptCore", "Bun.serve", "HTMLRewriter", "Bun.SQL", "Bun.RedisClient", "Bun.Glob", "Bun.plugin", "bun:ffi".

ebarti Bundle

Data modeling, storage engines, and encoding choices distilled from "Designing Data-Intensive Applications" (Kleppmann, 2nd ed) chapters 3-5. Covers relational, document, graph, and event-sourced models; LSM, B-tree, in-memory, and columnar storage; specialized indexes; encoding formats; and modes of dataflow. Use this skill when: - Choosing a database (relational/document/graph) - Picking a storage engine (LSM/B-tree/columnar) - Designing an analytics warehouse - Selecting a wire format (JSON/Avro/Protobuf) - Deciding REST vs RPC vs messaging - Modeling event-sourced systems - Building search/vector/geo indexes

ekkolearnai Bundle

Create, inspect, edit, restructure, recalculate, convert, and visually verify Excel .xlsx workbooks and CSV data.

fattain-naime Bundle

Define who a product is for, what they're trying to accomplish, how success is measured, and what to instrument to know if it's working. Covers user personas (goal- and behavior-based, not demographic), jobs-to-be-done, success metrics/KPIs, and an analytics/event-tracking plan. Use before or alongside requirements gathering so "who is this for and how do we know it's working" is answered explicitly.

findinfinitelabs Skill

Parse JW.org NWT EPUBs to extract individual Bible verses for verse previews, parallel-corpus building, and Bible-coverage analytics. Use when working with NWT EPUB files, building parallel Chuukese↔English Bible data, or wiring scripture preview features.

hiboys Bundle

基于东方财富数据库，支持自然语言查询全球宏观经济数据，涵盖国民经济核算、价格指数、货币金融、财政收支、对外贸易、就业民生、产业运行等多个领域，适配各类宏观经济研究、市场分析、政策解读等多元专业场景需求。返回结果包含数据说明及 csv 文件。Natural language query for macroeconomic data from financial databases, covering national economic accounting, price indices, monetary finance, fiscal revenue and expenditure, foreign trade, employment, industrial operation, and other fields. It supports diverse scenarios including macroeconomic research, market analysis, and policy interpretation.

hiboys Bundle

基于东方财富数据库，支持自然语言查询金融数据，覆盖A港美、基金、债券等多种资产，含实时行情、公司信息、估值、财务报表等，可用于投资研究、交易复盘、市场监控、行业分析、信用研究、财报审计、资产配置等场景，适配机构与个人多元需求。返回结果包含数据说明及 xlsx 文件。Natural language query for financial data across all markets, including A-shares, ETFs, bonds, Hong Kong and US stocks, and funds. It provides L1/L2 data, financial indicators, company profiles and valuation metrics. Ideal for investment research, strategy backtesting, market monitoring and industry analysis. It meets the needs of diverse institutions and individuals.

hiboys Bundle

基于东方财富数据库，支持通过自然语言输入筛选A港美股、基金、债券等多种资产，支持多元指标筛选，含技术面、消息面、基本面及市场情绪等，可用于全球资产速筛、跨市场监控、投资组合构建、策略回测等场景。返回结果包含数据说明及 csv 文件。Natural language screener for investment assets across global markets, including A-shares, ETFs, bonds, HK and US stocks, and funds. It enables multi-dimensional filtering via technical, fundamental, sentiment and news indicators. Ideal for global asset selection, cross-market monitoring, portfolio construction and strategy backtesting.

hiboys Bundle

金融领域的可比公司分析工具，通过行业分析法对目标公司与可比公司整合经营指标、估值倍数和统计基准比较。目前仅支持A股上市公司分析。输入单一公司问句后，调用可比公司接口并生成主题化Excel报告。适用于快速对比目标公司与同业在经营、财务、估值维度的差异。

ivy-interactive Bundle

Convert an Excel (.xlsx) document to an Ivy project. Use when the user wants to migrate from Excel, convert a spreadsheet, import Excel data, or build an Ivy app from an .xlsx file. Uses the ivy-inspector-excel CLI tool to inspect and extract data from Excel files.

ivy-interactive Bundle

Create a Dashboard app with metrics, charts, and KPIs for an Ivy project. Use when the user asks for a dashboard, analytics page, KPI view, reporting view, data visualization app, or metrics overview. Handles MetricView cards, line charts, bar charts, pie charts, area charts, date range filtering, and grid layouts.

ivy-interactive Bundle

Add a database connection to an Ivy project. Supports SQL Server, Postgres, Supabase, MySQL, MariaDB, SQLite, Airtable, Oracle, Spanner, ClickHouse, and Snowflake. Scaffolds a DbContext from an existing database with Entity Framework. Use when the user wants to connect to a database.

pubnub Bundle

Routes PubNub questions to the correct documentation source, MCP tool, and specialist skill. Classifies intent (chat vs non-chat, conceptual vs implementation, runtime testing vs analytics) and points the agent to the right next step. Use when a user mentions PubNub for the first time, asks "where do I start", "which docs", "what should I use", or any time the appropriate next skill is unclear.

researai Bundle

Use when structured numeric data, arrays, or CSV-like measurements should be turned into a publication-quality figure by adapting a bundled paper-style plotting template instead of improvising a new chart from scratch.

roebi Bundle

Creates a Swiss-law-compliant Datenschutzerklärung (Privacy Policy) for websites operated from Switzerland or targeting Swiss users. Guides the user through an interactive data-inventory phase covering all processing activities (hosting, fonts, analytics, contact forms, cookies, external embeds, etc.), then generates a ready-to-publish Privacy Policy in German and/or English. Covers obligations under nDSG (in force 01.09.2023), DSG Art. 19, and where relevant DSGVO (for EU visitors). Activate for phrases like: "create a privacy policy", "Datenschutzerklärung erstellen", "I need a privacy policy for my Swiss website", "nDSG privacy policy", "DSGVO Datenschutz", or "create privacy policy switzerland".

scalably-io Skill

Extract a contact email for each domain in a list (no niche or quality filtering, assumes the domains are already vetted). Scrapes common contact paths first, falls back to an email-lookup API only when scraping finds nothing, and delivers a CSV (or a markdown table for small batches) with one row per input domain, never silently dropping one. Triggers: find emails, extract emails, contact emails, email list, find contacts, emails for these sites, emails from domains, email extraction, contacts CSV, contacts sheet.

openinterpreter Bundle

Audit a spreadsheet for formula accuracy, errors, and common financial-model mistakes. Use for selected ranges, single sheets, or whole-workbook model checks including balance-sheet balance, cash tie-out, roll-forwards, and logic sanity.

openinterpreter Bundle

Produce a .xlsx workbook file on disk for headless sessions or artifact-based workflows instead of driving a live Excel workbook. Use when the user needs a workbook artifact created or updated from data and instructions.

openinterpreter Bundle

Create, inspect, analyze, and edit spreadsheets (`.xlsx`, `.xlsm`, `.csv`, `.tsv`) with local code execution. Use for formulas, formatting, charts, validation, financial models, and spreadsheet deliverables.

kappmaker Skill

Set up Firebase for a KAppMaker app — project, Android and iOS apps, and the google-services config files. Use when the user asks to set up Firebase, add google-services.json or GoogleService-Info.plist, or enable Firebase auth or analytics.

browseros-ai Skill

Extract structured data from web pages — tables, lists, product info, pricing — into clean CSV, JSON, or markdown tables. Parallelizes across hidden tabs for multi-source extraction and saves results to disk incrementally. Use when the user asks to scrape, extract, or pull data from a page.

ccfos Skill

Generate SQL query statements from natural language (supports MySQL/Doris/ClickHouse/PostgreSQL)

ccfos Bundle

Query data from various datasources in a Nightingale (n9e) environment. Supports Prometheus metric queries, Elasticsearch/Loki log queries, and SQL datasource queries such as ClickHouse/MySQL/PostgreSQL/TDengine/Doris. Use when the user asks to query metrics, view monitoring data, search logs, or run PromQL or SQL queries.

proyecto26 Bundle

This skill should be used when the user asks "SQL or NoSQL", "which database", how to design a "data model" or "schema design", picks an "indexing" strategy, needs "sharding" or "partitioning", sets up "replication" (leader-follower / multi-leader), defines a "primary key"/"sort key", asks whether to "denormalize", or weighs "polyglot persistence". Use it whenever a design must decide where records live, how they are keyed and accessed, and how the store scales past one node — even if the user just says "store the data".

novainsilico Bundle

Create, generate, inspect, or work with Jinkō virtual populations (vpops) and vpop designs via the jinko-sdk. Use this skill whenever the user wants to upload a vpop from CSV or pandas DataFrame, create a vpop generator from marginal distributions, generate a vpop from a vpop design, inspect vpop content/statistics, or edit an existing vpop design. Vpops generated or uploaded as Vpop project items are not editable; edit the vpop design instead and regenerate.

novainsilico Bundle

Create, sanity-check, run, poll, and download results for Jinkō in-silico trials via the jinko-sdk. Use this skill whenever the user wants to set up a trial from a computational model and simple output set, optionally attach a vpop, protocol, data table, or advanced scoring output set, launch a trial, wait for completion, inspect completed trials, or download TimeSeries and Scalar results as pandas DataFrames. Do not use this skill for model editing, vpop creation, protocol design authoring, data-table upload, output-set creation/editing, or trial visualization.