mguinada
@mguinada
Public Skills
phoenix-observability
by mguinada
"Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, monitoring production AI systems, or setting up observability infrastructure for agentic systems. PROACTIVE ACTIVATION: Auto-invoke when implementing observability/tracing for LLM agents, setting up evaluation pipelines, or configuring OpenTelemetry instrumentation. DETECTION: Check for arize-phoenix imports, OpenTelemetry setup, or observability-related code. USE CASES: Debugging LLM apps, running evaluations, monitoring production systems, setting up tracing infrastructure, instrumenting agent frameworks, tracing custom agents with decorators (@tracer.agent, @tracer.chain, @tracer.tool)."
tdd
by mguinada
"Guide Test-Driven Development workflow (Red-Green-Refactor) for new features, bug fixes, and refactoring. Identifies test improvement opportunities and applies pytest best practices. Use when writing tests, implementing features, or following TDD methodology. PROACTIVE ACTIVATION: Auto-invoke when implementing features or fixing bugs in projects with test infrastructure (pytest files, tests/ directory). DETECTION: Check for tests/ directory, pytest.ini, pyproject.toml with pytest config, or test files. USE CASES: Writing production code, fixing bugs, adding features, legacy code characterization."
refactor
by mguinada
"TDD-based code simplification that preserves behavior through tests. Use Red-Green-Refactor cycles to simplify code one test-verified change at a time. DISTINCT FROM: General code review or AI rewriting—this skill requires existing tests and only proceeds when tests confirm behavior is preserved. PROACTIVE: Auto-invoke when test-covered code has complexity (functions >50 lines, high cyclomatic complexity, duplication) and user wants to simplify it safely. Trigger phrases: 'clean up code', 'make code simpler', 'reduce complexity', 'refactoring help'. NOT FOR: Adding features or fixing bugs—use /tdd skill instead."
create-pr
by mguinada
"Creates GitHub pull requests with properly formatted titles. Use when creating PRs, submitting changes for review, or when the user says /pr or asks to create a pull request. Analyzes changes on the current branch and uses the pull request template from .github folder. PROACTIVE ACTIVATION: Auto-invoke when commits exist on feature branch and user mentions PR, review, or push. DETECTION: Check for unpushed commits, feature branch (not main/master), user asks to share/review changes. USE CASES: Code is ready for review, after completing feature work, user wants to share changes."
git-commit
by mguinada
"Generate concise, descriptive git commit messages following best practices. Use when creating git commits from staged changes, crafting commit messages, or reviewing commit message quality. Use when the user says /commit or asks to create a git commit. PROACTIVE ACTIVATION: Auto-invoke when staged changes detected or user asks to commit/save work. DETECTION: Run git status - if staged changes exist, offer to commit. User says \"commit\", \"save\", \"done with feature\". USE CASES: Staged changes detected, work completed, user wants to save progress."
ai-engineering
by mguinada
"Build AI agents and agentic workflows. Use when designing/building/debugging agentic systems: choosing workflows vs agents, implementing prompt patterns (chaining/routing/parallelization/orchestrator-workers/evaluator-optimizer), building autonomous agents with tools, designing ACI/tool specs, or troubleshooting/optimizing implementations. PROACTIVE ACTIVATION: Auto-invoke when building agentic applications, designing workflows vs agents, or implementing agent patterns. DETECTION: Check for agent code (MCP servers, tool defs, .mcp.json configs), or user mentions of \"agent\", \"workflow\", \"agentic\", \"autonomous\". USE CASES: Designing agentic systems, choosing workflows vs agents, implementing prompt patterns, building agents with tools, designing ACI/tool specs, troubleshooting/optimizing agents."
copilot-sdk
by mguinada
"Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent. PROACTIVE ACTIVATION: Auto-invoke when building agentic applications or integrating Copilot SDK. DETECTION: Check for @github/copilot-sdk imports, copilot dependencies in package.json/pyproject.toml/go.mod. USE CASES: Embedding agents in apps, creating custom tools, implementing streaming, managing sessions, connecting to MCP servers."
prompt-engineering
by mguinada
"Creates system prompts, writes tool descriptions, and structures agent instructions for agentic systems. Use when the user asks to create, generate, or design prompts for AI agents, especially for tool-using agents, planning agents, or autonomous systems. PROACTIVE ACTIVATION: Auto-invoke when designing prompts for agents, tools, or agentic workflows in AI projects. DETECTION: Check for agent/tool-related code, prompt files, or user mentions of \"prompt\", \"agent\", \"LLM\". USE CASES: Designing system prompts, tool descriptions, agent instructions, prompt optimization, reducing hallucinations."