collaboration tools向けのClaudeスキルを発見してください。30個のスキルを閲覧し、AIワークフローに最適な機能を見つけましょう。
Synchronizes multi-agent workflows by blocking execution until specific messages or acknowledgments arrive on specified topics.
Retrieves and displays critical details about the current Hive session, including unique session IDs and messaging inbox topics for AI agent coordination.
Conducts deep, investigative interviews to uncover non-obvious constraints and refine technical plans before generating comprehensive specifications.
Automates the developer onboarding journey through personalized plans, project management integrations, and milestone tracking.
Automates the integration between Linear project management and Git development workflows for streamlined issue tracking.
Automates the assignment of commits to issues and ensures project tracking accuracy at the end of a work session.
Analyzes feature requirements, technical dependencies, and security risks directly from GitHub issues to streamline implementation planning.
Generates standardized, comprehensive pull request descriptions with clear summaries, technical implementation details, and testing strategies.
Manages inter-agent communications and session handoffs within the Hive ecosystem.
Reviews LangGraph workflows for state management bugs, anti-patterns, and structural integrity issues.
Optimizes code review accuracy by analyzing feedback logs to identify patterns, reduce false positives, and refine automated review rules.
Processes external code review feedback using a verification-first methodology to ensure technical accuracy before implementation.
Audits Deep Agents implementations for configuration errors, architectural anti-patterns, and performance bottlenecks.
Retrieves and filters review comments from GitHub pull requests to streamline code feedback management.
Enables Claude to send interactive questions and receive user responses via Slack for remote task management.
Analyzes React Router v6.4+ implementations to ensure best practices for data loading, mutations, and error handling.
Automates comprehensive pull request reviews using a multi-agent system to analyze security, performance, architecture, and code quality.
Monitors project completion rates and identifies development blockers using GitHub issue data to ensure timely software delivery.
Conducts structured code reviews of Pull Requests using comprehensive checklists for quality, testing, and project-specific standards.
Posts structured progress reports, implementation notes, and technical findings directly to GitHub issues using the GitHub CLI.
Automates the posting of structured implementation plans, progress updates, and completion summaries directly to GitHub issues.
Generates scannable, outcome-focused progress reports and stakeholder communications with a professional yet warm tone.
Streamlines the code review process by drafting reviewer-centric PR descriptions, sizing work appropriately, and automating GitHub CLI submissions.
Provides an autonomous peer engineer subagent to review implementation plans, audit code, and brainstorm technical solutions.
Performs automated code reviews using the Radical Candor framework to provide actionable, tone-aware feedback based on project standards.
Conducts comprehensive Python code reviews to ensure type safety, PEP8 compliance, and efficient asynchronous patterns.
Provides legacy support for regenerating GitHub issues from plan files, now deprecated in favor of direct GitHub integration.
Reduces false positives in code reviews by enforcing a mandatory multi-step verification process before reporting findings.
Addresses GitHub Pull Request review comments by implementing requested code changes and providing automated replies to reviewers.
Generates context-aware code review checklists tailored to specific file types and programming languages including Mojo and Python.
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