productivity▌

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Ask an AI assistant what files it needs before answering your question. \n \n Prompts the assistant to identify required and optional files for context before attempting to answer \n Structures output into four categories: must-see files, helpful files, already-seen files, and remaining uncertainties \n Helps developers avoid incomplete answers by ensuring the assistant has examined relevant code upfront \n Reduces back-and-forth by clarifying dependencies and gaps in context before the actual q

Structured framework for writing blameless postmortems that drive organizational learning from incidents. \n \n Provides templates for standard postmortems, 5 Whys analysis, and quick incident reviews, with sections for timelines, root cause analysis, detection gaps, and action items \n Emphasizes blameless culture by shifting focus from individual blame to systemic failures and conditions that enabled incidents \n Includes facilitation guide for postmortem meetings, anti-patterns to avoid, and

Identify and review overdue Google Tasks requiring immediate attention. \n \n Requires the gws-tasks skill to query Google Tasks API \n Three-step workflow: list all task lists, filter incomplete tasks by list ID, and review due dates for prioritization \n Returns task data in table format for easy scanning of overdue items \n

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Automatically share Google Drive files with all attendees of a Calendar event. \n \n Requires gws-calendar and gws-drive skills as dependencies \n Retrieves event attendee list from Google Calendar, then grants each attendee reader access to specified Drive files \n Includes verification step to confirm sharing permissions were applied successfully \n

Analyze codebases and map task-relevant files before implementing changes. \n \n Automatically searches for related files, dependencies, tests, and similar code patterns to establish full context \n Generates structured markdown output with files to modify, dependency relationships, test coverage, and reference patterns \n Includes risk assessment checklist for breaking changes, migrations, and configuration updates \n Designed as a pre-implementation step to prevent missed dependencies and unin

Unified AI SDK for Dart enabling code generation, structured outputs, tools, flows, and agents. \n \n Provides core APIs for generation, tool definition, flow orchestration, embeddings, and streaming with a single interface \n Includes 8+ plugins for LLM providers (Google Gemini, Anthropic Claude, OpenAI GPT), Firebase AI, Model Context Protocol, Chrome browser integration, and HTTP server hosting via Shelf \n Built-in CLI with local development UI for flow execution, tracing, model experimentat

Prioritized keyword research with intent mapping, difficulty scoring, and cluster seeding for SEO strategy. \n \n Builds a three-tier keyword universe (head, body, long-tail) with monthly volume, difficulty scores (0-100), and intent classification across informational, commercial, transactional, and navigational categories \n Includes cannibalization screening to prevent targeting keywords your site already ranks for, plus low-hanging fruit detection for quick wins in positions 11-20 \n Scores

Web search optimized for AI agents with real-time data retrieval. \n \n Single command interface ( scripts/search ) for querying the web with results tailored for agent consumption \n Supports JSON output formatting for structured data integration into agent workflows \n Requires Tavily API key for authentication; free API key available from tavily.com \n