Data & Analytics

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Bulk Q&A Answers skill for Datasite deal rooms. Use this skill whenever a sell-side deal team wants to answer multiple buyer questions at once, generate AI draft responses from VDR content, produce a Q&A tracker spreadsheet, or build a Q&A management dashboard. Triggers include: "answer the Q&A", "draft responses to buyer questions", "process the question list", "generate Q&A tracker", "answer all questions", "bulk answer", "Q&A management dashboard", "respond to diligence questions", or any request to systematically work through a list of buyer questions using data room content as the source. Use this skill proactively whenever a buyer has submitted questions and the deal team wants AI-assisted drafting. Do not use for individual one-off questions outside a structured Q&A process. Do not draft answers from general knowledge — all responses must come from the data room.

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VDR Index Setup skill for Datasite deal rooms. Use this skill whenever a user wants to create, propose, design, or set up a Virtual Data Room (VDR) index or folder structure for a deal. Triggers include: "set up a data room", "create a VDR index", "build a deal room structure", "prepare the index", "set up the fileroom", "I need a data room for [deal/company]", or any request to organise or structure documents for due diligence. Also triggers when a user wants to replicate an existing deal room structure or import an index from a spreadsheet or reference deal. This skill MUST be used whenever the user is starting a new deal room or wants to customise the folder hierarchy before documents are uploaded. Do not use to audit or review an existing data room — use gap-analysis, document-quality-check, or risk-analysis-audit for that.

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Use this skill 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.

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Codex-native Amazon PPC setup workflow using Wilco's exact-match and analytics-first strategy. Use when the user wants stricter keyword control, exact-match campaigns, and a LaunchFast-driven bulk-sheet export.

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Design KPI frameworks, set targets, and develop measurement plans that help teams make product or business decisions. Use when success metrics, drivers, guardrails, targets, or measurement approach need to be defined or improved. Use $metric-diagnostics when the task is to explain why an existing metric moved.

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Analyze and edit connected Google Sheets with range precision. Use when the user wants to create Google Sheets, find a spreadsheet, inspect tabs or ranges, search rows, plan formulas, create or repair charts, clean or restructure tables, write concise summaries, or make explicit cell-range updates.

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Use when reading, reviewing, inspecting, or reasoning about hosted Deepnote notebooks, blocks, inputs, SQL, Python, or notebook outputs through the Deepnote app tools.

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Produce leadership-ready KPI updates, scorecards, WBR/MBR/QBR summaries, target and pacing readouts, operating status narratives, and performance updates for known KPIs. Use when the work is to define KPI reporting context, validate metric definitions, present actuals versus comparison or plan, summarize validated drivers, and state implications or next actions.

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Estimate a market or opportunity size, such as TAM/SAM/SOM, by defining scope, choosing a sizing model, checking connected context and public sources, and presenting transparent assumptions, sensitivity, uncertainty, and validation priorities. Use for market or opportunity sizing; not for KPI reporting or metric diagnostics.

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Design, specify, implement, revise, and QA quantitative visuals and chart choices. Use when an analytical answer needs visual judgment; for example comparing values, showing how a total breaks apart, reading concentration in a ranking, or understanding movement over time. This may mean rendering a chart for a report or dashboard, or simply choosing, rendering and QAing the right chart form for an inline answer.

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This skill should be used when the user asks about Mixpanel product analytics, event data, funnel analysis, retention curves, cohort analysis, segmentation queries, user behavior, conversion rates, churn, DAU/MAU, ARPU, revenue metrics, feature adoption, A/B test results, user paths, flow analysis, or any request to query, explore, visualize, or analyze Mixpanel data using Python. Also use when the user asks to read, write, or manage Mixpanel "business context" — the markdown documentation that grounds AI assistants in an organization's structure and goals.

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Python development. Use for Python, FastAPI, Pydantic, asyncpg, pytest, pandas, SQLAlchemy.

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Build source-backed analytical dashboards that help teams monitor performance, explore drivers, and act on product or business metrics. Use when the user needs a dashboard, scorecard, monitoring view, BI dashboard, MCP artifact dashboard, or Streamlit dashboard with clear metrics, filters, validation, and handoff.

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Use when GrayMatter should support analytics work by retrieving durable context, checking retrieval receipts, loading the live api-docs schema, and helping create user/workspace-specific semantic layers without assuming tenant business objects exist.

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Create, scaffold, edit, refactor, and validate Jupyter notebooks (`.ipynb`) for reproducible SQL/Python analysis, experiments, modeling, tutorials, diagnostics, data-quality checks, market-sizing calculations, and report support. Use when the notebook itself is a deliverable, review artifact, runnable analysis companion, or handoff artifact that other people should be able to skim, rerun, or extend.

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Connect to MySQL and run read-only queries to inspect table data. Use when the user wants to query MySQL, show tables, view table contents, check schema, or run read-only SQL. Connection info must be provided by the user; do not read from environment or application config.

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Diagnose why a metric changed or differs from expectation by reproducing the metric, choosing the right comparison, validating likely drivers, and producing a calibrated explanation. Use when the user needs to understand what drove a metric movement, anomaly, gap, or discrepancy.

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Produce Public Equity Investing comparable-company valuation in report or workbook mode. Use for peer selection, multiple analysis, valuation read-throughs, implied prices, comps dashboards, Excel or Sheets comps, refreshable peer tables, model updates, and comps workbook QA. Do not use for DCF-only, credit-security, or generic market commentary requests.

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Convert markdown to DOCX, PPTX, XLSX, PDF office documents — use when you need exportable deliverables

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Use when creating Deepnote projects or notebooks, adding or updating blocks or cells, moving existing blocks, scaffolding notebook content, inserting SQL/code/markdown/input blocks, or otherwise editing notebook structure through the Deepnote app tools.

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Edit SharePoint-hosted spreadsheet files while preserving workbook structure, formulas, and formatting. Use when the user wants to update a real spreadsheet in SharePoint rather than summarize extracted sheet text.

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Find the Django ORM code and request path responsible for slow SQL by using APM traces, slow query logs, Django Debug Toolbar, query logging, and local reproduction. Use when a Django database performance issue is suspected but the exact queryset, view, serializer, template, or job causing it is not yet proven.

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Assess whether tables, query results, files, or dataframes are trustworthy enough for analysis, modeling, dashboards, experiments, or pipelines. Use for grain, freshness, nulls, duplicates, schema drift, broken joins, referential integrity, distribution shifts, leakage, backfills, source mismatches, automated quality checks, and data-quality regressions.

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Safely update public-company Excel model copies from source-to-model maps; emits XLSX as the hero artifact and CSV/log/manifest as support. Do not use for pure earnings notes or broad workbook audits.

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Read and compare Django/PostgreSQL query execution plans using QuerySet.explain(), EXPLAIN, EXPLAIN ANALYZE, scan types, joins, estimates, actual timing, buffers, and row counts. Use when one SQL query dominates Django latency or when an index, ORM rewrite, pagination change, or materialized view needs proof from a query plan.

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Gather business context from connected or provided sources so downstream analysis starts with the right framing. Use before deeper analysis when an analytical question depends on context the prompt does not provide, for example to understand what a metric means, how the work is defined, what changed recently, or which sources should be checked.

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Run or plan deep germline WGS, WES, targeted-panel, cohort, or trio variant-calling workflows with reference-build, known-sites, QC, joint-calling, and annotation checks.

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Use when adding, changing, testing, or reviewing Postgres persistence in Rust services that use sqlx, especially when designing migrations, query! or query_as! calls, PgPool injection, transactions, compile-time checked SQL, SQLx offline mode, repository boundaries, or database-backed integration tests.

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Use when the user asks about Codex token usage, model/reasoning efficiency, usage dashboards, CSV exports, or per-session/per-turn Codex usage stats from local logs.

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Analyze product or business data to inform decisions with focused quantitative work, decision-relevant context, measurable opportunities, and a clear recommendation. Use when the user needs data-backed evidence to choose a direction, prioritize an opportunity, evaluate a change, understand implications, or decide what to do next; not for routine KPI reporting, metric diagnostics, or dashboard building.

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Use when the user asks for D&B Finance Analytics workflows such as customer onboarding, credit decisioning, credit limit validation, portfolio risk management, company reports, ownership trees, folder management, or alerts. Use only the D&B Finance Analytics MCP tools for these workflows.

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Guide the user to add a data source, connection, or API connector to a Canvas App via Power Apps Studio, then verify and continue. USE WHEN the user asks to add a data source, add a connection, add an API, add a connector, connect to SharePoint / Dataverse / SQL / Excel / OneDrive / Teams / Office 365, or any similar request to make new data available to the app. DO NOT USE WHEN the user is asking to list or describe existing data sources — call list_data_sources or list_apis directly instead.

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Narrow conversion skill. Invoke only when the user explicitly asks to convert an existing Data Analytics report, dashboard, or inline chart export into a PDF artifact.

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Use when the task is to inspect existing Roistat saved reports through API, assemble a new report from scratch via analytics/data, fetch attribution slices, split new vs repeated leads/sales/clients, validate report logic against orders, or export a reproducible report pack without using the UI.

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Record Twilio voice calls correctly. Covers the critical distinction between Record verb (voicemail) and Dial record (call recording), dual-channel for QA, mid-call pause for PCI, Conference recording, and the ConversationRelay workaround. Use this skill whenever you need to capture call audio for compliance, QA, or analytics.

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Analyze nonfiction manuscripts for reader engagement signals, including heading-level word counts, slow starts, long slogs, weak takeaway titles, value pacing, beta-reader comment dropoff, and abandonment risks. Use when auditing a book, guide, manual, course-like draft, or technical manuscript for value density, reader experience, or beta-feedback engagement patterns.