Data & Analytics

prism-shadow Skill

SKILL: ApexCloud Retention Operations — CRM Analytics SOP

prism-shadow Skill

SKILL: ApexCloud Retention Operations — CRM Analytics SOP

prism-shadow Skill

SKILL: ApexCloud Retention Operations — CRM Analytics SOP

prism-shadow Bundle

Solve Cedar Ridge Intake Coordination Portal reconciliation tasks — the family of jobs that point at a shared healthcare intake portal (patients, referrals, transfers, charts, coverage, PBM, pharmacies, ICD codes, program candidates) and ask for ONE strict JSON object that follows a provided answer_template.json. Covers new-patient access verification, referral readiness audits, transfer/dialysis intake review, chronic-care enrollment panels, and referral-to-chart activation. Use whenever a task references the Cedar Ridge / intake-coordination portal, gives an answer_template with enum allowed_values and ordering rules, and wants patient/referral/transfer-level status derivation plus cohort summary counts.

prism-shadow Bundle

Solve structured licensing / regulatory review tasks that read a prompt plus a strict JSON answer template, query a licensing data service (REST + a SQL endpoint), apply agency policy logic to specific target records, and emit only JSON matching the template. Covers three task families: contractor batch eligibility review, restricted liquor-license staff package, and alcohol renewal manual-review queue. Use when a task gives target IDs, points at /api/... endpoints, and supplies input/payloads/answer_template.json.

prism-shadow Bundle

Solve an Asteria "Fleet Data Quality Hub" reconciliation task. Use when a task gives you payloads/case_scope.json plus payloads/answer_template.json and asks you to reconcile overlapping source records from a read-only data hub (catalog, schema, SQL query, source-snapshot, contact/transaction/maintenance, and reference alias/conversion/fx interfaces) and return exactly one JSON object. Covers three task families: contact-master reconciliation, transaction normalization (fuel/freight), and maintenance-log integrity.

prism-shadow Bundle

Use when a task asks you to produce an operational reporting result written to answer.json for the "Atlas Commerce Operations" workplace — e.g. a fulfillment cutoff scorecard, a refund/settlement reconciliation, a carrier-quality correction, a warehouse-productivity review, a support-health review, or any similar request that pairs a business request-payload JSON with an answer_template JSON Schema and a governed SQL data service. It guides you to read both contracts, discover the real schema, translate business definitions into precise read-only SQL (eligibility windows, quantifiers, FX conversion, medians, active-time clocks, ordering/tie-breaks, rounding, status/risk bands), apply a minimal approved correction with an audit row through the controlled transaction interface when one is requested, and emit an answer that conforms exactly to the template.

prism-shadow Bundle

Solve Public Health Observatory (PHO) "registered algorithmic audit" analysis tasks — the ones that hand you a prompt.txt plus payloads/analysis_request.json and payloads/answer_template.json and point you at a read-only web data portal (a "<TASK_ENV_BASE_URL>" placeholder; a Public Health Observatory / Observatory data portal with /catalog, /methodology, state_health, county_health, country_indicators, socioeconomic, and revisions datasets). Use it whenever the request asks for a publication/cohort audit followed by a fixed roster of ~6 statistical "modules" (fixed-effects or GMM jackknife, nested ridge/elastic-net cross-validation, wild cluster bootstrap-t, grouped split conformal, trajectory PCA + k-means stability, source/year perturbation or Shapley, mediation, sensitivity surfaces) and a gated PASS/FAIL decision or classification, returned as one strict JSON object conforming to the answer template.

prism-shadow Skill

Reflect Portfolio Analytics Skill

charlieviettq Bundle

Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.

charlieviettq Bundle

Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

charlieviettq Bundle

Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.

charlieviettq Skill

Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.). Use when writing queries, optimizing slow SQL, translating between dialects, or building complex analytical queries with CTEs, window functions, or aggregations.

charlieviettq Skill

Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query patterns.

charlieviettq Skill

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.

caishengold Skill

当需要设计BI仪表盘、构建KPI报表、SQL查询分析时使用。触发场景：仪表盘设计、KPI报表构建、SQL数据查询、业务数据可视化。当用户提到"BI报表"、"仪表盘"、"dashboard"、"KPI"、"数据可视化"、"SQL查询"时应触发此技能。

caishengold Skill

当需要数据清洗、统计分析、趋势报告时使用。触发场景：CSV/Excel数据清洗、描述性统计分析、趋势图表报告、数据可视化建议。当用户提到"数据分析"、"数据清洗"、"统计"、"趋势"、"报告"、"CSV"、"Excel"时应触发此技能。

caishengold Skill

当需要撰写ETL规格相关专业文案、行业指南、科普文章时使用。触发场景：ETL规格/数据集成。当用户提到"规格"、"规格"、"数据集成"、"etl"、"spec"时应触发此技能。

caishengold Skill

当需要分析社交媒体数据、制作社媒报表、评估内容表现时使用。触发场景：社媒数据报表、内容表现分析、竞品社媒监控、受众画像分析。当用户提到"社媒数据"、"内容分析"、"社媒报表"、"互动率分析"、"social analytics"、"social media report"时应触发此技能。

caishengold Skill

当需要分析体育赛事数据、球员统计、赛事预测时使用。当用户提到“体育数据“、“赛事分析“、“球员统计“、“sports analytics“时应触发此技能。

paulasilvatech Skill

Review existing PostgreSQL SQL, schema, migrations, functions, triggers, indexes, JSONB, arrays, custom types, domains, extensions, privileges, and Row Level Security for PostgreSQL-specific anti-patterns. Use when asked to audit or critique PostgreSQL code, database migrations, PL/pgSQL, RLS policies, or schema design.

paulasilvatech Skill

Design, tune, and modernize PostgreSQL SQL, schemas, indexes, functions, and maintenance workflows using PostgreSQL-specific capabilities. Use this skill when the user asks for PostgreSQL optimization, query tuning, JSONB or array design, EXPLAIN ANALYZE interpretation, index strategy, full-text search, custom types, range/geometric types, pg_stat_statements, VACUUM, ANALYZE, partitioning, or secure parameterized database development.

paulasilvatech Bundle

Explain, design, build, and optimize Microsoft Fabric Lakehouse solutions using OneLake, Delta tables, Files, SQL analytics endpoints, semantic models, shortcuts, schemas, materialized views, Spark views, security, lineage, ingestion, and table optimization. Use when the user asks about Fabric Lakehouse concepts, architecture, data layout, shortcuts, PySpark, loading data, or Lakehouse best practices.

paulasilvatech Skill

Analyze COBOL programs, copybooks, PERFORM and CALL structure, file and VSAM access, embedded EXEC SQL and EXEC CICS, DB2 DDL, DCLGEN structures, cursors, and JCL job steps with source citations. Use when reading or inventorying a COBOL/DB2 legacy system before modernization.

paulasilvatech Skill

Review existing PostgreSQL SQL, schema, migrations, functions, triggers, indexes, JSONB, arrays, custom types, domains, extensions, privileges, and Row Level Security for PostgreSQL-specific anti-patterns. Use when asked to audit or critique PostgreSQL code, database migrations, PL/pgSQL, RLS policies, or schema design.

paulasilvatech Skill

Review existing PostgreSQL SQL, schema, migrations, functions, triggers, indexes, JSONB, arrays, custom types, domains, extensions, privileges, and Row Level Security for PostgreSQL-specific anti-patterns. Use when asked to audit or critique PostgreSQL code, database migrations, PL/pgSQL, RLS policies, or schema design.

paulasilvatech Bundle

Compare SQL Server tables across source and target instances for migration validation, ETL verification, production versus staging checks, schema drift, missing rows, extra rows, and column mismatches. Use this skill when the user asks for SQL Server reconciliation reports, and use mssql-python with Apache Arrow for fast extraction.

paulasilvatech Skill

Design, tune, and modernize PostgreSQL SQL, schemas, indexes, functions, and maintenance workflows using PostgreSQL-specific capabilities. Use this skill when the user asks for PostgreSQL optimization, query tuning, JSONB or array design, EXPLAIN ANALYZE interpretation, index strategy, full-text search, custom types, range/geometric types, pg_stat_statements, VACUUM, ANALYZE, partitioning, or secure parameterized database development.

paulasilvatech Skill

Design, tune, and modernize PostgreSQL SQL, schemas, indexes, functions, and maintenance workflows using PostgreSQL-specific capabilities. Use this skill when the user asks for PostgreSQL optimization, query tuning, JSONB or array design, EXPLAIN ANALYZE interpretation, index strategy, full-text search, custom types, range/geometric types, pg_stat_statements, VACUUM, ANALYZE, partitioning, or secure parameterized database development.

paulasilvatech Bundle

Route and execute Microsoft Fabric administration, data engineering, real-time intelligence, SQL, Spark, Power BI, Git integration, migration, cost estimation, and end-to-end architecture workflows. Use when a request spans Fabric workloads or needs the correct specialist guide, MCP server, REST/CLI path, safety gate, and verification sequence.

sheshiyer Skill

Use when large data ingestion, backfill, export, ETL, warehouse loading, manifest catch-up, or table synchronization needs to become much faster while preserving data correctness.

sheshiyer Skill

Query Hugging Face datasets through the Dataset Viewer API for splits, rows, full-text search, filters, and parquet links (read-only). USE WHEN you need read-only exploration or extraction from a Hugging Face dataset.

undermybelt Bundle

Deploys and configures osquery for real-time endpoint monitoring using SQL-based queries to inspect running processes, open ports, installed software, and system configuration. Use when building visibility into endpoint state, threat hunting across fleet, or implementing compliance monitoring. Activates for requests involving osquery deployment, endpoint visibility, fleet management, or SQL-based endpoint querying.

undermybelt Bundle

Implements SIEM detection use cases by designing correlation rules, threshold alerts, and behavioral analytics mapped to MITRE ATT&CK techniques across Splunk, Elastic, and Sentinel. Use when SOC teams need to expand detection coverage, formalize use case lifecycle management, or build a detection library aligned to organizational threat profile.

undermybelt Bundle

Performs User and Entity Behavior Analytics (UEBA) to detect anomalous user activities including impossible travel, unusual access patterns, privilege abuse, and insider threats using SIEM-based behavioral baselines and statistical analysis. Use when SOC teams need to identify compromised accounts or insider threats through deviation from established behavioral norms.

undermybelt Bundle

Parse Apache and Nginx access logs to detect SQL injection attempts, local file inclusion, directory traversal, web scanner fingerprints, and brute-force patterns. Uses regex-based pattern matching against OWASP attack signatures, GeoIP enrichment for source attribution, and statistical anomaly detection for request frequency and response size outliers.