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Analyze coverage, identify gaps, and generate missing tests toward the target threshold.

Scan project structure and generate token-lean architecture codemaps.

Sync documentation from source-of-truth files such as scripts, schemas, routes, and exports.

Fix Gradle build errors for Android and KMP projects

Answer a quick side question without interrupting or losing context from the current task. Resume work automatically after answering.

Review pull request test coverage quality and completeness, with emphasis on behavioral coverage and real bug prevention.

Accessibility Architect specializing in WCAG 2.2 compliance for Web and Native platforms. Use PROACTIVELY when designing UI components, establishing design systems, or auditing code for inclusive user experiences.

Software architecture specialist for system design, scalability, and technical decision-making. Use PROACTIVELY when planning new features, refactoring large systems, or making architectural decisions.

Build and TypeScript error resolution specialist. Use PROACTIVELY when build fails or type errors occur. Fixes build/type errors only with minimal diffs, no architectural edits. Focuses on getting the build green quickly.

Personal communication chief of staff that triages email, Slack, LINE, and Messenger. Classifies messages into 4 tiers (skip/info_only/meeting_info/action_required), generates draft replies, and enforces post-send follow-through via hooks. Use when managing multi-channel communication workflows.

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA standards. Use this skill to generate semantic ARIA for Web and accessibility traits for Web and Native platforms (iOS/Android).

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature.

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports.

28 hooks across 7 events