Agent Skills Directory

Design LLM-as-judge rubrics, direct scores and pairwise comparisons. Use for judge models, evals, position bias and calibration against human labels.

Advogado criminalista especializado em Maria da Penha, violencia domestica, feminicidio, direito penal brasileiro, medidas protetivas, inquerito policial e acao penal.

Advogado especialista em todas as areas do Direito brasileiro: familia, criminal, trabalhista, tributario, consumidor, imobiliario, empresarial, civil e constitucional.

Autonomous DevSecOps & FinOps Guardrails. Guide to reviewing Linux kernel patches, Terraform cost changes and Kubernetes policy with a separately reviewed upstream tool and configured model.

Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.

Evaluate agent behavior with versioned cases and explicit verifiers. Use when comparing agent or prompt changes, reproducing failures, or running agent regression tests.

Use when summarizing agent evaluations where autonomous, assisted, failed, timed-out, or invalid outcomes must remain distinct and comparable.

Build persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.

Use when an agent workflow needs deterministic recovery evidence for sandbox, MCP/tool, worker, checkpoint, memory, or orchestration failures.

Manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) in an explicitly authorized workspace.

A hybrid memory system that provides persistent, searchable knowledge management for AI agents.

Rules for when an agent should recall from long-term memory before acting and when it should save decisions, corrections and failures afterwards. Works with any memory backend.

A hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).

Design tenant-scoped memory, retrieval and retention for agents. Use when planning RAG, conversation history, vector stores or remembering across sessions.

Instrument AI agents with tracing, token metrics, latency, and cost visibility. Use for reliability and debugging.

Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.

Meta-skill que orquestra todos os agentes do ecossistema. Scan automatico de skills, match por capacidades, coordenacao de workflows multi-skill e registry management.

Create, edit, validate, and run Agent QA tests, suites, and hooks through MCP or CLI while preserving canonical IDs and schema contracts.

Debug, patch, and verify failed Agent QA runs from MCP evidence, artifacts, logs, and local code without hiding product or infrastructure defects.

Triage failed Agent QA runs with MCP evidence, artifacts, logs, fixed failure categories, confidence, and actionable next steps.

Find animation and video references on 1human, consult a human-agent shared library, and contribute public creations only with prior owner permission.

Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.

Main agent orchestrator that coordinates a specialized squad of agents

Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.

Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and recoverable pipeline design.

Skill for discovering and researching autonomous AI agents, tools, and ecosystems using the AgentFolio directory.

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.

Audit a pytest suite: surviving mutants and untested code, flaky, order-dependent and slow tests, and removal candidates checked on held-out mutants. Report-only.

Check that a Python change is caught by tests: run every mutant of the changed lines and write tests until they catch them. Reports evidence instead of a diff to read.

Email infrastructure for AI agents. Create accounts, send/receive emails, manage webhooks, and inspect billing balance via the AgentMail API.

Build AI phone agents with AgentPhone API. Use when the user wants to make phone calls, send/receive SMS, manage phone numbers, create voice agents, set up webhooks, or check usage — anything related to telephony, phone numbers, or voice AI.

Generate project-specific AGENTS.md and companion rules by analyzing a codebase. Supports full, minimal, update, and dry-run modes with package-manager detection, monorepos, backups, managed blocks, confidence scoring, and command validation.

Create, revise, or audit AGENTS.md files from repository evidence, verified commands, and correctly scoped instructions without overwriting maintainer intent.

Build container-based Foundry Agents with Azure AI Projects SDK (HostedAgentDefinition). Use when creating hosted agents with custom container images in Azure AI Foundry.

Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

Delegate coding tasks to the Google Antigravity CLI (`agy`) only when the user explicitly requests it, while the orchestrator retains review and landing responsibility.

AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom agents.

Autonomous AI agent benchmark evaluation register: task completion rates, planning accuracy, tool invocation precision, and cost benchmarks.

Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls.

Use when designing or reviewing an AI agent tool registry or MCP router: document parameter schemas, caller authorization, execution limits, replay-safe retries and verification evidence.

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.

AI驱动的综合健康分析系统，整合多维度健康数据、识别异常模式、整理风险因素、提供一般性健康信息。支持智能问答和AI健康报告生成。

Install and use the official AI Audiobook Generator package, pinned by digest, for paid hosted work on the Beatra service.

Use when reviewing AI-generated code before merge or execution: plan AST/security checks, isolated behavior tests and evidence, with language-specific coverage limits.

Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.

Search indexed AI and ML jobs, inspect listings and employers, match roles, and view salary and market stats via AI Dev Jobs MCP

Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.