Data & Analytics

stas2-git Bundle

Use when deciding which bundled Excel, workbook, spreadsheet, live Excel automation, VBA, screen interaction, backup, planning, summarization, or validation skill to use.

stas2-git Bundle

Use this skill when the user asks you to write, review, optimize, or explain SQL queries in an actuarial or insurance context — including loss triangles, claims analysis, reserving, premium calculations, policy/claims joins, and mortality studies. Also use for general SQL best practices, clean query writing, and join strategy.

stas2-git Bundle

Use when a user requests to create, modify, analyze, visualize, or work with spreadsheet files (`.xlsx`, `.xls`, `.csv`, `.tsv`) or Google Sheets-targeted spreadsheet artifacts with formulas, formatting, charts, tables, and recalculation.

stas2-git Bundle

Use this skill when the user wants to connect to a database, explore its schema, or execute SQL queries against a live server. Pairs with the actuarial-sql skill: actuarial-sql writes the query, odbc-connector executes it via connector.py.

stas2-git Bundle

Use when a user wants to turn an Excel workbook such as .xlsx or .xlsm into an LLM-readable text dump that summarizes workbook structure, sheet names, formulas, values, and named ranges. Best for auditing workbook logic, preparing workbook context for model analysis, or comparing workbook versions.

stas2-git Bundle

Use when a user wants to build, edit, reorganize, or clean up an Excel workbook through deterministic workbook actions instead of writing a one-off openpyxl script. Best for creating sheets, writing values or formulas, copying ranges, formatting ranges, sizing rows or columns, freezing panes, and other repeatable workbook edits.

stas2-git Bundle

Use when a workflow needs to open or attach to an Excel workbook, run a named macro, capture success or failure, and return structured execution results for autonomous workbook iteration.

stas2-git Bundle

Use when a task needs OCR over an image, the full screen, or an exact screen region, returning structured text, confidence, and bounding boxes without bundling clicks into the same skill.

stas2-git Bundle

Use when a workflow needs to inspect or export VBA modules from an Excel workbook, and when write-side VBA injection must happen through Excel screen automation in the VBE rather than direct Python-to-VBProject automation.

stas2-git Bundle

Use when a task needs a clean screenshot primitive such as full-screen capture or exact region capture, without bundling OCR or action logic into the same skill.

stas2-git Bundle

Use when a task needs macOS app or window activation, frontmost app inspection, window-title targeting, or saving and restoring app/window state before and after screen interaction work.

stas2-git Bundle

Use when a task needs to poll screen state until text appears or disappears, assert that text exists, or fail cleanly after a timeout.

stas2-git Bundle

Use when a workbook is already open in Excel and the workflow needs to make live edits through the Excel session, such as writing cell values, formulas, formatting, sheet labels, freeze panes, or simple structural changes, without closing the workbook.

stas2-git Bundle

Use when a workflow needs to attach to a live Excel session, open or activate a workbook, switch sheets, save the workbook, or coordinate focus between Excel, the VDI, and later live-editing steps.

stas2-git Bundle

Use when a task needs to locate visible text on screen and act on it, such as finding a match, returning the best target, or clicking the matched text box center.

samber Bundle

Design customer-facing SQL access to a product's data - a JDBC/ODBC endpoint, warehouse share, or hosted query surface. Covers the architecture gate by scan frequency (zero-copy share, replicated copy, per-tenant compute isolation), engine-level tenant isolation with secure views and row-level security, an additive-only schema-stability contract enforced in CI, BI-tool connectivity and driver certification, query governance and cost caps, short-lived credential issuance, and the pricing shape. Use whenever the user mentions JDBC, ODBC, SQL access for customers, connecting Tableau or Power BI to product data, or pricing a SQL add-on - even if they never say "SQL access". Do NOT use for bulk file delivery - use samber/developer-platform-skills@bulk-data-sharing-design instead.

samber Bundle

Design bulk file and lake export as a B2B product surface - the two-camp choice between Parquet file-drops on object storage and native warehouse/lake sharing (Snowflake shares, Delta Sharing, linked datasets), the partitioning and schema-evolution contract across batches, delivery cadence and freshness commitments (full dump vs incremental vs CDC vs streaming), shared-bucket security with per-recipient credentials, egress cost allocation, and cross-border data residency. Use whenever the user mentions bulk export, data dumps to S3, Parquet, Snowflake shares, Delta Sharing, or export freshness SLAs - even if they never say "bulk data sharing". Do NOT use for live SQL endpoints - use samber/developer-platform-skills@sql-jdbc-access-design instead.

samber Bundle

Decide whether and when a SaaS should build its own app/connector marketplace, versus joining others' marketplaces or buying embedded iPaaS, and design its operating model - curation level, partner mix, governance rules, take-rate, and seeding sequence. Use whenever the user mentions building an app store or integration marketplace, ecosystem readiness, marketplace revenue share or take-rate, curated vs open admission, third-party app governance, or seeding a two-sided developer ecosystem - even if they never say "marketplace strategy". Strategy layer only. Do NOT use for billing and payout mechanics (samber/developer-platform-skills@app-marketplace-monetization-model) or for being a connector on others' data platforms (samber/developer-platform-skills@etl-connector-strategy).

samber Bundle

Builds a developer relations measurement framework - a handful of metrics tiered from reach to product and business impact, each with a written attribution rule, a baseline-derived target, an owner and an action, and vanity metrics cut. Use whenever someone asks how to measure DevRel, which devrel KPIs matter, how to prove devrel value or ROI to an exec, what belongs in a devrel scorecard or quarterly report, why their numbers look good but leadership stays unconvinced, or reports only stars, impressions and event counts - even if they never say "metrics". Do NOT use for tracking instrumentation and dashboards - use samber/developer-relations-skills@devrel-analytics. Not community-only health metrics, not a single event's ROI.

samber Bundle

Builds the tracking plan that instruments developer-relations surfaces - docs, blog, repositories, package registries, community venues, and off-web appearances - with an event taxonomy, an identity spine, link-tagging discipline, source-confidence labelling, and funnel views. Use when the user says "devrel tracking plan", "docs analytics", "utm discipline", "event taxonomy for our docs", "our GitHub numbers don't match analytics", "how do we instrument the developer funnel", "join docs traffic to signups", or wants to know why devrel numbers disagree between tools. Instrumentation layer only - which KPIs deserve a target belongs to samber/developer-relations-skills@devrel-metrics.

samber Bundle

Designs an unpaid, perks-only developer champions or ambassador program end to end - readiness check, intake model, published selection criteria, behaviour-based obligations, an access-first perk ladder, fixed terms with renewal and alumni status, and a cohort scorecard. Use whenever the user mentions an ambassador or champions program, MVP-style recognition, community heroes, "how do we recognise our top community members", what perks ambassadors should get, an ambassador program that went quiet, or removing an inactive champion - even if they never say "champion". Not for paid creator, affiliate or revenue-share partnerships. For measuring the community itself use samber/developer-relations-skills@developer-community-health.

oracle Bundle

Oracle Database guidance for SQL, PL/SQL, SQLcl, ORDS, Oracle Vector SDK, administration, app development, performance, security, migrations, and agent-safe database workflows. Use when the user asks to write, edit, rewrite, review, format, debug, tune, or explain SQL; create or refactor PL/SQL; use Oracle VecDB through the Python SDK, REST API, or DBMS_VECTOR_DATABASE package; use SQLcl, Liquibase, ORDS, JDBC, node-oracledb, Python, Java, .NET, or database frameworks; troubleshoot vector tables, embeddings, vector search, reranking, queries, sessions, locks, waits, indexes, optimizer plans, AWR, ASH, migrations, schemas, users, roles, privileges, backup, recovery, Data Guard, RAC, multitenant, containers, monitoring, auditing, encryption, VPD, or safe agent database operations.

motherduckdb Bundle

Build MotherDuck analytics into customer-facing applications with tenant isolation, backend routing, and serving APIs.

motherduckdb Bundle

Read or maintain MotherDuck Guides for business definitions, join rules, and reusable warehouse conventions.

motherduckdb Bundle

Plan or implement migrations to MotherDuck with SQL translation, source-to-target validation, cutover, and rollback.

motherduckdb Bundle

Roll out governed MotherDuck analytics to internal teams, choosing trusted datasets, access boundaries, and owners.

motherduckdb Bundle

Write, execute, or optimize analytical DuckDB SQL against MotherDuck data.

motherduckdb Bundle

Look up or repair DuckDB SQL syntax and verify MotherDuck-specific command and feature support.

maximsamokhval Bundle

Extract, normalize, and trace a set of requirements from provided text or local PDF, DOCX, XLSX, Markdown, and TXT materials, then produce a requirements register and BRS/StRS/SyRS/SRS package. Use when mining multiple passages or existing project materials into a traceable register or specification package informed by public ISO/IEC/IEEE 29148:2018 principles. Excludes isolated sentence editing, blank-project interview elicitation, and clause-level compliance certification.

dennis-bv Bundle

Smart Money analytics on OKX: leaderboard traders, position tracking, trade records, aggregated consensus signals, and signal history. Use this skill when the user asks about 聪明钱, smart money, 牛人榜, leaderboard, top traders, 带单员, lead traders, 交易员排行, trader ranking, trader positions, trader PnL, 交易员持仓, 交易员收益, smart money signal, 聪明钱信号, long/short ratio, 多空比, capital flow, 资金流向, position conviction, 仓位强度, entry price distribution, smart money overview, 聪明钱总览, signal history, 信号历史, trader search, 搜索交易员, who is trading BTC, 谁在交易BTC, recommend traders, 推荐交易员, best traders, top performers.

easyindie Skill

飞书云空间：管理云空间中的文件和文件夹。上传和下载文件、创建文件夹、复制/移动/删除文件、查看文件元数据、管理文档评论、管理文档权限、订阅用户评论变更事件、修改文件标题（docx、sheet、bitable、file、folder、wiki）；也负责把本地 Word/Markdown/Excel/CSV 以及 Base 快照（.base）导入为飞书在线云文档（docx、sheet、bitable）。当用户需要上传或下载文件、整理云空间目录、查看文件详情、管理评论、管理文档权限、修改文件标题、订阅用户评论变更事件，或要把本地文件导入成新版文档、电子表格、多维表格/Base 时使用。

librefang Skill

SQL query expert for optimization, schema design, and data analysis

librefang Skill

Data analysis expert for statistics, visualization, pandas, and exploration

alxlemesh Bundle

Work with the BSC meme-token swap database (Four.meme, Flap and OpenFour) through the fastbuy-db MCP server. Use it when asked about tokens, swaps, wallets, volumes, pools or indexer state; when writing SQL against this database; or when the tables four_tokens, flap_tokens, openfour_tokens, four_curve_swaps, flap_curve_swaps, openfour_curve_swaps, four_dex_swaps, flap_dex_swaps, openfour_dex_swaps, dex_pools, indexer_state come up.

texarkanine Bundle

Run read-only SQL against your local warehouse of agentic-coding history (sessions, messages, tool calls, embeddings). Reach for this on exact or structured lookups — known ids, WHERE filters, counts, GROUP BY, joins, aggregations — not meaning-based search (that is sr-semantic).

texarkanine Bundle

Search your local warehouse of agentic-coding history — the friendly default entrypoint. Reach for this when you are unsure whether the question is an exact/structured lookup (sr-query) or meaning-based recall (sr-semantic), or when it needs both — it routes the question, runs the right surface(s), and synthesizes one answer.