Data & Analytics Skills

Complete CoinGecko Solana API integration for token prices, DEX pool data, OHLCV charts, trades, and market analytics. Use for building trading bots, portfolio trackers, price feeds, and on-chain data applications.

Real-time smart money analytics API for Polymarket prediction markets, Hyperliquid perpetual futures, and Meteora Solana LP/AMM pools. 63 endpoints. Pay-per-request via x402 on Solana Mainnet USDC. No API keys.

Use for GEPA reflective optimization, ReAct agent optimization, feedback metrics, LLM reflection, and execution trajectories.

Use for evaluating DSPy programs with Evaluate, answer_exact_match, SemanticF1, custom metrics, baselines, and program comparisons.

Use when X Analytics CSV exports must be inspected, validated, normalized, imported, or compared through a repeatable private-by-default workflow.

Create, revise, and audit executive-ready strategy-consulting presentations as native, editable PowerPoint files. Use when turning topics, text, Markdown, Word, PDF, spreadsheets, CSV data, URLs, research, or an existing PPTX into a board, client, strategy, transformation, market-analysis, or McKinsey-style consulting deck; when applying a brand or PowerPoint template; or when checking a deck's storyline, evidence, charts, layout, and visual quality.

Work with Dynatrace dashboards - create, modify, query, and analyze dashboard JSON including tiles, layouts, DQL queries, variables, and visualizations.

Work with Dynatrace notebooks - create, modify, query, and analyze notebook JSON including sections, DQL queries, and visualizations.

>- Analyze dashboards and notebooks using Davis analyzers — anomaly detection, novelty scoring, and correlation. Use when the user references a specific Dynatrace dashboard or notebook (by URL, UUID, or name) and asks what it shows, which DQL queries it runs, whether a tile looks off, or wants to find anomalies, score novelty, or correlate its metrics. The trigger is a dashboard or notebook as the data source, not a general DQL question. This skill extracts timeseries queries efficiently without reading the full raw document JSON, then optionally runs Davis analyzers on the extracted metrics. "novelty score", "correlate metrics", "extract DQL from dashboard", "dashboard URL", "tile", "run-analyzer", "timeseries extraction", "Davis analyzer".

Core DQL syntax, pitfalls, query patterns, and query optimization. Load to write, build, fix, or OPTIMIZE a DQL query — prevents syntax errors and makes queries faster, more efficient, and cheaper (less data scanned = lower query consumption/cost per run). Covers fetch commands, data models, field namespaces, time alignment, entity/smartscape patterns, metric discovery, and performance/cost optimization (filter early, bucket filters, short time ranges, field selection, sampling, cardinality). Trigger: \"write/build/fix a DQL query\", \"DQL syntax\", \"query logs/spans/metrics\", \"create a timeseries\", \"optimize my DQL\", \"make my query faster/cheaper\", \"reduce DQL cost/consumption/scanned data\", \"keep DQL cost under control\". Do NOT use to explain an existing query or answer product questions. For MONITORING a tenant's ACTUAL query consumption/billing (how much queries cost, who scanned most, cost trends) use dt-platform-costs — this tunes the query text, not billing data.

Real User Monitoring (RUM) on Dynatrace — web and mobile frontends. Core Web Vitals, user sessions, page performance, mobile crashes, frontend errors, and frontend-backend linking. Query via `user.events`, `user.sessions`, and `dt.frontend.*` metrics. Does NOT cover synthetic monitoring (HTTP/browser/network checks) — that's a separate domain.

>- Analyzes observability signals from customer GenAI applications with DQL. Reads OpenTelemetry GenAI spans and LLM evaluation bizevents. (model, provider, tokens); cost/token analytics, usage attribution, and prompt caching; agent signals (tool calls, steps, failures, loop detection, Smartscape topology); conversation/session analytics; guardrails (blocked/truncated responses); and evaluation signals (quality, pass/fail). "cost per conversation", "who is driving token spend", "do I have prompt caching", "failing agent tool calls", "find runaway agents", "responses truncated or blocked", "failed evaluations", "am I hitting rate limits", "token throughput / TPM", "provider throttling or 429s". metrics (dt-obs-services), logs (dt-obs-logs), or non-GenAI tracing (dt-obs-tracing).

Predictive analytics for Dynatrace — time series forecasting with the timeseries-forecast tool, capacity saturation planning, trend and anomaly detection across hosts, services, and infrastructure.

>- Service performance monitoring with RED metrics (Rate, Errors, Duration) and runtime-specific telemetry for Java, .NET, Node.js, Python, PHP, and Go. Use when analyzing service health, SLA compliance, or runtime issues. "service mesh overhead", "JVM GC", "Java heap", "Node.js event loop", ".NET CLR", "Python threads", "PHP OPcache", "Go goroutines", "service performance", "p95 latency", "request failures", "database response time by name". Do NOT use for explaining existing queries, product documentation questions, infrastructure metrics (use dt-obs-hosts), log analysis (use dt-obs-logs), or distributed tracing workflows (use dt-obs-tracing).

This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs. Use this skill when the user provides chart images and requests technical analysis, trend identification, support/resistance levels, scenario planning, or probability assessments based purely on chart data without consideration of news or fundamental factors.

> A standardized CLI wrapper for RDKit 3D/2D conformer generation that samples multiple conformers per molecule (ETKDGv3, default 10), optimizes each with a force field (MMFF94s/UFF), keeps the lowest-energy conformer, automatically falls back to 2D layout on total embedding failure with a printed warning, and writes results to SDF or XYZ format. USE WHEN you need to generate 3D (or 2D fallback) molecular geometries from SMILES datasets (.csv/.smi) for downstream tasks such as docking, visualization, or 3D-descriptor computation.

> A standardized CLI wrapper for RDKit molecular featurization workflows that handles physicochemical descriptor computation (outputs .csv) and molecular fingerprint extraction (outputs .npy or .csv), with built-in SMILES validation. USE WHEN you need to compute RDKit molecular descriptors or fingerprints from SMILES datasets (.csv/.smi), or when you want to list all available descriptor names and presets.

> Odoo 17 development reference for Python models and ORM (search, domain, read_group, compute fields), XML/CSV data and views, OWL/JS client code, QWeb reports, security (ACL, record rules, groups), cron and server actions, migrations and module upgrades, tests, i18n, and performance. Use this skill whenever work involves Odoo 17 or custom addons—even if the user only pastes a traceback, mentions addons/ or __manifest__.py, describes form/tree/kanban/XML errors, HTTP controllers, or business rules on models—including building features, fixing bugs, refactoring, or reviewing addon code.

> Odoo 16 development reference for Python models and ORM (search, domain, read_group, compute fields), XML/CSV data and views, OWL/JS client code, QWeb reports, security (ACL, record rules, groups), cron and server actions, migrations and module upgrades, tests, i18n, and performance. Use this skill whenever work involves Odoo 16 or custom addons—even if the user only pastes a traceback, mentions addons/ or __manifest__.py, describes form/tree/kanban/XML errors, HTTP controllers, or business rules on models—including building features, fixing bugs, refactoring, or reviewing addon code.

> Odoo 18 development reference for Python models and ORM (search, domain, read_group, compute fields), XML/CSV data and views, OWL/JS client code, QWeb reports, security (ACL, record rules, groups), cron and server actions, migrations and module upgrades, tests, i18n, and performance. Use this skill whenever work involves Odoo 18 or custom addons—even if the user only pastes a traceback, mentions addons/ or __manifest__.py, describes form/list/kanban/XML errors, HTTP controllers, or business rules on models—including building features, fixing bugs, refactoring, or reviewing addon code.

Generate charts: select type, extract data, render image.

Analyze Excel/CSV files with DuckDB SQL via bash.

Consulting-grade research reports: framework + final report.

Stand up the dashboard foundation (the platform layer — UI primitives, form system, charts, Repository + adapters, auth seam, theme, routing shell) into a new project as a zero-config runnable app. Run this FIRST when building a dashboard, then compose screens from the add-component catalogue's shapes (add-detail-page, add-kanban, …) and the add-backend operation skill.

Add a copy-ready admin UI building block to a dashboard built on the scaffold-dashboard base — forms (form, wizard, combobox, file upload, inline edit), lists & tables (CRUD list, card grid, infinite/virtual, column controls, filter panel, saved views, CSV export/import), rich views (kanban, calendar, tree, timeline, master-detail), detail & pages (detail/show, record tabs, related records, multi-column layout, settings, chart/dashboard), display & feedback (tags/metadata/progress, empty/loading/error states, notification center, audit trail), and platform features (RBAC, social/magic-link auth, ⌘K global search, i18n, billing, realtime). Each entry has a reference doc with the exact copy + rewire steps.

Turn rich agent answers and any file, folder, URL, or export into a polished single-file HTML page. Auto-picks a default route plus 17 concrete design systems (teaching, dashboard, atlas, timeline-story, document, …).

>- Runs real-user QA, manual test plans, UX bug hunts, build sign-off, bug filing, and bug triage for web or iOS/iPadOS apps. Use when asked "QA this", "is this ready to ship?", or similar. Produces P0/P1/P2 bug reports, YES/NO phase sign-off, tracker sync guidance, and an HTML QA dashboard; keeps Interactive BRB triage in a separate session.

| (1) User provides a Snowflake query_id (UUID format) to analyze or optimize (2) Task mentions "slow query", "optimize", "query history", or "query profile" with a query ID (3) Analyzing query performance metrics - bytes scanned, spillage, partition pruning (4) User references a previously run query that needs optimization Fetches query profile, identifies bottlenecks, returns optimized SQL with expected improvements.

| (1) User asks to find slow, expensive, or problematic queries (2) Task mentions "query history", "top queries", "most expensive", or "slowest queries" (3) Analyzing warehouse costs or identifying optimization candidates (4) Finding queries that scan the most data or have the most spillage Returns ranked list of queries with metrics and optimization recommendations.

Create testimonial and proof systems for websites. Use for testimonials, reviews, customer quotes, logo walls, metrics, press quotes, case-study excerpts, ratings, social proof, proof strips, trust sections, and copy that must be credible, approved, and specific.

Full health check of all your skills in one report. Use when the user wants to check for errors, find duplicates, detect broken skills, or get a complete overview of skill health. Pass --brief for inventory only. Trigger with '/janitor-report'.

Agent-callable Google Analytics 4 (GA4) tools — run analytics reports, discover the dimensions and metrics a property supports, navigate accounts and properties, manage key events and custom dimensions/metrics, and send Measurement Protocol events. Use when the user mentions Google Analytics or GA4, or wants website/app traffic, conversion, or reporting data — including requests that don't name GA4 explicitly, e.g. how many users visited last week, top pages by country.

Agent-callable Google Sheets tools — read and write spreadsheet data as rows or raw cells, manage worksheets and columns, and apply formatting, sorting, and validation. Use when the user mentions Google Sheets or wants to read, add, update, look up, or organize spreadsheet data, even if they don't name Sheets explicitly.

Agent-callable Google Sheets tools — read and write spreadsheet data as rows or raw cells, manage worksheets and columns, and apply formatting, sorting, and validation. Use when the user mentions Google Sheets or wants to read, add, update, look up, or organize spreadsheet data, even if they don't name Sheets explicitly.

Use when 王建硕 wants to systematically grow his X (Twitter) followers by running numbered, A/B-testable growth experiments and tracking which ones actually work. Every action gets a number, a hypothesis, a target metric, a before-state (for rollback), and a verdict. The North-Star metric is the new-follower ÷ profile-visit ratio (conversion) — every profile change is judged against it. Daily it ingests the X Analytics CSV export, scores each running experiment, and recommends keep / rollback. Triggers — "涨粉", "增加 X 粉丝", "X 涨粉实验", "follower growth", "A/B test my profile", "今天的涨粉检查", "/wjs-x-increasing-follower".

| 触发词：「data engineering」「data engineer」「数据工程」「数据工程师」「analytics engineering」

Investigate unexpected behavior and mysterious bugs. Use when the cause of a problem is unknown and the user needs to understand WHY something is happening — symptoms like: sudden unexplained changes in metrics or behavior, works locally but not in staging/production, inconsistent or intermittent failures, correct code producing wrong results, operations succeeding but having no effect, environment-specific failures, duplicate executions, stale data, or any \"why did this change?\" or \"why is this happening?\" situation. Covers infrastructure anomalies (cache hit rates dropping, latency spikes, queue behavior shifts) as well as code bugs. The key signal is confusion about root cause, not a request to implement a known fix. Do NOT use for feature requests, known fixes, planning, or documentation tasks.

Judge product usability and evidence quality. Use when running Persona-based walkthroughs on a built product, planning an expert heuristic review, defining evidence-backed success metrics, or checking quantitative claims without inventing measurements. Use lamina-research to plan or synthesize evidence collection and lamina-ux to design interaction behavior.

Add, review, or remove inline custom scripts on a Webflow site (up to 10,000 chars). Use for analytics, tracking pixels, chat widgets, or any custom JavaScript. Also manages page-level scripts.

Generate comprehensive ontological knowledge graphs in [[wikilinks]] syntax for InfraNodus visualization. Use when the user requests to create an ontology, extract entities and relationships from text, or generate knowledge graph structures. Handles both topic-based ontology generation and entity extraction from existing text. Output is formatted for direct paste into InfraNodus.com for network visualization and AI-powered gap analysis.

Use when user requests diagrams, flowcharts, architecture charts, or visualizations. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Generates .tldr JSON files and exports to PNG/SVG locally using @kitschpatrol/tldraw-cli.

Full-pipeline iOS App Store opportunity research. Discovers underserved niches, analyzes competitor gaps, estimates revenue, produces scored top-3 opportunity reports, and writes MVP PRDs — all through browser and web research. Use when the user wants to find profitable iOS app ideas, research App Store charts, analyze competitor apps (ratings, reviews, revenue, gaps), generate opportunity reports, or write MVP PRDs. Triggers on "find app opportunities", "app store research", "what app should I build", "research this app category", "find a gap in the app store", "ios app ideas".

[power-bi] Power BI PBIR Report Builder with IBCS Visuals. Generates Power BI report pages, visuals, and IBCS-compliant variance charts by writing PBIR JSON files directly into PBIP project folders. Use this skill EVERY TIME the user asks to: create a Power BI report page, add visuals to a report, generate KPI cards, create charts or tables in Power BI, build a dashboard layout with visuals, create IBCS variance charts, create actual vs plan visuals, or programmatically create Power BI visuals. Also trigger when the user mentions 'PBIR', 'IBCS', 'variance chart', 'variance table', 'actual vs plan', 'actual vs comparison', 'create visuals', 'add a page', 'build a report', 'KPI cards', 'place visuals', or wants to generate Power BI report content through code. If the user mentions any combination of Power BI + visuals/page/report/KPI/chart/table/IBCS/variance + create/build/generate/add, use this skill.

Render a finished BS report as a self-contained HTML page — score hero, filterable claims, readable on a phone, prints to a clean PDF. Use when the user wants to open, share, print, or show a report to someone who is not going to read a markdown table, or asks for "the HTML version", "something I can send", "a shareable page", or "make this readable".

Serverless Aura Graph Analytics (AGA) GDS Sessions — covers GdsSessions, AuraGraphDataScience, AuraAPICredentials, DbmsConnectionInfo, SessionMemory, get_or_create, remote graph projection with gds.v2.graph.project and gds.graph.project.remote, gds.v2 session endpoints, gds.v2.graph.construct, AuraDB Cypher API memory/sessionId projection, algorithms, write-back, and session lifecycle. Use for AuraDB-connected, self-managed Neo4j, or standalone DataFrame/Spark session workloads. Does NOT cover the embedded GDS plugin on Aura Pro or self-managed Neo4j — use neo4j-gds-skill. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover Snowflake Graph Analytics — use neo4j-snowflake-graph-analytics-skill.

Configure and operate the Neo4j Connector for Kafka (sink + source) and the native Neo4j CDC API. Covers Cypher/Pattern/CUD sink strategies, CDC-based and query-based source, exactly-once semantics, DLQ error handling, Confluent Cloud managed connector, schema registry (Avro/JSON), and native db.cdc.query cursor-loop patterns (Neo4j 5.13+ Enterprise/Aura BC/VDC). Use when streaming Kafka events into Neo4j, streaming Neo4j changes to Kafka, or querying Neo4j change events without Kafka. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle bulk CSV/file import — use neo4j-import-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.

Run Neo4j Graph Analytics algorithms (PageRank, Louvain, WCC, Dijkstra, KNN, Node2Vec, FastRP, GraphSAGE) directly inside Snowflake without moving data. Use when running graph algorithms against Snowflake tables via the Neo4j Snowflake Native App ("GDS Snowflake", "graph algorithms in Snowflake", "Neo4j Graph Analytics"). Covers the explore → prepare projection views → project-compute-write flow, the strict view/column type rules the graph engine requires, and exact SQL CALL syntax. Does NOT cover Cypher or Neo4j DBMS queries — use neo4j-cypher-skill. Does NOT cover Aura Graph Analytics — use neo4j-aura-graph-analytics-skill. Does NOT cover self-managed GDS — use neo4j-gds-skill.

> Aurora Smart Home orchestrator — routing layer for all smart home skills. Use this skill when the user asks ANY smart home question and you need to decide which skill to invoke, or when a task spans multiple skills (e.g., "build a sensor that shows on a dashboard and triggers automations"). Invoke aurora FIRST before reaching for a specific skill — it will route to the right specialist(s) and recommend the correct Claude model to keep automation, IoT, dashboard, ESP32, Node-RED, or any request about controlling or monitoring devices at home.