Data & Analytics

catpilotai Skill

Block the language-agnostic classes of injection and arbitrary-code-execution failures — SQL via string concatenation, command injection via shell-true subprocess calls, XSS via `innerHTML`/`document.write`, path traversal via unvalidated filenames, insecure deserialization (`pickle`, unsafe `yaml.load`, PHP `unserialize`, Java `ObjectInputStream`, Ruby `Marshal`), dynamic code execution (`eval`, `Function`, `setTimeout(string)`), TypeScript `as any` escape hatches, and SSRF via unvalidated outbound URLs.

kesslernity Bundle

Converts a priced estimate spreadsheet into a DRAFT statement of work populated from the user's own SOW template, after checking that line items, hours, rates, subtotals and the grand total add up. Returns the populated SOW and a validation report as Markdown, flags every discrepancy and marks missing fields TBC. Use when the user asks to "turn this estimate into an SOW", "build the statement of work from the pricing workbook", "convert the quote into a scope document", "populate our SOW template from the estimate" or "draft the engagement document from the rate card". Do not use for reviewing or editing an existing SOW, use contract-review-pack instead; for a proposal before pricing is fixed use proposal-skeleton; for RFP or tender answers use rfp-response-drafter. Drafts for human review; never approves, authorises or signs off.

kesslernity Bundle

Turns an actuals-versus-budget extract (spreadsheet, export or pasted table) into a DRAFT variance table with absolute and percentage variances, favourable or adverse marking and a ranking by size, then drafts plain-language driver hypotheses for each material variance as questions to verify with a named owner, never as asserted causes. Use when the user asks to "explain these variances", "why are we over budget on this line", "write the variance commentary for the management pack", "actuals versus budget analysis" or "which lines drive the variance". Do not use for a dataset with no budget or comparison column, use dataset-insight-pack instead; for weekly operational figures against last week, use kpi-weekly-report-writer. Drafts for human review; never approves, authorises or signs off.

kesslernity Bundle

Prepares the trend update for a recurring emailed report: identifies report emails not yet processed, extracts the configured metrics from their spreadsheet, CSV or PDF attachments, returns new rows for an append-only trends sheet and writes a DRAFT summary with period-on-period deltas and flagged anomalies. Use when the user asks to "update the trends for the weekly report", "analyse the latest monthly report", "what changed in the latest report", "do the latest numbers look unusual" or "set up tracking for a report that arrives by email". Do not use for a single file with no trend state, use dataset-insight-pack instead. Drafts for human review; never approves, authorises or signs off.

kesslernity Bundle

Reads one spreadsheet, CSV export or pasted table together with the user's question and drafts an insight pack: a data profile, observations cited to named columns and values and framed as leads, caveats, and suggested charts and follow-up analyses. Every figure carries the label "as read, verify in source"; correlation is never stated as causation. Use when the user asks to "profile this spreadsheet", "what does this data say", "find anomalies in this extract", "give me a first read on this CSV" or "summarise this table". Do not use for a purchase order log or spend extract, use purchase-order-anomaly-review instead; for actuals versus budget, use budget-variance-explainer instead; for a report that arrives by email on a schedule, use report-attachment-analyzer instead. Drafts for human review; never approves, authorises or signs off.

kesslernity Bundle

Reads a purchase order extract (spreadsheet, CSV or pasted table) and returns a DRAFT question sheet for the buyer: possible split orders, round amounts, amounts just under an approval threshold, first-seen or near-duplicate vendors, duplicate orders and missing or self approvals, each a neutral question naming the PO numbers, never a finding. Use when the user asks to "review these purchase orders", "screen the PO log", "spot anomalies in this spend extract", "sanity-check the PO register" or "prepare buyer questions before the audit". Do not use for an expense claim or travel request checked against policy, use expense-policy-precheck instead. Drafts for human review; never approves, authorises or signs off.

kesslernity Skill

Reads a cash forecast (spreadsheet, model export, pasted table or the narrative that accompanies it) and returns a DRAFT assumptions sheet: every assumption the forecast rests on, stated or implied by the figures, with its value as read, its location in the model, the cash lines it drives, its stated source or "not stated", the evidence that would test it, an owner, and one neutral challenge question, so a reviewer can work through the assumptions one by one. Use when the user asks to "list the assumptions behind this cash forecast", "what is this cash flow forecast assuming", "prepare the challenge questions for the treasury review", "pull out the drivers of the 13-week cash forecast" or "build an assumptions register for the liquidity plan". Do not use for actuals against budget by line, use budget-variance-explainer instead; do not use for the case behind a capital request, use capex-request-pack instead. Drafts for human review; never approves, authorises or signs off.

wanlanglin Skill

Pull the handful of lines that matter out of a long command output, keeping them in their original order. Use when a test run, build, install, CI job, or training loop dumps hundreds or thousands of lines and you need the few that answer a specific question — why it failed, where it got slow, what changed, what ran out of memory. Say what you are looking for with --goal; the ranking is conditioned on it, so the same log returns different lines for different questions. Do NOT use for short output you can just read, or for structured data (JSON, CSV) where you want a parser rather than a filter.

jay-nair-builds Bundle

Analyse a stock or ETF like a CFA: fair-value forecast, under/overvalued read, brand-lens BBS score, portfolio view, pre-mortem, as a visual scorecard, dashboard or Excel model. Education only.

cloudquant Bundle

将 Word/PDF/PPT/Excel 等文档转为 Markdown 文件。用户提到 markitdown、word转markdown、word转md、convert_to_markdown 时触发

praveeng0823 Bundle

Mixpanel event tracking, done carefully from your code. Use to set up Mixpanel tracking, add tracking for a feature or onboarding, audit and clean up events, fix duplicate or badly named events, debug events missing in Mixpanel, or review tracking in a pull request. Reads the codebase only, explains each event in plain English, and waits for approval before changing code. Not for other analytics tools or for querying Mixpanel data.

hi-donwi Skill

Build large reporting and export endpoints that do not exhaust memory: streaming XLSX with Apache POI SXSSF, PDF with OpenPDF, ZIP packaging, database-side aggregation, async job submission with 202 plus polling or SSE progress, spool storage and cleanup, idempotency, and download authorisation. Use when an export is slow or runs out of memory, when building any endpoint in the reporting module, when a report exceeds a few thousand rows, or when adding progress reporting for a long-running job. Do not use for ordinary paginated list endpoints (rest-api-contract) or general query tuning (quarkus-persistence).

cloudquant Bundle

数据库只读查询技能。用于写 SQL/代码/配置前核对真实表名与字段定义，防止臆造。能力：按表注释模糊搜索表（queryTable）、按表名精确查表及字段（findTable）、查字段结构（queryTableColumns）、查指定表指定字段数据（queryTableData）。用户提到查库表、查表结构、查字段定义、字段含义、表注释、queryTable、findTable、queryTableColumns、queryTableData 时触发

kirrito-k423 Bundle

对 Codex 桌面版或 CLI 可用模型进行可复现的实际速度测试，比较 GPT-5.6 Luna、Terra、Sol 等模型、low/medium/high/xhigh 等推理档位以及标准与快速服务层。用户询问 Codex 模型测速、首响应延迟、输入 token 处理速度、输出 token 吞吐、Fast 加速比、模型速度矩阵、性能回归或要求生成 CSV/JSON/Markdown 测速报告时使用。仅在用户确认会消耗 Codex 用量后运行真实请求；查环境、生成计划、试运行和解析已有结果不消耗模型用量。

mohitagw15856 Skill

Build a real, formula-driven Excel (.xlsx) model — not a static table. Use when asked to build an Excel model, a financial model, a budget/forecast spreadsheet, or any .xlsx with live formulas a user can edit. Produces an actual .xlsx file via a generated openpyxl script: an inputs/assumptions sheet, calculation sheets with real cell formulas, and formatting — so changing an input recalculates the model. Requires a code-execution environment (Claude Code, the API code tool, or Claude.ai).

mohitagw15856 Skill

Extract every hidden assumption from a plan or document and put a price on each one — what it costs if wrong, what it costs to test. Use before committing to anything whose author says 'obviously' or whose spreadsheet has hardcoded cells: the bounty hunt makes the invisible load-bearing beliefs explicit and tells you which three to test this week. Produces the assumption ledger (priced and ranked), the cheapest test for each dangerous one, and the document's honest confidence statement.

mohitagw15856 Skill

Untangle the spreadsheet formula nobody dares touch — decompose the seven-function nest into named readable steps, explain what it actually does (vs. what it's believed to do), and rebuild it maintainably with helper columns and modern functions. Use when asked what does this formula do, this IFERROR-VLOOKUP monster broke, make this formula maintainable, or nobody understands the sheet the analyst left. Produces the plain-language decode, the step decomposition into helper columns, the believed-vs-actual gaps, and the rebuilt version.

mohitagw15856 Skill

Audit a spreadsheet before trusting it — the error hunt (hardcoded overrides, broken ranges, silent unit mixes), the fragility map (what breaks when rows are added), and the load-bearing-formula review that catches the mistake before the meeting does. Use when asked check this spreadsheet before we present it, why don't these numbers add up, audit this model someone left behind, or is this sheet safe to build on. Produces the findings ranked by damage, the fragility map, the verified-vs-suspect ledger, and the fix list.

mohitagw15856 Skill

Explains, optimises, writes, and documents SQL queries. Use when asked to explain a SQL query, optimise slow SQL, translate SQL to plain English for non-technical stakeholders, write a query from a natural language description, or produce query documentation. Produces plain-English explanations, annotated optimised queries, or a data dictionary covering output shape, assumptions, and known limitations. Works across PostgreSQL, MySQL, BigQuery, Snowflake, and standard SQL.

mohitagw15856 Skill

Cash runway as a distribution, not a number — Monte Carlo simulated. Use when someone asks how long their cash lasts, when to start fundraising, or how burn/revenue volatility changes their runway; especially when the naive cash÷burn answer is driving a decision. Produces P10/P50/P90 runway, month-by-month death probabilities, and a real .xlsx with editable assumptions and a live naive-runway formula — via the bundled zero-dependency simulator.

mohitagw15856 Skill

Which assumption actually moves the answer — one-at-a-time sensitivity, ranked into a tornado. Use when a model's output is being argued about (LTV, ROI, forecast) and the room is debating drivers that don't matter, or before spending diligence effort: swing every driver low→high and see which one owns the outcome. Produces the ranked tornado table, share-of-swing per driver, and a real .xlsx — via the bundled zero-dependency script with a safely restricted formula evaluator.

mohitagw15856 Skill

Fit a retention curve to observed cohort data and project LTV — computed, not estimated. Use when someone has real cohort retention numbers (month 0, 1, 2…) and asks what lifetime value, lifetime periods, or long-run retention they imply, or whether retention is flattening or leaking. Produces a fitted power curve (parameters, R², retention floor), a 24-36 period projection, and a real .xlsx with live formulas where editing ARPU recalculates LTV — via the bundled zero-dependency script.

mohitagw15856 Skill

Project completion as a distribution, not a date — Monte Carlo over the task graph. Use when a plan's finish date came from summing 'likely' estimates (it's wrong, mathematically), when leadership needs a commit date, or when you need to know which tasks actually control the timeline. Produces P10/P50/P90 completion, per-task criticality (how often each task sits on the critical path), and a real .xlsx — via the bundled zero-dependency simulator, deterministic with a seed.

mohitagw15856 Skill

Hand over a spreadsheet so it survives its author leaving — the README tab that decodes the sheet's logic, the update runbook with sources and cadence, the fragility warnings, and the walkthrough that transfers the judgment. Use when asked document this spreadsheet before I leave, hand over the model to the team, make this sheet survivable without me, or we inherited a workbook nobody understands. Produces the README tab content, the update runbook, the known-fragilities list, and the handover walkthrough agenda.

mohitagw15856 Skill

Design a budget-vs-actuals tracker that stays alive past February — the category grain that matches real statements, the variance view that answers 'are we okay', the update ritual small enough to survive, and the honest handling of irregular expenses. Use when asked build me a budget spreadsheet, track team spend against budget, why do we always blow the budget invisibly, or design a household/project budget tracker. Produces the tracker structure, the variance logic, the irregulars ledger, and the monthly fifteen-minute ritual.

mohitagw15856 Skill

Decide honestly when a spreadsheet should become a database or app — the five outgrowth signals (concurrent editing, relational strain, permission needs, scale, process-in-comments), what staying costs vs what migrating costs, and the incremental escape paths. Use when asked should this be a database, our spreadsheet is breaking, is it time to move off sheets, or what should replace this monster workbook. Produces the signal assessment on the actual workbook, the stay-vs-move verdict with costs both ways, and the migration path sized to the team.

mohitagw15856 Skill

Audit the user's REAL spreadsheet by opening it in the Cowork sandbox — not by reading a description of it. Use when asked to check this sheet before we present it, audit the model in my Drive, why don't these numbers add up, or is this spreadsheet safe to build on. Pulls the file via the Google Drive connector (or an uploaded .xlsx), opens it programmatically in the sandbox to trace formulas, hunts hardcodes / broken ranges / unit mixes, and produces a ranked findings artifact with a verified-vs-suspect ledger and a fix list.

mohitagw15856 Skill

How many support agents does the queue actually need — Erlang C, computed, not 'tickets per agent' folklore. Use when staffing a support/CS team, defending headcount, or checking whether an SLA is mathematically possible with the current roster. Produces agent counts across load scenarios (with shrinkage), occupancy and average-wait numbers, and a real .xlsx — via the bundled zero-dependency script.

mohitagw15856 Skill

Simulate the due-diligence call where an acquirer's or investor's analyst takes your metrics apart — the questions behind the spreadsheet, the moment a number wobbles, and a debrief on which answers create risk. Use when asked simulate due diligence on my startup, stress-test my metrics before the raise, what will the acquirer's analyst ask, or prep me for the DD call. Produces the call transcript with the analyst's private notes, the internal memo they write afterward, and a debrief separating fixable presentation from fix-the-business findings.

mohitagw15856 Skill

Van Westendorp price sensitivity, computed from real survey answers — crossings found by interpolation, not read off a chart by eye. Use when someone has (or plans) the four-question pricing survey (too cheap / cheap / expensive / too expensive) and needs the optimal price point, the acceptable range, and a defensible readout. Produces OPP/IPP and the PMC–PME range, the four cumulative curves as data, and a real .xlsx with a live revenue what-if — via the bundled zero-dependency script.

blockrunai Skill

Use this skill — NOT browser or web_fetch — for ALL Surf crypto-data calls. 83 endpoints at localhost:8402/v1/surf/* covering CEX/DEX markets, on-chain SQL over 80+ ClickHouse tables (Ethereum, Base, Arbitrum, BSC, TRON, HyperEVM, Tempo), 100M+ labeled wallets, prediction markets (Polymarket + Kalshi), social/CT intelligence, news, project + DeFi metrics, token analytics, unified search, VC fund intelligence. Paid through ClawRouter — x402 USDC from the local wallet, or BlockRun account credit if an API key is configured. No Surf account or Surf API key required either way.

oliver-kriska Bundle

Enforce Elixir/Phoenix security — auth, OAuth, sessions, CSRF, XSS, SQL injection, input validation, secrets. Use when editing auth files, login flows, RBAC, or API keys.

tinyhumansai Skill

Find out what actually moved a metric, before anybody reacts to it.

emadmokhtar Bundle

Summarise a CSV of regional sales into a Markdown report and a JSON totals file

ai-analyst-lab Skill

Show the provenance trace, linking every reported number to the SQL that produced it with a confidence badge. Use after an analysis when someone asks "where did that number come from?"

ai-analyst-lab Skill

Retrieve proven SQL patterns, table cheatsheets, and join patterns from .knowledge/query-archaeology/ so past work gets reused. Fire as a pre-flight step before writing ANY SQL. Also trigger on "do we have a known query for X", "how do we usually join these tables", "have we computed this metric before". If the store is empty or missing, exit silently. Also owns the writer convention: after a validated analysis, curate the final SQL here.