Data & Analytics

cartodb Skill

Builds territory planning workflows in CARTO combining territory balancing and location allocation. Triggers when the user mentions territory balancing, territory planning, sales territories, service zones, workload distribution, balanced territories, location allocation, facility placement, optimal locations, maximize coverage, minimize cost, minimize travel distance, depot placement, hub placement, warehouse siting, response time optimization, demand coverage, or wants to divide an area into balanced regions or find optimal facility locations.

cartodb Bundle

Author, edit, publish, and validate CARTO Builder maps. Use when the user wants to create a map from a natural-language request, edit an existing map (datasets, layers, styling, privacy, popups, widgets, SQL parameters), duplicate one, upload custom marker icons, or wire up an AI agent on a map. Routes to the CARTO MCP server's map tools (`create_map`, `update_map`, `validate_map`, `read_maps`, `view_map`) when attached, and to the `carto maps` CLI — `create`, `update`, `delete`, `publish`, `validate`, `schema`, `agents`, `markers`, `screenshot`, `copy`, `datasets update` — for scripted/bulk authoring, cross-org copy, screenshots, or when the server isn't attached.

cartodb Skill

Preview an existing saved CARTO Builder map inline in the chat via the CARTO MCP server — resolve the map with read_maps (by name or search), then render it with view_map by map ID. Use whenever the user references a saved Builder map — by URL, by ID, or by name. Renders a lightweight read-only preview (layers, basemap, viewport, popups, legend). Widgets, SQL parameters, map description, and other Builder-only features are NOT included; the user can click "Open in Builder" for the full experience. Triggers on "show me the X map", "open the Y map", "preview the Z map", and inline previews of a freshly-created map. Distinct from carto-create-builder-maps (authoring), carto-render-inline-map (ad-hoc deck.gl spec), and carto-develop-app (developer app).

cartodb Bundle

Write spatial SQL against the connected warehouse — dialect-specific guidance, performance defaults, and CARTO's query/job execution model.

cartodb Bundle

Choose and configure the data warehouse engine connection for CARTO (BigQuery, Snowflake, Redshift, Postgres, Databricks, Oracle).

cartodb Bundle

Discover what's in the connected warehouse — schemas, tables, columns, and CARTO named sources.

dolphindb Bundle

DolphinDB data import guide for IoT and general scenarios. Covers CSV/TXT, JSON, binary, plugin-based (HDF5, Parquet, MySQL, ODBC), and IoT real-time ingestion (MQTT, OPC UA). Includes IOTDB engine, date/time conversion, array vector import, null handling, and binary record import. Does NOT cover database administration, permission management, stream compute engine configuration, or data export.

dolphindb Bundle

将CSMAR历史数据文件自动导入DolphinDB数据库，支持csv及zip格式的数据文件

dolphindb Bundle

为 DolphinDB / DolphinScript SQL 编写、审查和优化提供规则集。 Use when 用户需要编写、改写、审查或优化 DolphinDB SQL，包括 select/exec/update/delete、 where 条件、group by/context by/cgroup by/pivot by、aj/wj/pwj、时间窗口、数组向量、 SQL 元编程、分布式 SQL、执行计划和 SQL Trace。

dolphindb Bundle

为 DolphinDB / DolphinScript 基础语法、脚本骨架和初版代码生成提供规则集。 Use when 用户需要从自然语言生成可执行 DolphinDB 脚本、修复 DolphinScript 语法错误、 检查变量赋值、函数定义、索引切片、数据结构构造、字符串 / SYMBOL / 时间 / 空值字面量、 表访问、基础 select / exec / update / delete、loadTable / loadTextEx 等基础写法， 探查服务端已有 DFS 库表，编写建库建表样例，或在使用 SQL、函数式、向量化 skill 前先保证代码语法和脚本结构可运行。

dolphindb Bundle

在编写、优化、审查 DolphinDB / DolphinScript 代码时使用此向量化工作流。 适用于向量化编程、性能优化、for 循环改写、逐元素处理改写、逐列逐组脚本改写、 SQL / 流处理路线选择，以及根据 tag / scene 判定低效模式并给出改写方案。

dolphindb Skill

金融数据导入 — 将 CSV 文件导入到已存在的 DolphinDB 表中

dolphindb Skill

金融数据建库建表 — 自动检测 CSV 结构并在 DolphinDB 中建库建表

opendcai Bundle

Reference documentation for the PandasOperator operator. Use when: applying custom DataFrame transformations without LLM.

opendcai Bundle

Reference documentation for the BenchAnswerGenerator operator. Covers the constructor, full run() signature, actual generation behavior, and integration notes for unified bench evaluation pipelines. Use when: generating model answers from benchmark question rows before passing the dataframe into UnifiedBenchDatasetEvaluator.

opendcai Bundle

Reference documentation for the ChunkedPromptedGenerator operator. Covers the constructor, file-path based chunking flow, actual prompt construction, and output file writing behavior. Use when: the dataframe stores file paths, the file content may exceed a single LLM context window, and you want the generated results written into new text files.

opendcai Bundle

Reference documentation for the FormatStrPromptedGenerator operator. Covers the constructor, prompt template restrictions, placeholder-to-column mapping, actual prompt-building logic, and runnable example usage. Use when: one generation task needs multiple dataframe columns combined into a single prompt through a template.

opendcai Bundle

Reference documentation for the RandomDomainKnowledgeRowGenerator operator. [Purpose] Calls an LLM repeatedly with the same domain-generation prompt and writes the generated results into one column of an existing DataFrame. [When to use] Use it when you already have a seed DataFrame with the exact target row count and want to fill one output column with domain-specific generated content. If you need to build prompts from existing row fields, use PromptedGenerator or FormatStrPromptedGenerator instead.

planetscale Skill

Use the PlanetScale CLI (pscale) from automated agents with --format json, auth check, pscale sql, and per-command --force. Run before other PlanetScale skills when driving pscale directly. Use when the user asks to automate pscale, run CLI commands headless, or verify pscale auth from an agent.

tacticaldoll Bundle

Use when an agent needs to plan a safe data migration or database schema change; sequences the change into backward-compatible expand/backfill/contract phases with rollback and verification steps rather than executing SQL scripts or migrating data.

tkolleh Bundle

Trigger on: jq, jq filter, jq query, process JSON, filter JSON, transform JSON, extract from JSON, parse API response JSON, NDJSON, pretty-print JSON, jq select, group_by JSON, update JSON file with jq. Specialized procedure for complex JSON processing with the jq CLI. Prefer over ad-hoc Python/Node one-offs for extract, filter, format, aggregate, or in-place JSON transforms. Do not use for binary files, CSV/XML conversion, or general scripting unrelated to JSON.

tkolleh Bundle

Trigger on: chart, plot, visualize data, bar chart, line chart, scatter plot, pie chart, line graph, Vega-Lite, make a chart from CSV/JSON/table. Generates charts (bar, line, scatter, pie) from CSV, JSON, or pasted tabular data using Vega-Lite, with automatic column-type detection and chart-type recommendation. Use when the user wants a data visualization from a table or file — not for architecture/sequence diagrams (use diagram), network graphs, or design/art images.

trk Skill

Use when auditing ProcessWire modules, hooks, templates, or MCP endpoints for security vulnerabilities like OWASP, input sanitization, RBAC, CSRF, and SQL injections.

weorbitant Bundle

Step 0 — Load configuration

claude-office-skills Skill

股票估值报告引擎 — 数据质量门控/多方法估值/质量评估/风险矩阵/决策框架的 Excel 完整估值工作簿

zznabil Bundle

Create, edit, inspect, convert, or repair DOCX, PDF, PPTX, and spreadsheet files while preserving structure and validating the final artifact with the available file tools.

gabriel-f-santos Bundle

Guide LGPD (Brazilian data-protection) compliance for a web app/SaaS — audit the codebase for gaps, implement the required features, and scaffold the legal docs. Use for "LGPD", "adequação LGPD", "privacidade / proteção de dados", "política de privacidade", "banner de cookies / consentimento", "opt-in de analytics", "direitos do titular", "exclusão / portabilidade de dados", "DPO", "DPA", or "GDPR". Audits against the ANPD checklist (privacy policy, real cookie opt-in, data-subject rights, security by design, DPA), guides implementation (consent gating for GA4/Pixel, account-deletion cascade, data-export endpoint, MFA/crypto/log hygiene, Sentry sendDefaultPii:false), and drafts a privacy-policy / DPA. Technical guidance, NOT legal advice — a DPO/lawyer signs off. Do not use for general security review unrelated to privacy (use review-security) or for app features that don't touch personal data.

lossless-group Skill

The Lossless Group's discipline of pinning a curated collection of upstream repos (a "study") around a domain question *before* designing or coding in that domain. Use when starting work that touches conventions, file formats, schemas, protocols, or any decision where prior art exists; when the user mentions "study", "studies/", "reference collection", "prior art", "pin a submodule", or names of existing studies (open-specs-and-standards, memory-layers-for-agents, data-analytics-specifications-and-standards); when scaffolding a new study, extending one, or deciding whether something belongs in a study vs. a project. Encodes the "read upstream code, don't paraphrase from training data" behavior.

posteyai Bundle

Read what a post or an account actually did, say what the numbers support, and turn that into the next content decision. Includes the checks that stop a number being read as a result when it is not one.

tkoenig Skill

Cloudflare analytics via GraphQL API. Query HTTP request stats (status codes, 404s, top paths), video streaming analytics (minutes watched, top videos), geographic breakdowns, and time series data. Use when asked about Cloudflare analytics, HTTP errors, video stats, or traffic data.

methasit-pun Skill

Best-practice SQL for analytical workloads — window functions, CTEs, query optimization, partitioning strategies, and anti-patterns to avoid. Use this skill whenever the user is writing or reviewing a SQL query that goes beyond a basic SELECT, especially on BigQuery, Snowflake, Redshift, or DuckDB. Trigger on mentions of aggregations, ranking, running totals, session analysis, lag/lead comparisons, deduplication, slowly-changing lookups, or any time the user asks "how do I write a query for X". Also trigger when a query looks slow, returns wrong results, or the user asks for a code review of existing SQL.

methasit-pun Skill

Data Pipelines (Router)

methasit-pun Skill

Pandas, Polars, and PySpark idioms for production data engineering — chunked reads, memory-safe transforms, vectorized operations, type optimization, and performance patterns. Use this skill whenever the user is writing a Python data transformation script and running into memory issues, slow performance, or correctness bugs with large datasets. Also trigger when the user asks how to handle large CSV/Parquet files, process data in batches, use Polars instead of Pandas, optimize a PySpark job, or reduce DataFrame memory usage. If you see someone iterating row-by-row over a DataFrame, this skill should trigger immediately.

eigent-ai Bundle

General workflow for auditing ML CI failures, experiment regressions, training run failures, golden metric failures, and telemetry-backed ML work-product claims from local repositories, logs, metrics, configs, and artifacts. Use when Codex needs to decide whether an ML failure is a model/convergence issue, correctness bug, data/config issue, infrastructure/runtime issue, evaluation/gating policy issue, or unsupported claim, and produce structured evidence-backed outputs.

wangyendt Skill

Utility toolkit for pywayne.tools. Use when tasks need colored console output and tables (wayne_print, wayne_print_table), timing/profiling (@func_timer, @func_timer_batch), YAML config I/O (read_yaml_config, write_yaml_config), logging (wayne_logger), tracing (@trace_calls), retries (@retry), disk caching (@disk_cache), parallel execution (parallel_map), progress bars (@with_progress, progress_iter), file listing/line counting, FileWatcher callbacks, singleton/compose helpers, matplotlib helpers (@maximize_figure, binding_press_release), numpy/pandas display control, or TTS/speech helpers (say, leader_speech). Prefer these built-ins over adding new dependencies or using raw print/logging/config code.

impertio-studio Bundle

Use when generating Draw.io diagrams from tabular/CSV data or creating data-driven diagrams. Prevents the common mistake of missing directive lines or wrong connection JSON format. Covers all CSV directives (label, style, connect, layout, identity), column references, conditional styling, and auto-layout options. Keywords: CSV import, csv-to-diagram, data-driven diagram, # label, # style, # connect, tabular data, diagram from spreadsheet, import data, generate diagram from CSV, auto-generate diagram.