Data & Analytics

skills-il Bundle

Access Israeli election and political data from the Knesset OData v4 API and the Central Elections Committee (data.gov.il). Use when user asks about Knesset, Israeli elections, MK (Member of Knesset) information, Israeli voting records (per-MK plenum votes via KNS_PlenumVote/KNS_PlenumVoteResult), legislative bills in Israel, Knesset committees, Israeli political parties, coalition data, or election results by locality or ballot. Covers Knesset OData v4 API, Central Elections Committee CSV datasets on data.gov.il, municipal elections, and Israeli political system structure. Do NOT use for non-Israeli elections or political opinion/prediction.

nearform Bundle

Use this skill when writing, reviewing, or refactoring database queries with @nearform/sql — Nearform's tagged-template library that produces SQL-injection-safe parameterized queries for pg, mysql, and mysql2. Covers installation, the SQL tag (.text/.sql/.values/.debug), helpers (glue, map, unsafe, quoteIdent), Fastify integration, dynamic/bulk queries, and security best practices. Trigger terms: SQL, query, parameterized query, SQL injection, pg, postgres, mysql, @nearform/sql, glue, quoteIdent.

open-edge-platform Bundle

Generates or updates CHANGELOG.md by analyzing git commit history between two branches, tags, or revisions in ANY git repository or folder. Use this skill whenever the user asks to create, update, generate changelog, draft release notes from git history, or compare branches/tags (e.g., "generate changelog comparing release-2026.0.0 and release-2026.1.0", "update CHANGELOG.md for the time-series-analytics folder", "what changed between v1.0.0 and main", "create release notes for this project"). The skill auto-detects folder paths, infers version numbers from branch/tag names, detects existing CHANGELOG format, and produces well-categorized entries (Added, Changed, Removed, Fixed, Security, Documentation) matching the repository's established style. Works with ANY folder structure or repository.

poorvith-mp Skill

Moved to modernized catalog in skillary. Removed in v4.1.

varunk130 Skill

Revenue analytics architecture - ARR / NRR / GRR decomposition, cohort retention, expansion drivers, segment economics, and CAC payback diagnostics. Use when: revenue analytics, ARR waterfall, NRR analysis, GRR, expansion analysis, cohort revenue retention, CAC payback, magic number, segment economics, revenue diagnostics.

varunk130 Skill

Customer analytics framework - cohort retention, lifecycle funnels, engagement scoring, segmentation, and behavioral diagnostics for product and CS teams. Use when: customer analytics, cohort analysis, retention curve, engagement score, customer segmentation, behavioral analysis, lifecycle funnel, RFM, activation diagnostics, usage analysis.

yoanbernabeu Skill

Set up analytics tracking for your Product Hunt launch. Use this skill to configure tracking tools, create dashboards, and ensure you capture all important launch metrics.

yoanbernabeu Skill

Track and optimize conversions from your Product Hunt launch. Use this skill to measure signup rates, identify drop-offs, and calculate the true ROI of your launch.

rakib-nyc Skill

Builds parameterised SQL against the ledger schema. Use when the user asks to read from or write to the accounts, postings, or journals tables.

nick2bad4u Bundle

Inspect and manage Socket.dev organizations, repositories, scans, dependency and supply-chain alerts, policies, resolutions, reports, SBOMs, analytics, audit logs, and safe API operations. Use whenever the user mentions Socket Security or Socket.dev posture, findings, scans, configuration, or remediation.

alainlebret Skill

Packages pedagogical artifacts for LMS delivery (Moodle, Canvas, generic CSV/ZIP bundles) with reproducible naming and metadata. Use when output must be imported directly into institutional platforms.

alainlebret Skill

Generates realistic synthetic datasets, input files, traces, logs, images, CSV files, graphs, and edge-case inputs for computing labs, projects, and exams. Use when pedagogical artifacts need representative inputs or benchmark data.

kangwang42 Bundle

读取、提取、创建、合并、拆分、旋转、裁切、加水印、OCR、加密、检查或填写实际 PDF 文件。PDF 是主要输入或指定输出时使用；论文、报告、表格和统计内容仍由相应内容 skill 决定。不用于只处理 Word、PPT、Excel、网页或聊天正文。

kangwang42 Bundle

读取、清洗、创建、编辑、格式化、核验或转换 `.xlsx`、`.xlsm`、`.csv` 和 `.tsv` 文件。表格文件是主要输入或交付物时使用；统计表内容先用相应统计分析 skill，工作簿中的统计图内容先用 publication-figures。不用于以论文、报告、独立脚本、数据库流程或 Google Sheets 为主要交付物的任务。

kangwang42 Bundle

Python 流行病学与生物统计分析的可选执行层，仅用于用户明确要求 Python，或既有项目已经以 Python 为主流程时的数据清洗、描述统计、回归、生存分析、预测验证、统计表图、代码调试和结果复现。开工先遵循 biostat-principles；统计图配合 publication-figures，客户外发再用 consulting-delivery。未指定语言的普通统计分析、R 环境或依赖缺失、研究设计定稿、论文写作或仅操作 xlsx 文件不触发。

kimtth Skill

Fabric Lakehouse design, schemas, shortcuts, security, optimization, and PySpark patterns. Use when designing Lakehouse solutions, managing Delta tables, configuring OneLake shortcuts, or writing PySpark/Spark SQL code for Fabric notebooks.

kimtth Skill

Design, configure, evaluate, and govern Microsoft Fabric Data Agents for natural-language Q&A over Lakehouse, Warehouse, Power BI semantic model, KQL database, mirrored database, ontology, or Microsoft Graph data. Use when the user asks for Fabric data agent, conversational analytics, NL2SQL, NL2DAX, NL2KQL, data-agent instructions, example queries, agent evaluation, publishing, sharing, governance, diagnostics, or ALM.

kimtth Bundle

Analyze Fabric Data Warehouse performance via CLI using sqlcmd and queryinsights views. Diagnose slow queries, SQL pool pressure, cache coldness, and recommend clustering keys. Triggers: "DW slow query analysis", "slowest queries warehouse", "queryinsights long running", "warehouse CPU resource consumers", "SQL pool pressure window", "pressure events warehouse", "DW cache warmth cold start", "cache warmth analysis", "warehouse cluster key recommendation", "cluster tables performance", "DW performance baseline comparison", "performance degraded warehouse", "warehouse user query patterns", "queryinsights diagnostics", "DW optimization sqlcmd".

kimtth Skill

Analyze lakehouse data interactively using Fabric Lakehouse Livy API sessions and PySpark/Spark SQL for advanced analytics, DataFrames, cross-lakehouse joins, Delta time-travel, and unstructured/JSON data. Use when the user explicitly asks for PySpark, Spark DataFrames, Livy sessions, or Python-based analysis — NOT for simple SQL queries. Triggers: "PySpark", "Spark SQL", "analyze with PySpark", "Spark DataFrame", "Livy session", "lakehouse with Python", "PySpark analysis", "PySpark data quality", "Delta time-travel with Spark".

kimtth Bundle

Execute read-only T-SQL queries against Fabric Data Warehouse, Lakehouse SQL Endpoints, and Mirrored Databases via CLI. Default skill for any lakehouse data query (row counts, SELECT, filtering, aggregation) unless the user explicitly requests PySpark or Spark DataFrames. Use when the user wants to: (1) query warehouse/lakehouse data, (2) count rows or explore lakehouse tables, (3) discover schemas/columns, (4) generate T-SQL scripts, (5) monitor SQL performance, (6) export results to CSV/JSON. Triggers: "warehouse", "SQL query", "T-SQL", "query warehouse", "show warehouse tables", "show lakehouse tables", "query lakehouse", "lakehouse table", "how many rows", "count rows", "SQL endpoint", "describe warehouse schema", "generate T-SQL script", "warehouse performance", "export SQL data", "connect to warehouse", "lakehouse data", "explore lakehouse".

moda-design Bundle

Data charts on Moda from real data — CSV, a table, pasted numbers: bar, line, area, pie, scatter, combo; an editable chart on a live canvas, exported png or pdf. Use for: "chart/graph/plot this data", "visualize these numbers". NOT: a chart inside an artifact another moda skill is building — the building skill keeps it; boxes-and-arrows or quadrants → moda-diagram.

celticht32 Bundle

Design, build, and tune Couchbase Full Text Search (FTS) and vector search indexes. Use whenever the user asks about FTS indexes, Search service, text search, full-text search, fuzzy search, phrase search, wildcard search, regex search, geo search, geo-distance, geo-bounding-box, facets, scoring, boosting, analyzers, tokenizers, custom analyzers, language analyzers, type mappings, dynamic mappings, child mappings, FTS index design, FTS synonyms (8.x), vector search, kNN search, vector index, embedding search, hybrid search (FTS + vector), cb_fts_search, admin_fts_*, BLEVE, or 'how do I search text in Couchbase.' Distinct from couchbase-sqlpp-tuning (SQL++ index design) and couchbase-mcp (operating the tools). Use proactively when the user has a search use case — text relevance, semantic similarity, geo-proximity, or faceted navigation.

celticht32 Bundle

Operate Couchbase clusters and Capella v4 through an MCP server. Primary target is celticht32/MCP-Couchbase (167 tools) for full data-plane AND cluster admin; also covers the official Couchbase-Ecosystem/mcp-server-couchbase (narrower, data-plane-only, community-maintained, enterprise-supported via AI Data Plane license) and when to pick which. Use whenever the user mentions Couchbase, buckets, scopes, collections, SQL++ / N1QL, KV ops, subdocument ops, FTS, vector indexes, XDCR, eventing, backup, encryption / KMIP / DARE, user lock/unlock, query performance, Index Advisor, synonyms (8.x), or Capella organizations / projects / clusters / database users / allowed CIDRs / app services. Use proactively for cluster admin (rebalance, failover, recovery, autofailover, autocompaction, logs, alerts, audit, password policy), RBAC design, troubleshooting Couchbase errors, operational runbooks (rolling upgrade, node add/remove, post-failover recovery, backup/restore, credential rotation), and observability.

celticht32 Bundle

Design and use Couchbase Capella Analytics (formerly Capella Columnar), the standalone columnar analytics database service on Capella. Use whenever the user asks about Capella Analytics, Capella Columnar, columnar analytics, an Analytics instance, Capella Analytics vs the operational Analytics Service, Analytics collections, links to operational data, Analytics SQL++, pricing, when to use standalone Capella Analytics vs the embedded Analytics Service, or 'I need to run analytical queries on my Couchbase data.' Distinct from the cb-analytics-* skills (which cover the Couchbase Analytics Service embedded in Couchbase Server / Capella operational clusters) — Capella Analytics is a separate, standalone columnar database product on Capella. Use proactively when the user needs OLAP-scale analytics, BI tool integration, or columnar storage for analytical workloads.

celticht32 Bundle

Diagnose and tune slow Couchbase SQL++ / N1QL queries. Use whenever the user asks about query performance, slow queries, EXPLAIN plans, why an index isn't being used, IntersectScan, PrimaryScan, covering indexes, partial indexes, array indexes (ANY / EVERY / UNNEST), index selection, query hints, the cost-based optimizer, the Index Advisor (ADVISE), system:completed_requests, query profiling (kernTime / servTime / execTime), pagination performance, prepared statements, or 'this query is slow / how do I make it faster.' Distinct from couchbase-data-modeling (document shape) and couchbase-mcp (operating the cluster) — this skill is about reading plans, designing the right indexes, and reshaping queries that already exist. Use proactively when the user shares an EXPLAIN output or a slow query.

celticht32 Bundle

Design document models, choose document boundaries, and pick access patterns for Couchbase. Use whenever the user asks about document model, schema design, key design, document shape, embed vs reference, denormalization, scope vs collection vs bucket, modeling for query / index / FTS / vector search, time-series in Couchbase, TTL strategies, anti-patterns, migrating from SQL / MongoDB / DynamoDB / DocumentDB, or general 'how should I structure this data.' Triggers on design-phase conversations before any tools are called — distinct from the couchbase-mcp skill, which is for operating an existing cluster. Use proactively for: greenfield Couchbase projects, schema migrations, re-architecting an existing model, deciding between scopes/collections/buckets, modeling time-series or vector embeddings, planning denormalization tradeoffs, naming keys, choosing between embedded sub-documents and references.

celticht32 Bundle

Apply coding standards and a style guide for writing production application code against Couchbase, combining general software-engineering best practices (naming, functions, error handling, testing, docstrings, version control, code review, secrets hygiene) with Couchbase-specific conventions (SDK idioms, document-key naming, exception and retry handling, durability, parameterized SQL++, connection lifecycle). Use whenever the user asks about coding standards, code style, a style guide, clean code, naming conventions, structuring Couchbase application code, idiomatic SDK usage, how to write or review Couchbase code, code-review checklists, linting, formatting, testing Couchbase code, or best practices for writing Couchbase apps. Distinct from couchbase-app-integration (SDK mechanics: pooling, durability, scan consistency) and couchbase-data-modeling (document design) — this is the how-to-write-and-review-the-code layer on top of them. Use proactively when reviewing or authoring code that touches Couchbase.

celticht32 Skill

Use this skill when the user wants to inspect or manage the Analytics service's runtime — checking ingestion health, killing runaway queries, restarting nodes, or diagnosing performance. Trigger when they mention "ingestion status", "active queries", "completed requests", "restart service", "cancel request", "service status", or "Analytics health".

celticht32 Skill

Use this skill when the user wants to write or improve SQL++ queries against Couchbase Analytics through cb-analytics-mcp. Trigger when they mention "SQL++", "Analytics query", "execute_query", "scan_consistency", "request_plus", "pagination", "EXPLAIN", "truncated", "row cap", or anything about querying datasets, dataverses, joins, aggregations, windowing, query plans, or N1QL/SQL++ language features in this server's context.

celticht32 Bundle

Diagnose and tune cluster-level performance problems in Couchbase. Use whenever the user asks about slow KV operations, high latency, low throughput, DCP backpressure, connection limits, thread pool tuning, compaction impact on performance, autocompaction settings, KV engine tuning, vBucket distribution, rebalance performance, disk I/O bottlenecks, CPU saturation on Couchbase nodes, network throughput limits, or 'my cluster is healthy but slow.' Distinct from couchbase-sqlpp-tuning (SQL++ query tuning — index design and EXPLAIN plans), couchbase-observability (what metrics to watch), and couchbase-sizing (how much capacity to provision). This skill covers the operational tuning layer: what to change when the cluster is right-sized but still not performing.

celticht32 Skill

Use this skill when the user wants to inspect, discover, or document the structure of Couchbase Analytics dataverses and datasets — listing what exists, inferring document shapes, or building a data dictionary. Trigger when they mention "schema", "dataverses", "datasets", "what fields are in", "what's the structure of", "infer_schema", or "Metadata.\`Dataverse\`".

celticht32 Skill

Use this skill when the user wants to inspect or configure the Couchbase cluster itself — node membership, memory quotas, rebalance, auto-failover, system events, or just verifying that a cluster is reachable. Trigger when they mention "cluster info", "ping", "rebalance", "auto-failover", "system events", "nodes", "memory quota", or "who_am_i".

celticht32 Skill

Use this skill when the user wants to manage Couchbase users, groups, roles, or check permissions on the cluster — creating service accounts, rotating passwords, granting analytics privileges, or auditing who can do what. Trigger when they mention "user", "group", "role", "RBAC", "permission", "upsert_user", "check_permissions", "local domain", "external domain", or "analytics_reader" / "analytics_admin".

celticht32 Skill

Use this skill when the user is setting up cb-analytics-mcp from scratch or troubleshooting an existing install — generating secrets, configuring .env, running --check, picking single- vs multi-cluster mode, tuning rate limits, configuring audit rotation, or using the CLI. Trigger when the user mentions "install", "configure", "first run", "MCP_API_KEY", "GUI_PASSWORD", "clusters.json", "cb-analytics-mcp --check", "MAX_QUERY_ROWS", "RATE_LIMIT_", "AUDIT_ROTATE", "tools call", or "tools list".

cuga-project Bundle

Browse a Box folder and answer questions over its documents (PDF, DOCX, PPTX, XLSX, TXT, MD, CSV) with file-cited answers. Use when the user references "Box", a Box folder ID, or asks "find/show me <file> in my Box".

cuga-project Bundle

Extract and summarise the contents of a local document the user supplies by file path (.txt, .md, .pdf, .docx, .pptx, .xlsx, .csv). Use when the user uploads, drops, or names a path to a file and wants a TL;DR with key points and action items.