「edge」の検索結果

Use when the user asks to "package our proof points", "build reusable stat cards and case snippets", or "put proof where each pillar makes its claim"; turns claims-ledger-approved proofs into reusable proof modules — stat cards, case snippets, testimonial blocks, comparison proofs — each pinned to a message-house pillar and the ledger claim ID it substantiates, and flags any pillar making a claim with no approved proof behind it. Never adjudicates a proof: unverified or ledger-absent proofs are marked '[needs source]' and routed to the claims candidates. Not for adjudicating or substantiating claims — use offer-claims-registry; not for fabricating a benchmark to fill a gap — a missing proof is flagged, not invented; not for scoring narrative quality — use narrative-quality-auditor. 证据模块/证据卡/客户案例/主张对齐

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Use whenever datasets, cloud storage buckets, or data pipelines are mentioned — creating, saving, querying, listing, exploring, deleting, or processing data in S3, GCS, Azure Blob, or local storage. Also use when running any script that may create datasets as a side effect. Maintains a knowledge base at dc-knowledge/ (JSON + markdown). ALWAYS use this skill when the user creates a dataset, saves pipeline output, runs a data script, or references any storage bucket.

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Design any process, idea, problem, or body of knowledge into an ICM (Interpretable Context Methodology) workspace — folder structure as agent architecture — or restructure an existing folder, repo, or vault into one. Use when the user wants to (1) turn a recurring workflow into an agent-runnable folder pipeline, (2) organize scattered notes, files, or knowledge into a library one AI agent can walk, (3) map a team or company as connected context ("context map", "second brain", "team brain", "knowledge base for AI"), (4) audit a codebase or mixed folder into a walkable edit map (objects, processes, change-impact) so later agents can change it without slurping the tree, (5) audit or restructure an existing workspace to ICM conventions, or (6) says "make this an ICM", "ICM this", "map this repo", "audit this folder", "what would a change hit", "build me a workspace", or "structure this for agents".

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Extract facts from meetings and update your knowledge base — person profiles, chronological log, and index. Use when the user asks "ingest my meetings", "update my knowledge base", "extract facts from meetings", "sync meetings to wiki", "backfill knowledge", or wants their PARA/Obsidian/wiki profiles updated from conversation data.

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Build, refresh and query a deterministic code knowledge graph to cut orientation-token cost. Triggers: knowledge graph, graphify, code graph, god nodes, orientation cost, map the codebase, what connects, callers of, blast radius.

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When the user wants to optimize for entity recognition, Knowledge Graph, or entity-based SEO. Also use when the user mentions "entity SEO," "entity optimization," "Knowledge Graph," "Knowledge Panel," "entity signals," "brand entity," "entity linking," "entity relationships," or "entity-first content." For structured data, use schema-markup.

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Comprehensive global knowledge worker salary data with total market value calculations, sector breakdowns, geographic comparisons, and authoritative sources. USE WHEN discussing knowledge worker compensation, salary benchmarking, economic analysis of professional labor markets, or AI impact on wages.

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Confluence expert for spaces, knowledge bases, documentation, page layouts, macros, templates, and Jira-Confluence integration. Use for documentation strategy, space architecture, content organization, and collaborative knowledge management.

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Audit and repair an internal knowledge base — staleness, ownership gaps, orphans, duplication, and findability. Use when the wiki is untrusted, docs are out of date, nobody owns pages, or search returns the wrong answer.

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。

EU AI Act Knowledge Engine — authoritative regulatory Q&A grounded in 70 official EU source documents (including the 2026 Commission draft guidelines on Art. 6 high-risk classification — general principles, Annex I, Annex III). Answers any question about the AI Act with article-level citations from the full regulation text, Commission guidelines, EDPB/EDPS opinions, codes of practice, harmonised standards, FRIA guides, incident templates, and sector-specific guidance. This skill should be used when the user asks about the "EU AI Act", "AI Act regulation", "Regulation 2024/1689", "KI-Verordnung", asks to "explain an AI Act article", "what does Article X say", "AI Act requirements", "AI Act penalties", "AI Act timeline", "GPAI obligations", "high-risk AI", "prohibited AI practices", "AI Act and GDPR", "fundamental rights impact assessment", "AI Act standards", "AI Act national implementation", "AI literacy", "serious incident reporting", "Digital Omnibus", "AI regulatory sandbox", or any question about EU artificial intelligence regulation. Also triggers on German terms: "KI-Gesetz", "KI-Verordnung", "Hochrisiko-KI", "KI-Kompetenz", "Grundrechte-Folgenabschaetzung", "GPAI-Verhaltenskodex". For assessment workflows that produce a classification decision rather than a knowledge answer, offer to run a structured risk-tier classification in-session.

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。

Design learning tasks built on Ubuntu philosophy emphasising collective knowledge-building and mutual responsibility. Use when fostering collaboration that values community over individual competition.

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Design discipline-specific critical thinking tasks grounded in knowledge-contingent reasoning rather than generic skills. Use when embedding higher-order thinking into subject content.

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。

Expert knowledge for Azure VMware Solution development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring AVS networking/storage, HCX migrations, Horizon/VDI, vSAN clusters, or Azure-integrated backups, and other Azure VMware Solution related development tasks. Not for Azure Virtual Machines (use azure-virtual-machines), Azure Stack Edge (use azure-stack-edge), Azure Nutanix (use azure-nutanix), Azure Red Hat OpenShift (use azure-redhat-openshift).

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Expert knowledge for Azure Local development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when designing Azure Local clusters, SDN networking, multi-rack/disconnected setups, Arc VMs, or Stack HCI deployments, and other Azure Local related development tasks. Not for Microsoft Foundry Local (use microsoft-foundry-local), Azure Stack Edge (use azure-stack-edge), Azure Arc (use azure-arc).

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。

Expert knowledge for Azure IoT Operations development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring MQTT/OPC UA data flows, WASM/ONNX processing, Dapr/Fabric RT endpoints, or Arc Kubernetes deployments, and other Azure IoT Operations related development tasks. Not for Azure IoT (use azure-iot), Azure IoT Hub (use azure-iot-hub), Azure IoT Edge (use azure-iot-edge), Azure IoT Central (use azure-iot-central).

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。

Expert knowledge for Azure IoT Hub development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring IoT Hub/DPS routing, device twins, MQTT/AMQP clients, Device Update, or Cosmos DB event storage, and other Azure IoT Hub related development tasks. Not for Azure IoT (use azure-iot), Azure IoT Central (use azure-iot-central), Azure IoT Edge (use azure-iot-edge), Azure IoT Operations (use azure-iot-operations).

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。

Expert knowledge for Azure Nutanix development including decision making. Use when selecting NC2 on Azure regions, VM SKUs, and planning capacity, performance, availability, or cost, and other Azure Nutanix related development tasks. Not for Azure VMware Solution (use azure-vmware-solution), Azure Baremetal Infrastructure (use azure-baremetal-infrastructure), Azure Virtual Machines (use azure-virtual-machines), Azure Stack Edge (use azure-stack-edge).

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。

Expert knowledge for Azure IoT development including decision making, architecture & design patterns, and configuration. Use when managing Azure Device Registry X.509 PKI, ADR policies, IoT Hub cert revocation, or device schema namespaces, and other Azure IoT related development tasks. Not for Azure IoT Central (use azure-iot-central), Azure IoT Edge (use azure-iot-edge), Azure IoT Hub (use azure-iot-hub), Azure Defender For Iot (use azure-defender-for-iot).

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。

Expert knowledge for Azure Data Box development including troubleshooting, best practices, limits & quotas, security, configuration, and integrations & coding patterns. Use when using Data Box/Disk/Heavy for offline data copy, SMB/NFS uploads, REST APIs, CMKs/Key Vault, or NTFS ACL preservation, and other Azure Data Box related development tasks. Not for Azure Import Export (use azure-import-export), Azure Stack Edge (use azure-stack-edge), Azure Virtual Machines (use azure-virtual-machines).

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。

Expert knowledge for Azure Firmware Analysis development including best practices, security, integrations & coding patterns, and deployment. Use when configuring RBAC/service principals, uploading firmware via CLI/PowerShell/Python, mapping results to Device Registry, reading SBOM paths, or deploying workspaces with ARM/Bicep/Terraform, and other Azure Firmware Analysis related development tasks. Not for Azure Defender For Iot (use azure-defender-for-iot), Azure IoT Edge (use azure-iot-edge), Azure IoT Hub (use azure-iot-hub), Azure Confidential Computing (use azure-confidential-computing).

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。

Monthly, on the last weekday, light browser lane. Re-tests every named qualification test and every buyer segment against a month of this kit's own ledger evidence, then rewrites both files itself where the evidence disagrees with the assumption they were written on. It records every change in strategy/CHANGELOG.md with the ledger path that justified it. It sends only where you released the channel, never re-queues anyone, never edits the contacted ledger, and never writes a number it did not count out of a named file.

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Mines a pull request's review threads for lessons that generalize beyond that PR, reconstructs each against the actual code before deciding, checks whether it is already codified, and routes the genuinely-new, durable ones into Infrahub's internal documentation — `dev/knowledge/`, `dev/guides/`, `dev/guidelines/`, the `AGENTS.md` files, and `.agents/rules/` — proposing edits first and applying only with the user's approval. TRIGGER when: the user wants to turn PR review feedback into durable conventions, guidelines, or rules; capture recurring reviewer comments as internal documentation; or check whether review lessons are reflected in the knowledge/guides/guidelines/AGENTS.md/rules layer. DO NOT TRIGGER when: sweeping a feature's changes for documentation coverage across all layers → use `audit-docs`; extracting knowledge from completed spec directories → `speckit-opsmill-extract`; only replying to or resolving review threads → normal git/gh flow.

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。

Codebase'i knowledge graph olarak analiz et. Dependency, call graph, hotspot analizi.

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。

Interactive Archon integration for knowledge base and project management via REST API. On first use, asks for Archon host URL. Use when searching documentation, managing projects/tasks, or querying indexed knowledge. Provides RAG-powered semantic search, website crawling, document upload, hierarchical project/task management, and document versioning. Always try Archon first for external documentation and knowledge retrieval before using other sources.

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。