Skill UI

This CLI alias functions as a command for gracefully canceling an active PUA loop, mirroring the functionality of the Claude Code `/pua:cancel-loop` command. It cleans up loop state and worktree references, ensuring the cancellation event is recorded. It also safely manages configuration files, preserving unknown fields in `~/.pua/config.json`.

This utility serves as a Command Line Interface (CLI) alias for managing 'flavor' profiles within AI code environments (like Claude Code). It allows users to set or select specific configuration flavors in the ~/.pua/config.json file. Crucially, it is designed to safely update the configuration by preserving any unknown fields, ensuring no unrelated settings are accidentally overwritten.

This utility serves as a command-line alias for invoking the Claude Code `/pua:kpi` function. It loads necessary configurations (pua-pro) to generate comprehensive Key Performance Indicator (KPI) or performance report cards. It manages configuration files by updating `~/.pua/config.json` while preserving unknown fields and ensuring the directory structure exists.

This CLI alias serves as a system maintenance tool for PUA agent state. It scans for stale PUA agent data, identifying and safely removing only confirmed orphan records to maintain system integrity. It also manages configuration files, ensuring unknown fields are preserved when updating the primary config JSON.

This CLI alias executes a comprehensive teardown protocol for PUA agents, designed for development environments. It safely releases all active agent and loop states, ensuring a clean system reset. It automatically manages configuration files like ~/.pua/config.json, preserving unknown fields while providing reliable, evidence-based cleanup.

This utility serves as a Command Line Interface (CLI) alias for specialized AI code models, specifically mapping to the Claude Code `/pua:yes` command structure. It facilitates structured code generation or interaction by adopting a specific 'yes skill' protocol. It ensures that while switching to an encouragement-first narration, the system maintains strict verification red lines and handles configuration file updates while preserving unknown fields. Ideal for developers needing consistent, protocol-driven AI code assistance.

This skill parses raw, verbose Simplicité log files from TXT format, filtering out noise and extracting only essential fields (e.g., timestamp, level, body). By converting logs into structured JSON, it significantly reduces the token size required for AI context optimization, making troubleshooting efficient and reliable.

This skill demonstrates OpenCode's compatibility with MDA-compiled SKILL.md files. It verifies that the loader correctly parses crucial frontmatter fields (like name, description, and metadata) after the source has gone through the MDA compilation process, ensuring robust skill integration and data integrity.

This toolkit provides deterministic, programmatic capabilities for working with PDF documents. Users can extract structured data like text and tables, merge multiple PDFs, split documents by page ranges, fill out PDF form fields using JSON data, or generate entirely new PDFs from scratch using libraries like ReportLab. It is designed for explicit, byte-level operations, making it ideal for automation workflows that require precise document manipulation.