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Design relational database schemas (and choose when to go NoSQL) that stay maintainable and fast. Use this skill whenever the user mentions tables, DDL, entities and relationships, normalization (1NF/2NF/3NF), primary and foreign keys, UUID vs bigint IDs, indexes (B-tree, composite, covering, partial), EXPLAIN, constraints (CHECK, UNIQUE, exclusion), transactions and isolation levels, migrations (Alembic, Prisma, Flyway, expand-contract, backfilling), or SQL vs NoSQL (MongoDB, DynamoDB, Cassandra, graph databases). Also trigger for "design the database", "model this domain", "which database should I use", or writing ORM models and migration files for PostgreSQL, MySQL, SQLite, or SQL Server.

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Use when the user asks for a multi-agent .NET code review - five parallel reviewers (correctness, performance, security/observability, data/messaging/integration, generalist) plus an adversarial maintainer that refutes weak findings. Requires the review agent roles registered by scripts/install-codex.sh. Keywords: dotnet review pipeline, multi-agent review, parallel reviewers, maintainer pushback, review this branch, cynical review.

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Validate agent output against declared domain rules and ground truth before trusting it downstream. Trigger after any agent produces output that will be used in a decision, stored persistently, or passed to another agent.

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Framework de dados para construir aplicações LLM com RAG. Especializado em ingestão de documentos (300+ conectores), indexação e consultas. Inclui índices vetoriais, mecanismos de consulta, agentes e suporte multimodal. Use para perguntas sobre documentos, chatbots, recuperação de conhecimento ou construção de pipelines RAG. Ideal para aplicações LLM centradas em dados.

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[DDD Quality] Use when you need to review domain entities and value objects for DDD design quality.

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Maintains repo-local action contracts and harness repositories where product CLI and MCP adapters stay thin over core libraries. Use when adopting or improving steward.yaml actions, capability-level adoption evidence, cold-start proof loops, probes, benchmarks, CLI/MCP/core parity, adapter refactors, packages/core boundaries, or sibling harness layout; use repo-quality-system-lifecycle first for general app/library/tool stewardship baselines.

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Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a CONTEXT.md, or recording or editing an ADR.

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Structured Domain Modeling Architecture (SDMA) principles. Trigger when: - Designing domain models, building ologs (ontological graphs), verifying protocol equivalence, selecting schemas, or measuring architectural entropy. - Modeling structures using Category Theory, Coalgebra, or Information Theory. - Prompt contains keywords: sdma, olog, Category Theory, Coalgebra, Information Theory, entropy, schema, pullback, functor, monad.

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Create or refactor business calculations and rules spanning multiple domain objects when no single entity or value object naturally owns the behavior. Use when assessing a growing service class.

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スキルを作成・更新・プロンプト改善するためのメタスキル。 **最初のアクションは必ず AskUserQuestion**（インタビュー深度確認）。 **collaborative**モードでユーザーと対話しながら共創し、抽象的なアイデアから具体的な実装まで柔軟に対応する。 **orchestrate**モードでタスクの実行エンジン（Claude Code / Codex / 連携）を選択。 Anchors（主要3件・全7件は references/anchors.md 参照）: • Continuous Delivery (Jez Humble) / 適用: 自動化パイプライン / 目的: 決定論的実行 • The Lean Startup (Eric Ries) / 適用: Build-Measure-Learn / 目的: 反復改善 • Domain-Driven Design (Eric Evans) / 適用: 戦略的設計・ユビキタス言語・Bounded Context / 目的: ドメイン構造の明確化 Trigger: 新規スキルの作成、既存スキルの更新、プロンプト改善を行う場合に使用。 スキル作成, スキル更新, プロンプト改善, skill creation, skill update, improve prompt, Codexに任せて, assign codex, 実行モード選択, IPC Bridge統一, safeInvoke/safeOn, Preload API標準化, contextBridge, Electron IPC pattern

Lightweight multi-agent research orchestration using one coordinator, three domain leads, and three lightweight research agents. Use for medium-size research, market scans, competitor comparisons, prior-art style exploration, report planning, and any task that benefits from parallel domain decomposition without running a full high-cost research lab.

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Use when frontend, backend, mobile, data, DevOps, or security work needs domain routing and at most four focused references.

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Find and buy a domain for the current Convex app through Convex, then bind it (labs; spend action).

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Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.

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Turn any domain folder of skills into a bounded agentic loop: compile a goal into a verifiable task plan, execute tasks with the domain's own tools, verify every task with machine-run checks, retry with caps, escalate to a human when budgets exhaust.

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Queries Certificate Transparency logs via crt.sh and pycrtsh to detect phishing domains, unauthorized certificate issuance, and shadow IT. Monitors newly issued certificates for typosquatting and brand impersonation using Levenshtein distance. Use for proactive phishing domain detection and certificate monitoring.

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Analyzes DNS query logs to detect data exfiltration via DNS tunneling, DGA domain communication, and covert C2 channels using entropy analysis, query volume anomalies, and subdomain length detection in SIEM platforms. Use when SOC teams need to identify DNS-based threats that bypass traditional network security controls.

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Monitor Certificate Transparency logs using crt.sh and Certstream to detect phishing domains, lookalike certificates, and unauthorized certificate issuance targeting your organization.

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Run Tamanu pre-release verification checks: verify that hotfixes on the current release branch are merged forward to main, and that hotfixes from prior release branches are included in the current release. Use when the user wants to run "pre-release checks", verify hotfix integrity before cutting or shipping a Tamanu release, confirm a release/X.YY branch is safe to release, or check that no hotfix has been orphaned (left on neither main nor the current release). Handles Tamanu's train-release model (release/X.YY branches vs vX.YY.Z patch tags) and the cherry-pick model where the same logical fix has different SHAs on different branches. Purely git-based — no live database or Canopy access needed. Not for deciding which tests to run (see scope-tamanu-release-tests).

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Build and sharpen a project's domain model. Use only when actively changing glossary or ubiquitous-language terms, or recording a durable architectural decision; merely reading a glossary is not a trigger.

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显式授权一个已经由 Codex Flight Control 封存、用户可见且 hash 精确匹配的本地维护计划。仅当用户原样输入 `$flight-maintain` 并依次提供 plan_id 与 plan_hash 时使用；不能用自然语言同意、模型判断或 UI 点击替代。

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Work through which package to add for a capability, and what each option costs — maintenance, licence, bundle weight, transitive risk, and whether the platform already does it. Use when someone needs a library for a job and has not picked one yet, when weighing two candidates, or when a package looks convenient but unmaintained.

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METAINFORMANT rules for directory src/metainformant/protein/domains. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.

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METAINFORMANT rules for directory scripts/maintenance. Use when editing, adding tests, or reviewing code under this path. Read the linked AGENTS.md first; use uv only, write outputs to output/, real implementations.

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。