「ai governance」の検索結果

Use when Codex must make a high-quality judgment on any complex problem, not only technical problems. Trigger when a question has high complexity, uncertainty, cost of being wrong, long-term impact, value tradeoffs, possible structural causes, or when the user asks for 全面思考, 深度理解, 系统性分析, 帮我想清楚, 从根上看, 这件事到底怎么看, 方法论, 复杂问题拆解, 系统方案, 架构判断, 策略判断, or 根因分析. Also trigger for project and engineering high-risk scenarios such as multi-module, multi-environment, multi-data-source, multi-state, financial truth, live trading, ledger, revenue, customer assets, order governance, broker interfaces, online availability, major solution selection, and system closure.

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Register trained models in MLflow Model Registry with version control, implement stage transitions (Staging, Production, Archived) with approval workflows, and manage model lineage with comprehensive metadata and deployment tracking. Use when promoting a trained model from experimentation to production, managing multiple model versions across development stages, implementing approval workflows for governance, rolling back to previous versions, or auditing model changes for compliance.

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Maintain schema-governance contracts and related Odylith registry truth.

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Maintain Odylith delivery and governance surfaces after source-of-truth changes.

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Maintain governance artifacts without implementation work. Use when: (1) Accepting or refining ADRs, (2) Clarifying or amending RFCs without code changes, (3) Governance-only docs/check/render updates

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"Apply Agency Theory (Jensen and Meckling, 1976) to diagnose principal-agent problems — moral hazard, adverse selection — and design governance mechanisms to align interests. Use this skill when the user needs to analyze conflicts of interest between owners and managers, design incentive or monitoring structures, evaluate corporate governance effectiveness, or when they ask 'how do we ensure managers act in shareholders interest', 'why is this incentive plan failing', or 'what governance mechanisms reduce agency costs'.".

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Audit ESG reporting software and sustainability metric accuracy. Analyzes Environmental (Scope 1/2/3 emissions, water, waste, biodiversity), Social (workforce diversity, pay equity, human rights due diligence), and Governance (board composition, ethics, risk) data collection against GRI.

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Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse instead).

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Use this skill when building or maintaining a Requirements Traceability Matrix (RTM) on a Salesforce project: one row per requirement, columns for source, user-story id(s), test-case id(s), defect id(s), sprint, release, and status. Covers forward traceability (req → story → code → test) and backward traceability (test → req). Trigger keywords: RTM, requirements traceability matrix, audit trail for salesforce delivery, traceability for steerco, deferred requirement tracking, regulatory traceability. NOT for eliciting the requirements in the first place — use admin/requirements-gathering-for-sf. NOT for user-story authoring — use admin/user-story-writing-for-salesforce. NOT for UAT test design — use admin/uat-test-case-design. NOT for Apex test design — use apex/test-class-standards. NOT for backlog prioritization — use admin/moscow-prioritization-for-sf-backlog. More triggers: traceability.md, build-layer traceability, REQ-XXX and FG-XXX id mapping, artefact-to-requirement orphan report, coverage-gap report, check_rtm.py --manifest-dir, owning run-time agent column, design decision ref column, metadata API name in a traceability row.

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Discovery, download, and configuration hub for the entire aelf agent skill ecosystem. Use when the user wants to: (1) explore or list available aelf skills, (2) install/bootstrap aelf skills into Cursor, Claude Desktop, OpenClaw, Codex, or Claude Code, (3) route an aelf-related intent to the correct skill, (4) check health or audit installed skills, (5) onboard a new skill into the aelf ecosystem. Covers domains: Portkey CA wallet, Portkey EOA wallet, Awaken DEX, eForest NFT marketplace, AelfScan explorer, TomorrowDAO governance, aelf node interaction.

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Design an Azure AI gateway layer for centralized model routing, policy enforcement, and operational control. Use this skill when users ask about centralized AI traffic management, model governance, rate limiting, or gateway patterns.

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The LAW a council SEAT is bound by — deliberation protocol, pact obligations, governance, and decision-ledger recording — the discipline half of a seat. Trigger when: - Holding a seat on a bound council (architect, lead-maintainer, process-auditor, or a summoned guest). - Depositing an independent assessment, routing a decision, or recording assent or a finding. - Auditing whether the council honored the pact, the delegation table, or the barring lifecycle. - Prompt contains: /council, council seat, deliberation protocol, pact, delegation table, decision ledger, barring, merge-consent.

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governance config一式の用途と必須keyを確認したいとき、projectへの導入差分をread-onlyで把握したいときに使う。

governanceの登録・rubric合成を実行したいとき、再評価・rollback automationを安全に選択したいときに使う。

governance artifactのmigration候補とdry-run差分を確認したいとき、rollback条件を保った移行を実行したいときに使う。

governance secret helperの利用可否を確認したいとき、key名とbackendを値を露出せず監査したいときに使う。

governance出力adapterの利用可能性を確認したいとき、入出力契約と代替経路を安全に特定したいときに使う。

governance hookのevent・matcher・commandを監査したいとき、対象file ownershipと配線漏れを確認したいときに使う。

Use when performing cybersecurity operations - offensive or defensive - including threat detection and hunting, SOC operations, incident response, digital forensics and DFIR, malware analysis and reverse engineering, threat intelligence, cloud/container/network/application/API security, identity-access and zero-trust, OT/ICS and endpoint security, vulnerability and supply-chain management, DevSecOps, cryptography, AI security, compliance and governance, and red-team or penetration testing under signed rules of engagement; routes to one of 800+ technique playbooks mapped to MITRE ATT&CK, D3FEND, and NIST CSF.

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Reviews a proposal, business case, deck or plan in character as a Chief Data Officer archetype and returns a DRAFT review in the chat with a verdict, findings that cite the exact passage, data and AI governance risks, what would change the verdict and five interrogation questions. Use when the user asks to "run a CDO review", "pressure-test the data governance in this plan", "what would a CDO say about this", "check the metric definitions and data sources" or "prepare this for the data governance board". Do not use for security controls or third-party security risk, use ciso-reviewer instead; for contract, liability or regulatory terms, use general-counsel-reviewer. Drafts for human review; never approves, authorises or signs off.

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Deployless delivery-model audit. Use first when adapting any repository toward single-mainline development, automatic deployment from main, runtime release controls, production-trace-driven iteration, AI PR governance, or multi-agent delivery workflows.

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Operational guide for the NV oOS Model Foundry (Proposal 067) — the cluster fine-tuning flywheel. Phase 1 shipped: the Corpus Foundry (Pro addon, addons/pro/includes/model-foundry/) — consent-gated, deduplicated, PII-scrubbed corpus exporters (trajectory_v1, preference_v1, docs_v1) with deterministic holdout splits and R12 provenance manifests. Covers the governance contract, row schemas, output layout, filter seams, the registration pattern for foundry tool slices, how to add a new exporter, and the test/validation gates. Use when extending the Corpus Foundry, debugging corpus exports, wiring a new data source, or continuing Phases 2–6 (train-worker, registry/serving, eval gate, fleet sharing).

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Expert en data mesh (domain ownership, data products, self-serve, gouvernance fédérée)

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ISO/IEC 27001:2022 is the international standard for establishing, implementing, maintaining, and continually improving an Information Security Management System (ISMS). bu skill covers the complete

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。