automate-whatsapp
Supports creating and debugging Kapso WhatsApp automation. Covers workflows, triggers, functions, and their executions.
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Find your next superpower If you are an agent, refer to our llms.txt for full access."..." for exact phrases · Try typography, debugging or spreadsheetSupports creating and debugging Kapso WhatsApp automation. Covers workflows, triggers, functions, and their executions.
Automates radare2/rizin analysis through r2pipe to script function enumeration, string and import extraction, and cross-reference queries across samples programmatically. Activates for requests to automate radare2 with r2pipe, script rizin analysis, or batch-extract functions and xrefs from binaries.
Controls tmux windows through MCP tools to launch background processes, monitor builds or servers, and send debugger commands. Supports interactive prompts, commands requiring sudo, and orchestration across multiple terminal sessions.
Uses the execute_metadata_action MCP tool to generate Screen, Autolaunched, Record-Triggered, and Scheduled Flows. Handles requests such as updating fields after record creation or sending email when conditions are met.
Transforms customer SOPs from documents, spreadsheets, text, or screenshots into configuration arrays. Defines OutboundMessages, RemoteSiteSettings, and ScheduledApex entries with fields, activation settings, and execution order.
Resolves and updates target records through Salesforce APIs using a post-copy JSON configuration. Schedules Apex entries through anonymous Apex and verifies them through CronTrigger queries, with support for dry runs and previews.
Covers design patterns for autonomous coding agents and assistants. Addresses tool integration, tool API design, permission systems, browser automation, and workflows that include human oversight.
Covers autonomous systems that decompose goals, plan actions, execute tools, and self-correct. Explores ReAct and Plan-Execute loops, reflection patterns, and production reliability, emphasizing how errors compound across multiple decisions.
Covers autonomous AI systems that decompose goals, plan actions, execute tools, and self-correct. Emphasizes reliability and the compounding risk of failure across successive decisions.
Orchestrates a ratified milestone across multiple slices with bounded assignments, senior slice reviews, integrated validation, and a final senior verdict. Requires explicit outcomes, authority limits, acceptance evidence, and escalation conditions.
Handles end-to-end builds for users who expect a finished result without reviewing specifications, tickets, or code. Supports requested modes and levels of depth, from fully automatic execution to interviews, manual involvement, and strict adherence to a brief.
Auto-review pipeline — reads the full CEO, design, eng, and DX review skills from disk and runs them sequentially with auto-decisions using 6 decision principles. (gstack)
A growing collection of real, public skills. Descriptions and instructions indexed 24 Sept 2026.
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