Other skills

Analyze Rails apps and provide upgrade assessments

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Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.

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Complete toolkit for senior architect with modern tools and best practices.

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Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions.

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Run ADR conformance checks, explain failures, and identify required ADR/doc updates for the current change.

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Review a change for architectural drift, guardrail weakening, and ADR impact before shipping.

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Stage files, run pre-commit, fix failures, loop until clean

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<What this skill does>

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マルチテナント前提の設計差分から、テナント分離（データ/権限/リソース/障害影響）の抜けや越境リスクを検出

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運用で発見されたレビューパターン (findings / retrospective) を分析し、新 skill への昇格候補 / 既存 skill 更新候補 / 人間判断が必要な項目に分類する

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.river-review.{yaml,json} の context.budget / ranking / reviewMode 設定をモデル仕様とリポジトリ規模に合わせて調整するレビュー観点。

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Ensure requirement docs define scope, terminology, acceptance criteria, edge cases, and non-functional requirements.

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River Review の artifact / memory / log に対して、retention 設定 + hard guards + excludes から決定論的に KEEP/REMOVE を判定する GC skill

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複数の AI / 人間レビュー結果 (review-self / review-external / findings-pool) を統合し、実在性・重大度・対応優先度・merge 可否を検証する。

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Detect missing loading/error/empty state handling that could trap users in spinners or disabled states.

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Detects mass assignment via create/update($request->all()), unguarded models, and missing authorization on mutating controller actions in Laravel.

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Ensure architecture docs define bounded contexts, ownership, and a consistent ubiquitous language to prevent domain drift and coupling.

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Applies standard AI review policy guidelines for midstream (implementation) phase reviews.

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Ensure architecture updates document affected stakeholders, notification plan, and deprecation/retirement signals to keep knowledge aligned.

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Checks whether AI-assisted work defines review criteria, accessible context, explicit review loop, human judgment boundary, and feedback capture before delegating to an agent.

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Ensure ADRs capture context, decision, alternatives, tradeoffs, and follow-ups in a way that prevents future drift.

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Detects long-lived objects (caches, listeners, singletons) that capture an entire enclosing scope via closures/environment capture, keeping large arrays or buffers alive, and proposes copying only the needed fields.

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Minimal always-on sample skill to guarantee an end-to-end review experience.

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Detect i18n/locale keys that are removed from source but remain in locale files, or keys added to locale files without source usage.

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