geo-platform-optimizer
Platform-specific AI search optimization — audit and optimize for Google AI Overviews, ChatGPT, Perplexity, Gemini, and Bing Copilot individually
Platform-specific AI search optimization — audit and optimize for Google AI Overviews, ChatGPT, Perplexity, Gemini, and Bing Copilot individually
One-time setup that gathers design context for your project and saves it to your AI config file. Run once to establish persistent design guidelines.
Multi-agent pipeline orchestrator that plans and dispatches parallel development tasks to worktree agents. Reads project context, configures task directories with PRDs and jsonl context files, and launches isolated coding agents. Use when multiple independent features need parallel development, orchestrating worktree agents, or managing multi-agent coding pipelines.
Handle cascading data retrieval tool failures by falling back to embedded knowledge generation
Identify and classify agent failures occurring before execution starts
Identify and handle pre-execution agent failures occurring before any iterations or tool usage
Systematic document generation with unicode sanitization, engine fallback chain, and explicit error diagnosis
Document generation with direct pandoc/ReportLab execution (lightweight default) and optional shell_agent fallback for complex scenarios
Robust document generation with engine fallback chain, error diagnostics, and Python alternatives
Fallback workflow for multi-format document generation when shell_agent encounters errors
Robust PowerPoint generation with shell_agent primary approach and python-pptx fallback, including working directory verification and inline error debugging
Resilient PowerPoint generation with shell_agent primary path and python-pptx fallback
Delegate web search tasks to shell_agent when direct search_web tool fails, using its retry mechanism and multi-step capabilities for resilient data gathering
Implement fallback strategies when web-reading tools fail simultaneously
Identify and handle agent failures with 0 iterations as pre-execution system issues
Trigger ADO pipelines for a Copilot-created PR by posting /azp run comments. Use when the user asks to trigger CI pipelines for a specific PR.
Generates optimized prompts for any AI tool. Use when writing, fixing, improving, or adapting a prompt for LLM, Cursor, Midjourney, image AI, video AI, coding agents, or any other AI tool.
Guide for developing the OpenShell TUI — a ratatui-based terminal UI for the OpenShell platform. Covers architecture, navigation, data fetching, theming, UX conventions, and development workflow. Trigger keywords - term, TUI, terminal UI, ratatui, openshell-tui, tui development, tui feature, tui bug.
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.
You MUST use this for gathering contexts before any work. This is a Knowledge management for AI agents. Use `brv` to store and retrieve project patterns, decisions, and architectural rules in .brv/context-tree. Uses a configured LLM provider (default: ByteRover, no API key needed) for query and curate operations.
Set which voice pack (character voice) plays for the current chat session. Automatically enables session_override rotation mode if not already set. Use when user wants a specific character voice like GLaDOS, Peon, or Kerrigan for this conversation.
Add, update, or remove text/image/video models. Handles any provider.