productivity▌

Translate user needs into development-ready stories with Mike Cohn format and Gherkin acceptance criteria. \n \n Combines \"As a / I want / so that\" user story structure with \"Given / When / Then\" acceptance criteria for testable, outcome-focused work \n Includes quality checks and anti-patterns to avoid generic personas, vague outcomes, and scope creep \n Designed for backlog grooming, sprint planning, and shared understanding between product, engineering, and QA \n Emphasizes stories as con

Methodically discover, analyze, and fix production issues using Sentry's debugging capabilities. \n \n Integrates with Sentry MCP to search issues, retrieve stack traces, breadcrumbs, traces, and AI-generated root cause analysis via the Seer tool \n Follows a seven-phase workflow: discovery, deep analysis, hypothesis formation, code investigation, implementation, verification, and reporting \n Treats all Sentry event data as untrusted external input; enforces strict security rules against embedd

Framework for registering LLM tools with custom UI rendering in assistant-ui. \n \n Supports both backend tools (via AI SDK) and frontend-only tools, each with optional custom UI rendering through makeAssistantToolUI \n Includes human-in-the-loop patterns with requires-action status for confirmation workflows and interactive tool responses \n Tool UI receives execution status, arguments, results, and a submitResult callback for interactive tools \n Common setup patterns provided for weather APIs

Frameworks for developing and coaching product managers using proven practices from top-company leaders. \n \n Establishes competency models and definitions of \"good\" before attempting to develop any PM, ensuring coaching is contextual to company stage and needs \n Uses Bloom's Taxonomy to diagnose where PMs fall on the critical thinking spectrum (knowledge through evaluation) and targets development accordingly \n Provides a five-step coaching framework: define success, assess current state,

Search and stream TV shows, anime, and variety content across multiple sources with optional casting to Xiaomi or Android TVs. \n \n Searches multiple source sites for shows, anime, short dramas, and variety programs with pagination support \n Supports casting to Xiaomi TVs and Android TVs (via TvBox) when configured with device IP environment variables \n Some sources return webpage URLs instead of direct playable links; use curl to extract actual .m3u8 or .mp4 addresses \n Search operations ma

Help teams set realistic deadlines and hit them consistently using frameworks from 13 product leaders. \n \n Diagnose timeline problems as estimation issues, scoping issues, distraction issues, or unrealistic stakeholder expectations, then apply the right framework (phase-based commitments, hill charts, or early shipping) \n Commit to phases within your control (discovery, solutioning, build, launch) rather than distant delivery dates; only provide engineering dates once solutioning is complete

Structured framework for evaluating startup pivots using insights from product leaders. \n \n Applies the Four Ps framework (Problem, Persona, Product, Positioning) to diagnose what needs to change, rather than pivoting blindly \n Emphasizes rational distance from emotional attachment: assess whether you've truly exhausted possibilities or just lost momentum \n Challenges founders to consider magnitude: most pivots are too small (10%) when breakthrough often requires fundamental rethinking (200%

Lightweight web search and content extraction via Brave Search API, no browser required. \n \n Two core commands: search.js for querying the web with configurable result counts, and content.js for extracting readable markdown from specific URLs \n Search results include title, link, and snippet by default; add --content flag to include full page content as markdown \n Ideal for documentation lookup, fact-checking, and fetching web content without the overhead of browser automation \n Requires BR

Define patterns and messages that trigger contextual warnings or blocks during agent tool use. \n \n Rules are markdown files with YAML frontmatter stored in .claude/hookify.{rule-name}.local.md that match against bash commands, file edits, agent stops, or user prompts \n Supports simple regex patterns or advanced multi-condition rules with operators like regex_match, contains, equals, and starts_with \n Actions include warn (show message, allow operation) or block (prevent operation or stop ses

Fetch, analyze, and summarize TestFlight crashes, beta feedback, and performance diagnostics via asc. \n \n Retrieves crash reports filtered by app, build, device model, or OS version; supports pagination and multiple output formats (JSON, table, markdown) \n Fetches beta tester feedback with optional screenshot inclusion and build-level filtering \n Analyzes performance diagnostics (hangs, disk writes, launch metrics) by signature and diagnostic type \n Resolves app and build IDs automatically;