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概要と使いどころ
Map a LookML view/model/explore into ktx semantic layer sources. Covers the LookML to ktx primitive table, provenance tagging, and three worked examples (overlay, standalone from derived_table, standalone with sql_always_where). Load when the turn contains `.lkml` content.
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Installs and configures ktx, the open-source context layer for data agents — runs ktx setup non-interactively with hidden CLI flags, configures database connections and embeddings, installs agent integration, and verifies readiness. Use when the user asks an agent to add ktx to a project, connect data sources, install agent rules, ingest schema, or troubleshoot a local ktx install.
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。
Map a MetricFlow semantic_model or metric into ktx semantic layer sources. Covers the MetricFlow to ktx primitive table, `extends:` inheritance flattening, metric-type handling (simple / derived / ratio / cumulative / conversion), `model: ref('x')` resolution, and four worked examples. Load when the turn contains `.yml`/`.yaml` files with top-level `semantic_models:` or `metrics:`.
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。
Synthesize durable ktx wiki pages and semantic-layer sources from staged Notion pages, databases, data-source rows, and clustered Notion evidence. Load when a WorkUnit contains Notion raw files or Notion evidence chunks.
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。
ktx's semantic layer - a structured catalog of sources (tables/views), measures, joins, and segments expressed as YAML. Covers the schema and how to query it via `sl_query`. Use when the task involves querying pre-defined metrics (ARR, churn, retention, LTV, MAU) or reading SL source YAML to understand the catalog. Capture is handled by the `sl_capture` skill (memory-agent 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。
ktx's knowledge base - wiki pages for durable, reusable business knowledge. Covers capture workflow for user preferences, metric definitions, organizational conventions, and cross-references between wiki pages and semantic-layer sources. Loaded by the post-turn memory-agent only. The research agent reads wiki via `wiki_read`/`wiki_search` but does not write 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。
Use when generating a single installable agent that should keep learning, track sources, refresh research, propose repairs, or improve itself over time without becoming a multi-agent team.
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。
Debug live Azure Kubernetes Service (AKS) incidents with a read-only, evidence-first investigation. WHEN: pod crashes or Pending, CrashLoopBackOff, OOMKilled, ImagePullBackOff, node NotReady, DNS or ingress failure, connectivity timeout, network policy, SNAT exhaustion, node-pool scaling blocked by QuotaExceeded or InsufficientVCPUQuota, upgrade stuck, spot or zone disruption, a bare VMExtensionProvisioningError or AllocationFailed wrapper, an uncataloged capacity symptom, or 'investigate my AKS cluster'. DO NOT USE FOR: packet capture (use aks-network-capture); GPU or model-serving issues (use aks-gpu-inference); cluster creation or provisioning (use azure-kubernetes); cost (use cost-analysis from the optional azure-cost plugin); pod rightsizing (use azure-kubernetes); a fully qualified documented AKS signature with every required nested qualifier (use aks-known-issues); standalone failures on non-AKS Azure resources (use azure-diagnostics). Unqualified errors and open-ended incidents stay here only for AKS.
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 an Azure portal deep link to a specific blade/menu item for supported Microsoft.ContainerService, Microsoft.Kubernetes, and Microsoft.Compute resources using the aks-search-direct-mid semantic search API. WHEN: 'find where in the Azure portal to do something', 'search the portal for an operation', 'construct a portal link from a search query and a resource'.
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。
Forecast Azure spend and price planned resources or workloads. WHEN: "forecast Azure spending", "project next month cost", "compare forecast to my planning target", "how much will Azure cost", "estimate VM cost", "compare storage tiers", "compare Azure regions", "retail price", "EA rate card", "negotiated pricesheet". DO NOT USE FOR: configured budget health or alerts, bill analysis, cost spikes, rightsizing, or commitments.
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, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke agent, agent.yaml, agent insights, pull agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, prompt optimizer, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
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。
Run Azure compliance and security audits with azqr plus Key Vault expiration checks. Covers best-practice assessment, resource review, policy/compliance validation, and security posture checks. WHEN: compliance scan, security audit, BEFORE running azqr (compliance cli tool), Azure best practices, Key Vault expiration check, expired certificates, expiring secrets, orphaned resources, compliance assessment.
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 actual Azure spend, bill changes, and AKS or AI costs. WHEN: "Azure cost breakdown", "most expensive resources", "why did my bill increase", "cost spike", "unexpected charge", "Cosmos DB charges", "Foundry model costs", "AKS cluster cost", "namespace cost", "enable AKS cost analysis", "idle AKS capacity". DO NOT USE FOR: forecasts, pricing estimates, rightsizing, commitments, or budgets.
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。
Assess and improve the reliability posture of PaaS Applications (Azure Functions and Azure App Service). Scans deployed resources for zone redundancy, ZRS storage, health probes, and multi-region failover. Presents a feature-pivoted checklist, then drives staged remediation (CLI or IaC patches) end-to-end with user confirmation. WHEN: "assess reliability", "check reliability", "zone redundant", "multi-region failover", "high availability", "disaster recovery", "single points of failure", "reliability posture", "resiliency".
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。
Microsoft Cloud Security Benchmark (MCSB v2) control-domain taxonomy and NIST 800-53 / CIS Controls crosswalk for planning and reviewing Azure cloud resources.
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Build traceable internal-review proposal, RFI, RFP, tender, bid, and questionnaire responses from supplied questions and approved sources. Use to analyze questions, contribute business or product evidence, or draft qualified responses.
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Build Godot 4.7 user interfaces with Control nodes: anchors and offsets for responsive layout, Container nodes (VBox/HBox/Grid/Margin) for automatic arrangement, Theme resources for consistent styling, and keyboard/gamepad focus navigation. Use when laying out a HUD, menu, or UI in a Godot project, working with Control/Container nodes, anchors, themes, or focus in a .tscn.
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Answer questions using the Arkon knowledge base. Searches wiki first, drills into raw sources only when needed. Supports quick, standard, and deep modes. Triggers on: what do we know about, find in KB, look up, query:, arkon query, search the wiki, tell me about, based on the KB.
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A-share sector research: computes board-wide Top N gainers, cross-checks week/month announcement windows across two sources, and grades market-sentiment evidence (L1–L3), via parallel Agent Team execution with fresh-context adversarial verification. Use for 「XX 行业 Top N/Top 10 标的」, 「这些标的最近一周/一个月发过哪些公告」, 「判断 XX 行业/板块现在的市场情绪」, or 「用 Agent Team 做行业投研」/对抗验证行业研究结论。
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Collects real financial data for any US publicly traded company from free public sources (yfinance) and outputs structured JSON for downstream skills (DCF modeling, comps analysis, earnings review): market data, historical financials, WACC inputs, analyst estimates — never fabricated fallback values. Use to collect or pull financial/market data, or gather DCF inputs, for a ticker.
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Runs adversarial due-diligence on a benchmark the user envies — a founder, KOL, company, or product whose success looks inflated — splitting marketing bubble from real signal, then mapping the validated playbook onto the user's own resources. Use for 尽调/对标/拆解 a competitor, 抄/偷师 their playbook, or suspecting 水分/泡沫 in claims. Prefer over deep-research when debunking inflated claims, not a neutral briefing.
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Verifies factual claims in documents using web search and official sources, then proposes corrections with user confirmation. Use when the user asks to fact-check, verify information, validate claims, check accuracy, or update outdated information in documents. Supports AI model specs, technical documentation, statistics, and general factual statements.
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 credit history from zero in a new country — understand that credit doesn't transfer across borders, get the first products that report, avoid the newcomer traps, and reach a usable score in months not years. Use when someone says 'I have no credit history in [country]', 'build credit as a newcomer/immigrant', 'why was I rejected with a great score back home', or 'how do I get a credit card/loan as a new arrival'. Produces a credit-building plan, the starter products that report, a timeline, and the traps to avoid. Educational, not financial advice; routes to official credit sources.
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Write a credit memo for a lending decision: borrower story, facility structure, repayment sources, financial-ratio spread with covenant headroom, risk factors with mitigants, risk-rating rationale, and a recommendation. Use when asked to write a credit memo, credit application, credit paper, loan write-up, or prepare a deal for credit committee. Produces a complete credit memo ready for committee review.
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。