aka. Agent Skills
Discover skills for AI coding agents. Works with Claude Code, OpenAI Codex, Gemini CLI, Cursor, and more.
Business rules elicitation and analysis techniques. Covers rule types (constraints, derivations, inferences), decision tables, rule templates, and policy documentation. Use when identifying business policies, constraints, calculations, and decision logic during requirements elicitation.
Manage AI CLI tools (Claude Code, Gemini CLI, Codex CLI). Use when user asks about AI tool versions, updates, installation, or wants to update their AI CLI tools. Detects installed tools, checks versions, and retrieves update instructions from authoritative sources using delegation-first pattern.
Guide for creating Gemini CLI policy engine TOML rules. Covers rule syntax, priority tiers, conditions, and MCP wildcards. Use when restricting Gemini tools, creating security policies, controlling MCP server permissions, or setting up approval workflows.
Expert guide for Model Context Protocol (MCP) integration with Gemini CLI. Covers MCP server configuration (HTTP, SSE, Stdio), connection management, and tool permissions. Use when adding MCP servers to Gemini, configuring transports, troubleshooting MCP connections, or managing tool permissions. Delegates to gemini-cli-docs.
Retrieval-Augmented Generation (RAG) system design patterns, chunking strategies, embedding models, retrieval techniques, and context assembly. Use when designing RAG pipelines, improving retrieval quality, or building knowledge-grounded LLM applications.
Track and measure agentic coding KPIs for ZTE progression. Use when measuring workflow effectiveness, tracking Size/Attempts/Streak/Presence metrics, or assessing readiness for autonomous operation.
Parse Gemini CLI headless output (JSON and stream-JSON formats). Covers response extraction, stats interpretation, error handling, and tool call analysis. Use when processing Gemini CLI programmatic output.
Expert guide for building and managing Gemini CLI Extensions. Covers extension anatomy, GEMINI.md context, commands, MCP integration, and publishing. Use when creating Gemini extensions, linking local extensions, packaging MCP servers, or installing extensions from GitHub. Delegates to gemini-cli-docs.
Strategic patterns for Claude-to-Gemini delegation. Covers decision criteria, execution patterns, result parsing, and error handling. Use when determining if a task should be delegated to Gemini CLI.
Scans code for security vulnerabilities, identifies CVE patterns, and provides severity ratings with remediation guidance. Use when scanning for security issues, code vulnerabilities, or OWASP top 10 problems.
Facilitates context sharing and strategic delegation between Claude Code and Gemini CLI. Syncs CLAUDE.md to GEMINI.md and provides agent selection guidance. Use when onboarding Gemini to a project, syncing instructions between agents, or deciding whether to use Claude or Gemini for a specific task.
Set up conditional documentation loading to prevent context pollution. Use when organizing project docs, implementing progressive disclosure, or reducing CLAUDE.md token consumption with on-demand loading.
Create meta prompts, meta agents, and meta skills that build other agentic components. Use when scaling agentic layer development, creating generators/templates, or implementing "build the system that builds the system" patterns.
Map value chains from user needs to underlying components
Build observability interfaces for multi-agent systems. Use when monitoring multi-agent execution, tracking agent metrics, implementing logging for parallel agents, or debugging agent workflows.
Expert guide for configuring Google Gemini CLI. Covers global vs project settings.json, Trusted Folders, Policy Engine, and environment variables. Use when configuring Gemini settings, managing trusted folders, setting up security policies, or troubleshooting configuration precedence. Delegates to gemini-cli-docs for official references.
Expert guide for creating custom Gemini CLI commands. Covers slash command definitions (.toml), argument parsing, and shell execution. Use when creating custom Gemini commands, defining TOML command files, adding command arguments, or building extension-based commands. Delegates to gemini-cli-docs.
Add console output and logging to make errors visible to agents. Standard out is a critical leverage point - without it, agents cannot see errors or understand application state. Use when agents fail silently, when debugging agentic workflows, or when setting up a new codebase for agentic coding.
AI-led stakeholder interviews using LLMREI research-backed patterns. Conducts structured interviews to elicit requirements through context-adaptive questioning, active listening, and systematic requirement extraction.
Analyze requirements for completeness, missing areas, and gaps. Uses domain checklists, NFR categories, and INVEST criteria to identify what's missing from elicited requirements.