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Claude skill that turns Claude into a Connecticut-specific divorce planner — nine operating modes from pre-flight intake to post-judgment modification, modeled on Untangle.us's feature surface and grounded in C.G.S. Title 46b, Practice Book Chapter 25, and the 2026-08-01 CCSG schedule. Covers eligibility triage (nonadversarial under § 46b-44a vs standard), financial affidavit (JD-FM-6), child support (JD-FM-220 / CCSG-1 / 1A), alimony (§ 46b-82 fourteen factors), parenting plan (with GAL/AMC escalation under JD-FM-224), settlement agreement (JD-FM-172, TCJA-aware), filing packet (marshal 12-day rule, $360 + $50 fees, JD-FM-75 waiver), and post-judgment motion practice. Hard UPL gate: refuses non-CT, domestic violence (refers CTCADV 1-888-774-2900), hidden assets, courtroom advocacy. Heppner-aware: AI prompts are not privileged. First family-law skill in the Lawvable registry.

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AI co-counsel for divorce and family-law attorneys — a jurisdiction-portable scaffold spanning the full matter lifecycle. Eight operating modes mirror how a matter actually moves: intake and onboarding, financial disclosure, children and support, property division and QDRO, discovery and document review, drafting, negotiation and mediation prep, and court prep — plus post-judgment modification and enforcement. The methodology is jurisdiction-agnostic: it forces real, verifiable research for every local form, formula, or rule rather than inventing one, handling common-law, community-property, civil-law, and MENA personal-status regimes as variables. Built around one non-negotiable: privilege. It drafts, analyzes, organizes, and pressure-tests. It is not the lawyer.

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Map evidence-based connections between a wellbeing initiative and specific academic learning outcomes. Use when justifying wellbeing programmes, integrating SEL, or linking pastoral and academic work.

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Design targeted interventions that strengthen belonging and inclusion for specific classroom dynamics. Use when students feel isolated, cliques form, or new students need integrating.

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Capture confidence ratings before and after a learning attempt to identify overconfidence and underconfidence patterns. Use when a student wants to understand how well they actually know something versus how well they think they know it.

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Before any explanation or answer, require the learner to produce a free-recall attempt and confidence rating. Use when a student wants help understanding or reviewing a topic — this skill ensures the AI works from what the learner already knows.

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Develop TPACK for integrating a specific technology or AI tool into subject teaching with pedagogical alignment. Use when adopting new ed-tech, reviewing AI tools, or planning technology integration.

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Script a teacher think-aloud demonstrating expert reasoning processes for a specific task. Use when modelling problem-solving, writing, reading comprehension, or analytical processes.

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WS-Discovery protocol scanner for discovering and enumerating ONVIF cameras and IoT devices on the network. Use when you need to discover ONVIF devices, cameras, or WS-Discovery enabled equipment on a network.

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Use when orchestrating Agent Teams for parallel development - team composition, task distribution, dependency management, and result aggregation. Triggers on /orchestrate, multi-agent coordination, parallel team work, task delegation to teammates.

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Consolidated expert library for professional Godot 4.7+ game and application development. Orchestrates 92 Domain Skills through architectural workflows, anti-pattern catalogs, performance budgets, and Server API patterns. Use when: (1) starting a new Godot project, (2) designing game or app architecture, (3) building entity/component systems, (4) debugging performance or physics issues, (5) choosing between 2D/3D approaches, (6) implementing multiplayer, (7) optimizing draw calls or script time, (8) porting between platforms, (9) migrating from 4.6 to 4.7. Primary entry point for ALL Godot development tasks. Keywords: Godot 4.7, AreaLight3D, HDR, Asset Store, godot-master.

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Use when auditing or recalibrating game balance: build a source-driven Monte Carlo balance lab (Rust + rayon) that extracts live game data, simulates human playstyles (AFK→pro), emits win-rate/economy verdicts with confidence intervals, and bruteforce-tunes parameters. Trigger on unfair levels, unreachable shops, farm exploits, interest-curve cliffs, post-content recalibration, or CI balance JSON diffs. Keywords: balance lab, Monte Carlo, win rate, difficulty curve, economy career, playstyle simulation, Resource extraction, GDScript parser, bruteforce tuning.

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Godot Expert Analyst: Anara. Visionary project scoring and certification for Godot 4.7+ architecture. Use when evaluating project health, modernity, scalability, dependency graphs, or generating Visionary Certificates. Keywords: analyst, Anara, scoring, certification, architecture audit, ResourceLoader.get_dependencies, typed Dictionary, folder-by-feature, Visionary Certificate, Godot 4.7.

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Expert patterns for migrating 2D games to 3D including node type conversions, camera systems (third-person, first-person, orbit), physics layer migration, sprite-to-model art pipeline, and control scheme adaptations. Use when porting 2D projects to 3D or adding 3D elements. Trigger keywords: CharacterBody2D to CharacterBody3D, Area2D to Area3D, Camera2D to Camera3D, Vector2 to Vector3, collision_layer migration, sprite to MeshInstance3D, 2D to 3D conversion.

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。

Consolidated expert library for professional Godot 4.7+ game and application development. Orchestrates 92 Domain Skills through architectural workflows, anti-pattern catalogs, performance budgets, and Server API patterns. Use when: (1) starting a new Godot project, (2) designing game or app architecture, (3) building entity/component systems, (4) debugging performance or physics issues, (5) choosing between 2D/3D approaches, (6) implementing multiplayer, (7) optimizing draw calls or script time, (8) porting between platforms, (9) migrating from 4.6 to 4.7. Primary entry point for ALL Godot development tasks. Keywords: Godot 4.7, AreaLight3D, HDR, Asset Store, godot-master.

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 auditing or recalibrating game balance: build a source-driven Monte Carlo balance lab (Rust + rayon) that extracts live game data, simulates human playstyles (AFK→pro), emits win-rate/economy verdicts with confidence intervals, and bruteforce-tunes parameters. Trigger on unfair levels, unreachable shops, farm exploits, interest-curve cliffs, post-content recalibration, or CI balance JSON diffs. Keywords: balance lab, Monte Carlo, win rate, difficulty curve, economy career, playstyle simulation, Resource extraction, GDScript parser, bruteforce tuning.

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 patterns for migrating 2D games to 3D including node type conversions, camera systems (third-person, first-person, orbit), physics layer migration, sprite-to-model art pipeline, and control scheme adaptations. Use when porting 2D projects to 3D or adding 3D elements. Trigger keywords: CharacterBody2D to CharacterBody3D, Area2D to Area3D, Camera2D to Camera3D, Vector2 to Vector3, collision_layer migration, sprite to MeshInstance3D, 2D to 3D conversion.

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。

Godot Expert Analyst: Anara. Visionary project scoring and certification for Godot 4.7+ architecture. Use when evaluating project health, modernity, scalability, dependency graphs, or generating Visionary Certificates. Keywords: analyst, Anara, scoring, certification, architecture audit, ResourceLoader.get_dependencies, typed Dictionary, folder-by-feature, Visionary Certificate, Godot 4.7.

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。

Manage, deploy, operate, and instrument applications with Temps. Use this skill whenever the user mentions Temps, `@temps-sdk/cli@0.1.37`, deploying or migrating an app to Temps, projects, environments, services, domains, backups, logs, monitoring, analytics, browser Performance Insights/Core Web Vitals, observability, error tracking, OpenTelemetry, tracing, session replay, or Temps Cloud. Also use it when preparing an application for production on Temps even if the user does not explicitly ask for the CLI. Route to focused references, proactively detect missing observability during create/link/deploy journeys, and use pinned `bunx` or `npx` CLI invocations with explicit target contexts.

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Swift concurrency patterns including Swift 6.2 approachable concurrency, structured concurrency, actors, continuations, and migration. Use when reviewing or building async code, fixing data race errors, or migrating to Swift 6.

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Migration guides for CoreData to SwiftData, UIKit to SwiftUI, ObservableObject to @Observable, XCTest to Swift Testing, Objective-C to Swift, and StoreKit 1 to StoreKit 2. Use when migrating between Apple framework generations.

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Master orchestrator that generates all implementation specs (PRD, Architecture, UX, Implementation, Test, Release) from product plan. Use when generating complete specification package.

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Generates smart App Store review prompt infrastructure with configurable conditions and platform detection. Use when user wants to add review prompts, request ratings, or implement StoreKit reviews.

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Privacy-preserving ad measurement with AdAttributionKit (SKAdNetwork's successor) — install and re-engagement attribution, conversion-value strategy under crowd anonymity, and end-to-end postback testing. Use when running paid acquisition beyond Apple Ads, measuring re-engagement campaigns, designing conversion values, or migrating from SKAdNetwork.

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。