「tax」の検索結果

Company expense receipt workflow. OCR, rename, sort, summarize, and prepare receipt images/PDFs/videos for D365 expense mapping and attachment. Use when sorting company expense receipts, organizing travel expense files, OCR renaming, receipt sorting, expense sorting, レシート仕分け, 出張経費バッチ, D365経費仕分け, D365経費カテゴリマッピング, or D365経費精算. Not for personal or sole-proprietor tax receipts (確定申告).

Add or update the code syntax in demo app from all components

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Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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Diátaxis Documentation Expert. An expert technical writer specializing in creating high-quality software documentation, guided by the principles and structure of the Diátaxis technical documentation authoring framework.

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Generate diagrams of any kind from a description, ticket, spec, or file. Outputs Mermaid syntax (renders natively in GitHub, Notion, Confluence, Obsidian, Slack with apps) plus an optional single-file HTML preview that renders the diagram in the browser. Use this skill when the user says: - "draw a flowchart", "create a diagram", "visualize this flow" - "sequence diagram", "state diagram", "ER diagram", "class diagram" - "user journey", "mindmap", "timeline", "gantt", "org chart" - "sankey", "quadrant chart", "git graph" - or pastes a ticket / spec / description and asks for a visual Picks the right Mermaid diagram type for the input, asks if ambiguous, then emits clean syntax + an optional preview 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。

Explain, draft, or validate Obsidian Flavored Markdown syntax: properties, wikilinks, embeds, callouts, tags, comments, highlights, block references, math, and Mermaid. Use when the user explicitly requests Obsidian note formatting or syntax help, not for general Markdown or broad vault operations.

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Use this skill when setting up, configuring, or managing Salesforce Lightning Knowledge — enabling the feature, designing record types on Knowledge__kav, configuring Data Categories for organization and visibility control, setting up publishing workflows, and layering approval processes. Trigger keywords: Lightning Knowledge setup, Knowledge article record types, Data Category visibility, Knowledge publishing workflow, Knowledge__kav configuration. NOT for converting Classic Article Types to Lightning — use admin/knowledge-classic-to-lightning. NOT for bulk-loading articles from an external help center — use data/knowledge-article-import. NOT for sizing the taxonomy itself (how many groups, how deep) — use architect/knowledge-taxonomy-design.

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ที่ปรึกษาภาษีไทย — ภ.ง.ด.90/91/50, ลดหย่อน, tax planning, VAT, ภาษีนิติบุคคล รองรับบุคคลธรรมดา + บริษัท

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Automatically organize invoices and receipts for tax preparation by extracting key information, renaming files consistently, and sorting into logical folders. Transform chaotic bookkeeping into tax-ready records.

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。

Reference guide for using Xpoz effectively. Load this skill whenever working with Xpoz MCP tools, SDKs, or CLI — it ensures correct query syntax, optimal field selection, proper pagination, and best practices for every Xpoz interaction. Covers authentication, query syntax (boolean operators, date filtering), response modes (fast/paging/CSV), field selection, tracking setup, and all platform tool references (Twitter, Instagram, Reddit, TikTok). Use for ANY Xpoz-related work, not just explicit best-practices questions.

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Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2024 bioRxiv; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.

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Set up, audit, and debug analytics tracking implementation — GA4, Google Tag Manager, event taxonomy, conversion tracking, and data quality. Use when building a tracking plan from scratch, auditing existing analytics for gaps or errors, debugging missing events, or setting up GTM. Trigger keywords: GA4 setup, Google Tag Manager, GTM, event tracking, analytics implementation, conversion tracking, tracking plan, event taxonomy, custom dimensions, UTM tracking, analytics audit, missing events, tracking broken. NOT for analyzing marketing campaign data — use campaign-analytics for that. NOT for BI dashboards — use product-analytics for in-product event analysis.

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Agentes autônomos são sistemas de IA que conseguem decompor objetivos, planejar ações, executar ferramentas e se auto-corrigir sem orientação humana constante. O desafio não é torná-los capazes - é torná-los confiáveis. Cada decisão extra multiplica a probabilidade de falha. Esta habilidade cobre loops de agentes (ReAct, Plan-Execute), decomposição de objetivos, padrões de reflexão e confiabilidade em produção. Insight-chave: taxas de erro compostas matam agentes autônomos. Uma taxa de sucesso de 95% por passo cai para 60% b

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Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.

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Builds automated threat intelligence feed integration pipelines connecting STIX/TAXII feeds, open-source threat intel, and commercial TI platforms into SIEM and security tools for real-time IOC matching and alerting. Use when SOC teams need to operationalize threat intelligence by automating feed ingestion, normalization, scoring, and distribution to detection systems.

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Create, update, fix, or refine documentation using Diataxis framework and BMad Method style guide. Use when user asks to 'create a doc', 'update docs', 'fix docs style', 'refine docs', or 'improve docs writing'.

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Use when explaining or writing TBQ3 language syntax, including Params, Vars, Events, data types, variables, sequence variables, arrays, Map variables, control flow, operators, assignment, functions, and formula execution rules.

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。

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why.

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。

PRテンプレートの必須項目（日本語記載、Diátaxis、検証コマンド、チェックリスト）が明確かを確認し、抜けや誤解を生む文言を指摘する

Layered technical-writing standard: Diátaxis structure, Google developer style sentences, STE instruction rules, Global English syntax. Use for /technical-writing or when writing or reviewing docs, RFCs, readmes, PR descriptions, or commit messages.

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Assign transactions to tax-aligned expense categories using vendor name, line items, and amount patterns. Handles ambiguous vendors like Amazon by inspecting line-item detail from the receipt source. Supports split categorization and learns from user corrections. Trigger on "categorize expenses", "sort transactions", "assign expense categories", "what category is this".

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Extract structured data from receipts and invoices for bookkeeping, expense tracking, and tax preparation. Supports email, photos, scanned images, PDFs, and accounting exports. Outputs vendor, date, amount, tax, line items as table, CSV, or JSON. Trigger on "process receipts", "extract receipts from email", "scan invoices", "capture expenses".

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Calculate the home office deduction using either the simplified method ($5/sq ft, max $1,500) or actual expense method (Form 8829). Covers qualification rules, exclusive-use test, direct vs indirect expenses, and depreciation of home. Trigger on "home office deduction", "Form 8829", "can I deduct my home office", "work from home tax".

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Use for Nauthilus configuration loading, config schema and defaults, Viper-backed config formats, config dump behavior, vim syntax generation, template validation, prompt guideline sync, documentation under README/IDP/server docs, config converters, and generated documentation or syntax artifacts.

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。