「value」の検索結果

Answers business questions about the user's own spreadsheet or data export (CSV, TSV, XLSX from a CRM, Shopify, Stripe, QuickBooks, ad platforms, HR or payroll systems) correctly and auditably. Profiles every file first (grain, duplicate keys, embedded Grand Total rows, text-stored numbers, mixed currencies, UTC timestamps, Excel serial dates, hidden rows), states the metric definition used, computes every number in SQL or pandas instead of mental math, checks joins for fan-out, reconciles to a known total, and returns the query, filters, row counts, and rows behind the answer. Use this whenever the user says "analyze this spreadsheet", "how many...", "what's the total in this export", "which customers...", "pivot this", "revenue by month", "top 10", "what's our churn/MRR/AOV", or asks any question about their data, CSV, or Excel file, even a quick one. Also use when they ask to change values in a data file.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze spreads, over/unders, prop bets. Historical trends, situational stats, value bet identification. For entertainment/education only.

日本語の概要は準備中です。原文の説明を表示しています。

Audits business spreadsheet models (.xlsx, .xlsm, or Google Sheets exported to .xlsx) for structural integrity errors and explains each fix -- budgets, forecasts, pricing models, commission calculators, FP&A packs, ops trackers, not only banking models. A bundled openpyxl script finds hardcoded numbers inside formulas, typed values pasted over formulas, inconsistent formulas across a row or column,

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Pulls financial statement numbers for US public companies straight from SEC EDGAR's free official XBRL APIs (companyfacts, companyconcept, frames, submissions) into a cited table. Every value carries its accession number, form, fiscal period, filed date, XBRL tag and a link to the filing, and the tool handles fiscal-year ends, quarterly vs YTD vs TTM, derived Q4, restatements and units. Use this whenever the user wants 10-K numbers or 10-Q numbers, says "pull financials for", asks for public company revenue, net income, EPS, cash, debt or capex, wants comps or a competitor side-by-side, a credit check, prospect research, or model inputs, or mentions SEC filings or EDGAR, even if they never say XBRL. Free and primary-source, no paid data terminal needed. Do not use it for private companies, stock prices or valuation multiples.

日本語の概要は準備中です。原文の説明を表示しています。

Designs pricing strategies for products and services. Takes product/service, costs, target market, competitors. Analyzes cost-plus, value-based, competitor-based, penetration, premium models. Researches competitor pricing. Generates pricing-strategy.md with recommended model, price points, tier structure, discount policies, annual vs monthly analysis, sensitivity to churn, expansion revenue modeling.

日本語の概要は準備中です。原文の説明を表示しています。

Writes conversion-focused landing page copy - headlines, subheads, value propositions, feature and benefit blocks, social proof, FAQs, and CTA button text - using PAS, AIDA, or StoryBrand. Use when the user wants words for a landing page, sales page, product or pricing page, waitlist page, homepage hero, or ad-to-page flow, including rewriting weak copy, generating headline or CTA variants for A/B tests, or turning a product description into page sections. Use landing-page-optimizer instead for auditing an existing page's performance, and a frontend skill for building the page itself.

日本語の概要は準備中です。原文の説明を表示しています。

Builds a custom lead scoring model for a business. Takes ICP definition, historical win/loss data, CRM export. Analyzes which attributes correlate with closed-won deals. Generates lead-scoring-model.md with scoring dimensions, point values, thresholds, CRM implementation guide, and validation methodology. Can also score a batch of current leads against the model.

日本語の概要は準備中です。原文の説明を表示しています。

Merges, appends, joins, and deduplicates multiple CSV, TSV, and Excel files (including multi-sheet workbooks) with pandas - mapping mismatched column names to one schema, normalizing keys, resolving conflicting values, tracking which file each row came from, and verifying the row math. Use when the user wants to combine spreadsheets or exports, stack monthly files, consolidate contact or lead lists, VLOOKUP-style join two sheets on an ID or email, or dedupe records across sources, even if they only say "put these together" or "clean up these lists into one".

日本語の概要は準備中です。原文の説明を表示しています。

Audit and sync design tokens between the source of truth (tokens.json, Figma variables export) and the code that should consume them (Tailwind config, CSS custom properties, theme files). Finds drift -- hardcoded values, orphan tokens, out-of-date copies -- and fixes it in the right direction.

日本語の概要は準備中です。原文の説明を表示しています。

Build a quarterly business review from a client folder -- reports, usage exports, support tickets, meeting notes, emails. Extracts delivered value with receipts, surfaces risks before the client does, and drafts the QBR narrative plus expansion asks. For agencies, consultancies, and CS teams.

日本語の概要は準備中です。原文の説明を表示しています。

Build an insurance-grade home inventory from a folder of photos and receipts -- identifies items, pulls values from receipts, estimates replacement costs, organizes by room, and outputs the documentation an insurance claim actually requires. Update mode keeps it current after new purchases.

日本語の概要は準備中です。原文の説明を表示しています。

Writes, explains, debugs, and optimizes BI calculations - Power BI / Fabric DAX measures and calculated columns, Tableau calculated fields (FIXED/INCLUDE/EXCLUDE LOD expressions, table calculations), and Looker LookML measures, dimensions, and derived tables. Use it whenever the request involves DAX, CALCULATE, a Power BI measure, a Tableau calc or LOD, LookML, or a business metric such as YoY, YTD, rolling 12 months, running total, percent of total, distinct customers, ranking, new vs returning customers, closing balances, or basket analysis. Use it especially when someone says a measure "shows the wrong total", "is blank", "ignores my slicer/filter", "repeats the same value on every row", or "is slow" - those are filter context, context transition, LOD order-of-operations, or fanout bugs this skill is built to diagnose. Produces the formula, the context it evaluates in, and a hand-checkable test with expected numbers.

日本語の概要は準備中です。原文の説明を表示しています。

Use when you must prove an analysis ran on the intended data or lock a dataset version. Builds a deterministic content-hash manifest (file SHA-256, schema, per-column value hashes), verifies later copies against it for drift, and diffs two manifests.

日本語の概要は準備中です。原文の説明を表示しています。

Use when a tabular dataset (CSV, Excel, Parquet, Stata, SAS) needs a data dictionary. Profiles every variable (type, levels, range, missingness) into codebook.md and codebook.json and flags coded values of unknown meaning as [NEEDS DICTIONARY] instead of guessing.

日本語の概要は準備中です。原文の説明を表示しています。

Use when a clinical CSV/Excel dataset needs profiling and cleaning before analysis (missing values, outliers, duplicates, type mismatches). Profiles, flags and generates cleaning code in three stages, each gated on the researcher's approval. Never auto-cleans.

日本語の概要は準備中です。原文の説明を表示しています。

Business-logic flaw hunting - workflow/state bypass, price/quantity tampering, negative/overflow values, coupon/refund abuse, mass assignment, and logic races. The top-paying bug class with no scanner coverage. Wiki-first, FIND schema output.

日本語の概要は準備中です。原文の説明を表示しています。

Read huge, dense, read-only text as rendered PNG pages instead of raw text — image tokens scale with pixels, not characters, so token-dense bulk (big files, vendored code, diffs, logs) costs ~60–75% less as an image. Use when you must skim or reason over thousands of lines you will NOT edit or byte-copy. Lossy on exact strings: never for files you'll Edit, secrets, hashes, or byte-exact values. Fable-class readers only.

日本語の概要は準備中です。原文の説明を表示しています。

Create, scaffold, or generate Helm charts, Chart.yaml, values.yaml, templates, helpers.

日本語の概要は準備中です。原文の説明を表示しています。

Validate, lint, audit, check Helm charts — Chart.yaml, templates, values.yaml, CRDs, schemas.

日本語の概要は準備中です。原文の説明を表示しています。

Main app analytics tracking patterns (AnalyticsEvent enum, AnalyticsTrackerWrapper, KEY_*/VALUE_* constants). Use when writing, editing, exploring, debugging, or reviewing analytics tracking in the store management app. NOT for POS (WooPos*) code — use the `pos-analytics` skill instead.

日本語の概要は準備中です。原文の説明を表示しています。

Turn a curious developer into an activated one: the docs, the quickstart, and the first-run experience that gets them to their first real win fast, and back again. Use when people sign up or star the repo but never get it working, come once and never return, or you're about to pour traffic into a first-run that leaks.

日本語の概要は準備中です。原文の説明を表示しています。

Help the user decide what to charge and how to package it: the value metric, the tiers, the free-to-paid line, and finding the actual number. Use when the user is guessing at a price, priced too cheap and can't change it, is stuck on free vs paid, or believes "developers won't pay" so never charges.

日本語の概要は準備中です。原文の説明を表示しています。

Before showing the user any substantive GTM deliverable (positioning, value prop, homepage, launch post, pricing, sales script, the brief or roadmap), stress-test it against the standard as an independent critic, because the agent that wrote it is the worst judge of whether it is good. Use as a gate right before presenting work, or when the user asks whether something is actually strong.

日本語の概要は準備中です。原文の説明を表示しています。

Coach leaders and managers to prepare, run, and review high-bandwidth meetings that advance real work and decisions. Use for meeting retrospectives, employee work reviews, decision meetings, agenda and question design, direct feedback, meeting-quality diagnosis, or repeated low-value discussions. Preserve direct standards without taking over the worker's work or degrading the truth signal.

日本語の概要は準備中です。原文の説明を表示しています。