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概要と使いどころ
Use when building AI chat UIs with @ant-design/x components — covers Bubble, Sender, Conversations, Prompts, ThoughtChain, Actions, Welcome, Attachments, Sources, Suggestion, Think, FileCard, CodeHighlighter, Mermaid, Folder, XProvider, and Notification.
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。
使用 @ant-design/x 组件库构建 AI 对话 UI 时使用 —— 涵盖 Bubble、Sender、Conversations、Prompts、ThoughtChain、Actions、Welcome、Attachments、Sources、Suggestion、Think、FileCard、CodeHighlighter、Mermaid、Folder、XProvider 和 Notification。
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。
当需要用 @ant-design/x-card 让 AI Agent 动态渲染富交互 UI 时使用——涵盖 XCard.Box、XCard.Card、A2UI v0.9 命令、数据绑定、Catalog、Actions 和流式渲染模式。
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。
Automates browser interactions for web testing, form filling, screenshots, and data extraction using playwright-cli. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, extract information from web pages, mock network requests, manage browser sessions, or generate test code.
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。
Production-ready CI/CD configurations for Playwright — GitHub Actions, GitLab CI, CircleCI, Azure DevOps, Jenkins, Docker, parallel sharding, reporting, code coverage, and global setup/teardown.
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。
Battle-tested Playwright patterns for E2E, API, component, visual, accessibility, and security testing. Covers locators, fixtures, POM, network mocking, auth flows, debugging, CI/CD (GitHub Actions, GitLab, CircleCI, Azure, Jenkins), framework recipes (React, Next.js, Vue, Angular), and migration guides from Cypress/Selenium. TypeScript and JavaScript.
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 building Next.js 14+ applications with App Router, server components, or server actions. Invoke for full-stack features, performance optimization, SEO implementation, production deployment.
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。
Compute the EXACT sub-transaction impact of a rollup rule in TRES Finance — every filter applied — and flag genuine problems (zero matches, overlap, config mistakes) before the rule is created. Two modes. Mode A: a pre-create quality gate invoked by the tres-rollup-rules skill to vet proposed candidate rules. Mode B: standalone review of a rule someone submitted or of existing PENDING rules. Trigger this skill when the user says "review this rollup rule", "what would this rollup rule actually match", "preview the rollup impact", "how many transactions would this rule catch", "is this rollup rule valid", "validate my rollup rule", "check my pending rollup rules", or "review the rollup requests". Do NOT use this to design or propose new rollups — that is tres-rollup-rules. This skill only measures impact and flags issues; it never executes mutations.
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。
Reprice swap transaction legs under ASC 845 (Nonmonetary Transactions) to ensure clearing accounts net to zero. Use this skill whenever the user wants to: reprice swaps, fix clearing account residuals, apply equal-value exchange to swap legs, run setBatchUseCounterpartyFiatValue, zero out a clearing account, apply ASC 845, fix swap pricing mismatches, ensure no gain/loss on swaps, or close a month where a swaps/trade clearing account has a residual balance. Also trigger when the user mentions "counterparty fiat value", "swap repricing", "clearing account net to zero", or "equal value exchange".
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 any TRES Finance report XLSX and produce an automatic findings summary. Trigger this skill whenever a user uploads a .xlsx file that came from TRES Finance and asks to "analyze", "summarize", "review", "check", "audit", "look at", "what does this show", "any issues", "anything interesting", or "walk me through" the report. Also trigger when the user uploads an Excel file and mentions TRES, reconciliation, balances, transactions, cost basis, roll forward, or ERP sync. The skill identifies the report type from the file structure, runs targeted analysis based on report-specific logic, and produces a clear findings summary highlighting anomalies, key metrics, and action items.
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。
Match TRES ledger transactions to ERP invoices/bills (AP/AR) and optionally sync them to the connected ERP (Xero, QuickBooks Online, NetSuite). Trigger this skill whenever the user wants to match, link, close, reconcile, or sync an invoice or bill against a blockchain transaction — even if they don't say "skill" or use those exact words. Trigger phrases include: "match this invoice to a transaction", "match a bill to tx", "close invoice INV-123", "close bill 9988", "link this tx to a bill", "pay this invoice from this transaction", "set up this tx as AP", "set up this tx as AR", "sync this transaction as AP/AR", "match AP/AR", "find the invoice/bill for this hash", "what bill does this tx pay". Trigger ONLY for explicit AP/AR matching/closing intent — do NOT trigger for general transaction explanations (use tres-tx-story), for ingesting an explorer link into the ledger (use tres-explorer-tx-to-ledger), or for ERP connection setup itself (use tres-settings-management).
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。
Extract all 3rd-party (non-owned) addresses from a TRES Finance environment and export them as an XLSX workbook to help users build their contacts list. Use this skill whenever the user wants to export, list, or identify 3rd-party addresses, counterparties, or external addresses from their transactions — even if they don't say 'contacts'. Also trigger when the user asks to prepare a contacts import file, find unknown addresses, or build an address book from transaction history. Do NOT trigger for viewing existing contacts or searching the address book — only for extracting NEW 3rd-party addresses from transaction data.
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。
This skill covers game-theoretic methods in structural econometrics and industrial organization. Use when the user is working with strategic interactions, equilibrium analysis, or game-theoretic structural models — including entry games, conduct testing, auction models with strategic bidding, bargaining, or matching markets. Triggers on "Nash equilibrium", "subgame perfect", "best response", "strategic interaction", "entry game", "conduct testing", "auction", "mechanism design", "matching market", "bargaining", "BNE", "Bayesian Nash", "static game", "dynamic game", "repeated game", "multiple equilibria", "equilibrium selection", "discrete game", "oligopoly", "game-theoretic", "player", "payoff", "strategy", "dominant strategy", "Bresnahan-Reiss", "Ciliberto-Tamer", "partial identification", "set identification", or markup test.
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。
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
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。
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven + fixest + sandwich + lmtest + clubSandwich + AER + ivreg + did + bacondecomp + HonestDiD + eventstudyr + rdrobust + rddensity + Synth + gsynth + synthdid + MatchIt + WeightIt + cobalt + ebal + grf + DoubleML + mediation + marginaleffects + modelsummary + kableExtra + gt + ggplot2 + ggpubr + cowplot + binsreg. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step R pipeline an applied economist runs on every paper — (1) data import & cleaning (read_dta/read_csv, naniar, janitor, validate-merges), (2) variable construction (mutate/across/winsorize/group_by + lag/lead with dplyr), (3) descriptive statistics & Table 1 (gtsummary, modelsummary::datasummary, tableone), (4) classical diagnostic tests (shapiro/jarque.bera.test/bptest/dwtest/bgtest/vif/adf.test/kpss.test/Hausman), (5) baseline modeling (fixest::feols, ivreg, did::att_gt, eventstudyr, sun_ab, did_imputation, synthdid, rdrobust, MatchIt, WeightIt, grf::causal_forest, DoubleML, mediation), (6) robustness battery (modelsummary stack, clubSandwich CRSE, fwildclusterboot, ri2, robomit Oster, bacondecomp, HonestDiD), (7) further analysis (interactions + marginaleffects, mediation::mediate, gsem via lavaan, dose-response splines, grf CATE), (8) publication-ready tables & figures (modelsummary, kableExtra, gt, stargazer, texreg, flextable to LaTeX/Word/HTML; ggplot2 + ggpubr + cowplot + binsreg + iplot for figures). **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation, IPTW + g-formula + TMLE doubly-robust triplet via `WeightIt` / `gfoRmula` / `tmle` / `ltmle`, Mendelian randomization via `MendelianRandomization` / `TwoSampleMR` / `MRPRESSO`, KM / Cox / AFT / RMST survival via `survival` / `survminer` / `flexsurv`, E-value sensitivity via `EValue`, principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `DoubleML`, S/T/X/R/DR meta-learners via `causalweight` / `grf`, causal forest via `grf::causal_forest`, BART/BCF via `bartCause` / `bcf`, matrix completion via `MCPanel`, CATE distribution + policy tree via `policytree`, off-policy evaluation, conformal causal via `conformalInference` / `cfcausal`, fairness audit via `fairmodels`, DAG learning via `pcalg` / `bnlearn` / LLM-assisted). Use when the user asks for a complete R empirical analysis, wants a tidyverse-style reproducible R script / Quarto workflow, prefers fixest over reghdfe, needs the R counterpart to StatsPAI / 00.1 / 00.2, or names a specific R step in isolation ("feols with cluster", "MatchIt nearest neighbor", "bacondecomp in R", "gtsummary table 1", "modelsummary to Word"). Mode A triggers on "target trial emulation R", "tmle ltmle", "MendelianRandomization", "TwoSampleMR", "MRPRESSO", "survival cox AFT", "STROBE R", "EValue R", "公共健康 R", "流行病学 R". Mode B triggers on "DoubleML R", "grf causal forest", "policytree", "bartCause bcf", "conformal causal R", "fairmodels", "pcalg NOTEARS", "因果机器学习 R".
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。
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc + binscatter. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step Stata pipeline an applied economist runs on every paper — (1) data import & cleaning (use/import, destring, misstable, duplicates, merge assert), (2) variable construction (gen/egen/winsor2/xtile/xtset with L./F./D.), (3) descriptive statistics & Table 1 (tabstat/balancetable/asdoc), (4) classical diagnostic tests (sktest/swilk/hettest/imtest/xtserial/xttest3/vif/dfuller/kpss/hausman/estat overid), (5) baseline modeling (reg/xtreg/reghdfe/ivreg2/ivregress/csdid/did_imputation/eventstudyinteract/sdid/rdrobust/synth/psmatch2/teffects/heckman/qreg/ppmlhdfe), (6) robustness battery (bacondecomp/honestdid/rwolf/ritest/wildbootstrap/oster), (7) further analysis (subgroup/triple-diff/interactions/medsem/marginsplot/binscatter by group), (8) publication-ready tables & figures (esttab/outreg2/estout/coefplot/marginsplot/rdplot/twoway combined). **Also covers two parallel domain modes that share the same 8-step scaffolding** — **Mode A — Epidemiology / public health** (target-trial emulation, IPTW + g-formula + TMLE doubly-robust triplet via `teffects ipw` / `teffects ipwra` / `teffects aipw` / `eltmle`, Mendelian randomization via `mrrobust` (IVW / Egger / weighted median) and `mregger` / `mrpresso`, KM / Cox / AFT / RMST survival via `sts` / `stcox` / `streg` / `strmst2`, E-value sensitivity via `evalue` (Linden-Mathur), principal stratification — STROBE / TRIPOD reporting), and **Mode B — ML causal inference** (DML via `ddml` / `pdslasso`, S/T/X/R/DR meta-learners via `crforest` and `ddml interactive`, causal forest via `crforest` / `cforest`, BART/BCF via `bart` / `bartCause`-style externals, CATE distribution + policy tree via `crforest`, off-policy evaluation, conformal causal externals, fairness audit, DAG learning via `pcalg` / external Python callouts). Use when the user asks for a complete Stata empirical analysis, wants a reproducible .do-file pipeline, needs a Stata counterpart to the Python StatsPAI / Full-empirical-analysis-skill, or names a specific Stata step in isolation ("run reghdfe with two-way clustering", "csdid event study", "winsor2 at 1%", "esttab to LaTeX", "coefplot with CI", "ivreg2 weak-IV test", "synth_runner placebos", "teffects psmatch balance check"). Mode A triggers on "target trial emulation Stata", "teffects ipw aipw", "eltmle", "mrrobust", "mregger weighted median", "stcox AFT survival", "strmst2", "evalue Stata", "STROBE Stata", "公共健康 Stata", "流行病学 Stata". Mode B triggers on "ddml Stata", "pdslasso", "crforest causal forest Stata", "policy tree Stata", "因果机器学习 Stata".
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。
Review or de-slop concrete changes in ccch1mneyyy/dsh-TUI at maintainer level: PR numbers or URLs, branches, commit ranges, patch files, staged or unstaged worktrees, and scoped repository-hygiene requests. Use for evidence-first correctness, contract, repository-rule, process, and behavior-preserving cleanup review, including debug residue, dead or duplicate code, speculative abstractions, stale comments or tests, and unrelated diff churn. Do not use for abstract designs with no concrete repository artifact; use audit for repository-wide assessments and vuln-check for security-only checks.
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。
How to work in a Worldbuilding project (the `worldbuilding` starter pack): a fiction encyclopedia of characters, settings, themes, factions, and lore. Read when the project has these folders, OR when asked to add a character, setting, faction, or piece of lore, or to check the world for internal consistency. Carries the auto-stub and consistency behaviors so that guidance does not live inside template bodies or folder descriptions. Complements the platform `open-knowledge` skill; does not replace it.
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 one approved master still into a character's whole animated sprite set - one image-to-video clip per action (idle, walk, run, attack, jump, hurt, cast and so on), all from that still, generated through generate2dmedia route_media.py (the xAI API when a key is configured, else the local Grok CLI) - then gate each take, key it with a soft matte, register it to the master, pick loops or retime actions, finish (HD by default, pixel on request) and package fixed-canvas frames, alpha WebM, packed MP4 for iPhone and a PNG fallback with engine metadata and a JS runtime. Also processes a supplied clip. Use for character and creature animation, fluid motion and any video-to-sprite work. Not for FX, icon or prop sheets (generate2dsprite), maps or plate loops (generate2dmap), code-drawn animation (codeart2d, only on request) or calling a video API by itself (generate2dmedia).
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。
Inspect or change the sidebar thread list's layout preferences: organization mode, sort, section order, hidden groups, collapsed groups, and thread row actions.
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。
Examine what a file claims about itself and what it actually contains — powered by Apache Tika. True content-based type detection (extensions lie), provenance claims (authors, dates, creating application), revision and tamper signals (PDF incremental updates, tracked changes, hidden slides, zip integrity), hidden and embedded content (attachments, macros), risk indicators (PDF JavaScript actions, encryption), and content digests. Evidence gathering, not verdicts: Tika reports what the file asserts and what parsing observed; it does not attribute authorship or validate signatures. Use for triaging suspicious files, provenance questions, e-discovery-style review, or "is this file what it claims to be."
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。
Comprehensive guide for AntV L7 geospatial visualization library. Use when users need to: (1) Create interactive maps with WebGL rendering (2) Visualize geographic data (points, lines, polygons, heatmaps) (3) Build location-based data dashboards (4) Add map layers, interactions, or animations (5) Process and display GeoJSON, CSV, or other spatial data (6) Integrate maps with AMap (GaodeMap), Mapbox, Maplibre, or standalone L7 Map (7) Optimize performance for large-scale geographic datasets
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。
Inspect and manage guarded Codex App-native or launchd heartbeats for Codex main control threads. Use when the user wants Codex to periodically continue a specific thread only when it is idle, avoid interrupting active work, keep App-visible interactions, inspect thread status, or enable/disable project autopilot heartbeats.
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。
Swift Concurrency review and remediation for Swift 6.2+. Use when asked to review Swift Concurrency usage, improve concurrency compliance, or fix Swift concurrency compiler errors in a feature or file. Concrete actions include adding Sendable conformance, applying @MainActor annotations, resolving actor isolation warnings, fixing data race diagnostics, and migrating completion handlers to async/await.
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。