task▌

Lightweight task tracking via a shared TASKS.md file with optional visual dashboard. \n \n Stores tasks in a simple markdown file with four sections: Active, Waiting On, Someday, and Done \n Includes an optional HTML dashboard for drag-and-drop task reordering and auto-saving changes \n Supports task extraction from meetings and conversations, with user confirmation before adding \n Uses checkbox syntax and strikethrough formatting to mark completion, with context fields for due dates, assignees

Execute implementation tasks directly from design documents. Tasks are managed as markdown checkboxes - no separate session files needed.

Annotate Airflow tasks with data lineage using inlets and outlets. \n \n Supports OpenLineage Dataset objects, Airflow Assets, and Airflow Datasets for defining inputs and outputs across databases, data warehouses, and cloud storage \n Use as a fallback when operators lack built-in OpenLineage extractors; follows a four-tier precedence system where custom extractors and OpenLineage methods take priority \n Includes dataset naming helpers for Snowflake, BigQuery, S3, and PostgreSQL to ensure cons

Initialize a Google Tasks list and populate it with multiple tasks via command sequence. \n \n Requires the gws-tasks skill to execute task list and task management operations \n Provides step-by-step commands to create a new task list, add tasks with optional notes and due dates, and display results in table format \n Demonstrates task insertion with structured JSON payloads including title, notes, and ISO 8601 due date formatting \n

Convert Gmail messages into Google Tasks entries with subject-to-title mapping. \n \n Extracts email subject as task title and message snippet as task notes \n Supports custom task list selection via --tasklist flag; defaults to @default list \n Requires Gmail message ID as input; recommends user confirmation before task creation \n Depends on gws-shared for authentication and global workflow flags \n

Estimate software development tasks using story points, planning poker, and t-shirt sizing. \n \n Provides Fibonacci-based story point scales (1–21+) with time and complexity guidelines for each level \n Includes planning poker process for team consensus estimation with discussion and re-voting workflows \n Offers t-shirt sizing (XS–XL) for quick backlog grooming and rough roadmap planning \n Adjusts estimates for risk and uncertainty using configurable buffers, with examples for medium and high

Write comprehensive task breakdowns assuming the expert who is going to implement the specs has zero context for our project and questionable taste. Document everything they need to know: which existing files to check, which files to touch for each task and what changes to make to them. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD.

Tools:

The monitor_task.py script provides automatic updates:

Keep long-running work recoverable, stateful, and honest.